Minutes Matter: A Bus Transit Service Reliability Guidebook (2020)

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69 7.1 Chapter Organization Unlike the previous six chapters, this chapter is not intended to be read from beginning to end. Rather, it is designed to be a reference tool for users to locate information on specific reliability measures and treatments that may be appropriate for the user’s particular situation. Section 7.2 provides instructions on the different ways this chapter can be used to access the information contained in subsequent sections of the chapter. Section 7.3 provides a set of hyperlinked menus that can guide users to the details on the measures and treatments of interest. Section 7.4 and Section 7.5 provide detailed descriptions of the reliability measures and treatments that were discussed in more general terms in Chapter 4 and Chapter 6, respectively. 7.2 Instructions Users may make use of this chapter in several different ways. The hyperlinked menus in Section 7.3 can be used to access information on measures and treatments based on an agency’s goals and needs in terms of specific aspects and causes of reliability to be addressed, but users may alter- natively choose to browse through the various measures and treatments or may be interested in obtaining information on only one specific measure or treatment. 7.2.1 Using the Selection Menus Table 7.1 (discussed in Section 7.3.1) contains a hyperlinked menu that can be used to view detailed descriptions of the data requirements, analyses, and best usage of each of the various broad reliability measures first discussed in Chapter 4. Each of the menu’s hyperlinked choices will bring the user to a page in Section 7.4 that corresponds to the measure selected. Section 7.3.2 contains a set of tables with hyperlinked menus that can be used to view the various reliability treatments. The first menu in that section allows the user to select a specific factor that may be causing unreliability. Selecting one of the factors listed will take the user to a second menu that lists possible treatments for that factor. Selecting one of those treatments will take the user directly to the detailed description of that treatment in Section 7.5. 7.2.2 Browsing for Measures and Treatments Users interested in simply browsing through the available measures and treatments can jump to Section 7.4 and Section 7.5. Each of the broad reliability measures discussed in Chapter 4 is presented in Section 7.4 in the same order that it was listed in Table 4.2. Each of the reliability treatments listed in Table 6.1 is discussed in greater detail in Section 7.5 following the same order. C H A P T E R 7 Bus Transit Reliability Menus

70 Minutes Matter: A Bus Transit Service Reliability Guidebook 7.2.3 Searching for Individual Measures or Treatments For users interested in a specific reliability measure, the menu in Section 7.3.1 provides a listing of the measures that is hyperlinked to the pages describing each measure contained in Section 7.4. For users interested in a specific reliability treatment, a hyperlinked listing of the treatments is contained in the index at the end of this chapter. The index is hyperlinked to the pages describing each treatment contained in Section 7.5. 7.3 Reliability Selection Menus 7.3.1 Reliability Measure Selection Use Table 7.1 to select a measure based on an aspect of reliability. Selecting a measure will take the user to a discussion of the data requirements, analyses, and usage of that measure contained in Section 7.4. 7.3.2 Reliability Treatment Selection Use Table 7.2 to select a treatment based on a cause for unreliability. Table 7.3 through Table 7.7 list the reliability elements/factors in detail. Listed in Table 7.3 are reliability treat- ments related to non-operation, in Table 7.4 are reliability treatments for early/late trip start, in Table 7.5 are reliability treatments for variable travel speed, in Table 7.6 are reliability treatments for variable dwell time, and in Table 7.7 are reliability treatments for variable transfer time. 7.4 Reliability Measure Information Sheets This section contains information sheets on each of the broad reliability measures discussed in Chapter 4. Aspect of Reliability Reliability Measure Punctuality On-time performance Variability Running time Dwell time Travel time Buffer time indices Headway Wait times Non-operation Pullouts missed Missed hours of service Scheduled trips cancelled Number of crashes Mean distance between failures Multiple Passenger ratings of reliability Table 7.1. Reliability measure menu.

Reliability Elements and Factors Non-Operation Operator availability Vehicle availability Breakdowns Early/Late Start Insufficient recovery time Operator restroom breaks Holds for late connections Poor operational control Mechanical issue Variable Travel Speed Insufficient/excess scheduled time Too few/too many time points Overly long route Lack of adherence to time points Operator skill/behavior Delays merging into traffic from stops Incidents, special events, construction Traffic congestion Signal delay Weather Variable Dwell Times Too many stops/poorly located stops Poor transfer connections Uneven loading due to variable headway Demand in excess of capacity Variable passenger demand Fare payment delays Access for cyclists Access for mobility impaired Variable Transfer Times Insufficient recovery time Poor schedule coordination Poor route connectivity Table 7.2. Reliability treatment menu. Operator Availability Operational Enhanced route operational control Employ more full-time bus operators Vehicle Availability Operational Enhanced route operational control Introduce scheduled short turns Increase fleet size Policy Reliability-based fleet maintenance Breakdowns Operational Enhanced route operational control Introduce standby buses Increase fleet size Technology Bus control center Policy Reliability-based fleet maintenance Table 7.3. Treatments for non-operation.

72 Minutes Matter: A Bus Transit Service Reliability Guidebook 7.4.1 Measure: On-Time Performance Category On time/punctuality Orientation Agency/customer Data/Source(s) Actual arrival and departure times at terminals, time points, and bus stops obtained through AVL systems, supervisor logs, or manual data collection. This measure also requires scheduled times at the same terminals, time points, and stops. Calculation The scheduled arrival or departure time at a scheduled time point for a given trip is subtracted from the actual time at that time point for that trip on each day. The difference is compared to the standards set by agency policy. Insufficient Recovery Time Operational Enhanced route operational control Introduce standby buses Introduce scheduled short turns Limited-stop service Bus stop consolidation Route network adjustments Schedule and headway optimization Increase fleet size Physical Dedicated transitways and bus lanes Queue-jump lanes Operator Restroom Breaks Operational Enhanced route operational control Schedule and headway optimization Operator training, incentives, and monitoring Technology Bus control center Holds for Late Connections Operational Enhanced route operational control Route network adjustments Coordinating schedules at transfer points Technology Bus control center Real-time information systems Poor Operational Control Operational Enhanced route operational control Operator training, incentives, and monitoring Technology Bus control center Real-time information systems Mechanical Issue Operational Enhanced route operational control Introduce standby buses Increase fleet size Technology Bus control center Policy Reliability-based fleet maintenance Table 7.4. Treatments for early/late trip start.

Bus Transit Reliability Menus 73 Insufficient/Excess Scheduled Time Operational Schedule and headway optimization Increase fleet size Technology Bus control center Real-time information systems Too Few/Too Many Time Points Operational Schedule and headway optimization Overly Long Route Operational Limited-stop service Route network adjustments Divide very long routes Schedule and headway optimization Physical Dedicated transitways and bus lanes Technology Traffic signal optimization Transit signal priority Traffic Congestion Operational Route network adjustments Divide very long routes Schedule and headway optimization Coordinating schedules at transfer points Route contingency plans Enhanced route operational control Physical Dedicated transitways and bus lanes Queue-jump lanes Technology Bus control center Transit signal priority Policy Yield-to-bus laws Bus-on-shoulder operation Lack of Adherence to Time Points Operational Schedule and headway optimization Operator training, incentives, and monitoring Technology Bus control center Operator Skill/Behavior Operational Operator training, incentives, and monitoring Delays Merging into Traffic from Stops Operational Limited-stop service Bus stop consolidation Right-sizing bus stops Coordinate with traffic and parking enforcement Physical Dedicated transitways and bus lanes Far-side stop placement Curb extensions at bus stops Physical Coordinate with roadway agencies to incorporate bus-supportive features Policy Yield-to-bus laws Table 7.5. Treatments for variable travel speed. (continued on next page)

74 Minutes Matter: A Bus Transit Service Reliability Guidebook Incidents, Special Events, Construction Operational Enhanced route operational control Introduce standby buses Route contingency plans Coordinate with roadway agencies to anticipate construction impacts Technology Bus control center Real-time information systems Traffic Congestion Operational Enhanced route operational control Introduce standby buses Route network adjustments Divide very long routes Schedule and headway optimization Route contingency plans Coordinate with traffic and parking enforcement Physical Dedicated transitways and bus lanes Queue-jump lanes Coordinate with roadway agencies to incorporate bus-supportive features Technology Traffic signal optimization Transit signal priority Policy Yield-to-bus laws Bus-on-shoulder operation Signal Delay Operational Coordinate with traffic and parking enforcement Physical Dedicated transitways and bus lanes Queue-jump lanes Far-side stop placement Coordinate with roadway agencies to incorporate bus-supportive features Technology Traffic signal optimization Transit signal priority Weather Operational Enhanced route operational control Route contingency plans Table 7.5. (Continued). Analysis Typically, agencies report the percentage of trips over a period falling within an on-time window defined by agency standards. Alternatively, the standard deviation of the difference from the scheduled time can be computed over multiple trips or over a period of days. Standards Agencies set a standard defining the on-time window during which a bus is considered neither early nor late. Agencies may set multiple windows (for example, early, on-time, late, and very late). Different sized windows can also be established for different types of service. The on-time window is defined in terms of minutes before and after the scheduled time, and the percentage of bus departures (or arrivals) that occur within that window is considered on-time. The most commonly used windows are 0 to 5 minutes late and 1 minute early to 5 minutes late.

Bus Transit Reliability Menus 75 Too Many Stops/Poorly Located Stops Operational Limited-stop service Bus Stop Consolidation Right-sizing bus stops Physical Coordinate with roadway agencies to incorporate bus-supportive features Poor Transfer Connections Operational Schedule and headway optimization Increase fleet size Physical Coordinate with roadway agencies to incorporate bus-supportive features Uneven Loading Due to Variable Headway Operational Enhanced route operational control Schedule and headway optimization Physical Dedicated transitways and bus lanes Technology Transit signal priority Policy Boarding limits Demand in Excess of Capacity Operational Schedule and headway optimization Increase fleet size Physical Articulated buses Policy Boarding limits Variable Passenger Demand Operational Introduce standby buses Right-sizing bus stops Schedule and headway optimization Increase fleet size Physical Level boarding and low-floor buses Articulated buses Technology Transit signal priority Policy Boarding limits Fare Payment Delays Physical Coordinate with roadway agencies to incorporate bus-supportive features Technology Fare innovations for dwell time improvements Policy Boarding limits Public education Access for Cyclists Operational Enhanced route operational control Right-sizing bus stops Route contingency plans Physical Level boarding and low-floor buses Articulated buses Physical Coordinate with roadway agencies to incorporate bus-supportive features Policy Boarding limits Public education Access for Mobility Impaired Operational Right-sizing bus stops Route contingency plans Increase fleet size Physical Level boarding and low-floor buses Articulated buses Coordinate with roadway agencies to incorporate bus-supportive features Policy Public education Table 7.6. Treatments for variable dwell time.

76 Minutes Matter: A Bus Transit Service Reliability Guidebook Much of the debate surrounding the measurement of on-time performance since the early 1990s has revolved around the definition of this window. As evidenced by the survey conducted for this project, buses departing no more than 5 minutes late has become the most common late standard for on-time performance across much of North America and in the UK (see Figure 7.1). Agency standards for what constitutes an early trip tend to vary to a greater extent. As evidenced by the survey, most agencies consider trips to be early if they depart either before the scheduled time or more than 1 minute before the scheduled time (see Figure 7.2). Of the 10 agencies contacted for the case studies that use on-time perfor- mance as their primary reliability measure, five (RTD, CTA, LA Metro, NYCT, and SORTA) use 1 minute early to 5 minutes late for the on-time performance standard. Pierce Transit’s standard is slightly stricter at 1 minute early to 4 minutes late. Kingston does not consider any variation from the schedule time to be acceptable. VIA and Manatee did not specify their on-time window. Although any early departure, even of 1 minute, is undesirable from an arriving passenger’s standpoint, most transit agencies that use such a standard make a note in their timetables that vehicles may depart up to 1 minute early, thereby giving passengers notice of their policy. Slightly early departures can Insufficient Recovery Time Operational Introduce scheduled short turns Route network adjustments Schedule and headway optimization Increase fleet size Poor Schedule Coordination Operational Route network adjustments Coordinating schedules at transfer points Increase fleet size Poor Route Connectivity Operational Route network adjustments Coordinating schedules at transfer points Increase fleet size Table 7.7. Treatments for variable transfer time. 2% 2% 3% 6% 6% 67% 10% 3% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 0 1 2 3 4 5 6 to 10 Not Displayed Pe rc en t o f R es po nd in g A ge nc ie s Number of Minutes After Scheduled Time Figure 7.1. Agency standard for late trips.

Bus Transit Reliability Menus 77 also help maintain schedule reliability farther down a route and reduce holding delay at time points for passengers already on the bus. On-time performance standards can be applied at the start and end of a route or at intermediate time points. Agencies may want to consider a narrower window for trip start times because the trip start time tends to be more under agency control, and starting a trip as close to the scheduled time as possible can foster better on-time performance downstream by keeping headways on frequent routes more consistent, avoiding bunching and uneven loading that can exacerbate poor on-time performance. Also, while not leaving a sched- uled time point early avoids the potential problem of an on-time passenger missing a bus, early arrival at the end of a route where a layover is scheduled generally should not be treated as not on time since no passengers would be boarding there. Agencies should also consider whether they are measuring bus arrival or departure times. Departure times are the better measure from a customer perspective since boarding passengers care about what the latest time is that they can arrive at the stop. The exception would be the end of the route, where arrival times are most important to passengers and to the agency as well to monitor layover times. Determining which on-time window is the best standard for a specific agency or service is largely done based on service characteristics and the agency’s ability to achieve its stated on-time performance target (the percentage of trips within the on-time window). Usage This measure is used by most agencies. It is commonly used for public and internal agency reports on reliability and is easily understood by the public. It is useful for identifying where and when reliability problems exist and for comparing different routes or services, but it is not effective for identifying underlying causes of unreliability. Evaluation Measuring the deviation from the scheduled arrival and departure times directly addresses the definition of reliability as providing for on-time arrivals at the destination. It also can directly represent customer impacts if times are measured at stops near most customers’ destinations and not just at the end of routes. With AVL/APC systems, the data are easy and inexpensive to obtain for scheduled time points if polling is done frequently enough and the necessary infrastructure is in place to download, store, access, and report 47% 31% 10% 5% 1% 3% 1% 3% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 0 1 2 3 4 5 6 to 10 Not Displayed Pe rc en t o f R es po nd in g A ge nc ie s Number of Minutes Before Scheduled Time Figure 7.2. Agency standard for early trips.

78 Minutes Matter: A Bus Transit Service Reliability Guidebook the data. Without AVL/APC, the data are more limited and can be expensive to obtain for many destinations. The most common measures of on-time performance allow easy comparison of routes or service to specific desti- nations. Comparisons between different agencies are possible if a standard definition of the on-time window is employed. Direct comparisons to non- transit modes, such as auto travel, are not possible because nontransit modes lack a scheduled time for comparison. (Comparisons to auto travel could be based on whether the total travel time of an auto trip exceeded a desired time based on target speeds for each roadway facility type used. Auto trip times exceeding the target travel time would be considered “not on time.”) On-time performance, expressed as a percentage of trips that are on time, is a concept that is easy to communicate to all audiences; however, the measure does little to identify actions to correct poor reliability. Definition of Reliability very good Customer Impact very good Cost/Ease very good Transit Comparisons very good Multimodal Comparisons fair Corrective Actions poor Communicating Results very good Source of Added Information: TCRP Report 165: Transit Capacity and Quality of Service Manual [24], Figure 5-21. 7.4.2 Measure: Running Time Variability Category Travel time variability Orientation Agency Data/Source(s) Bus travel measured over the entire length of a bus route, but may also be calculated for route segments. Typically measured for a particular time of day, either a period or an individual scheduled trip. Obtained from AVL or similar automated data collection systems or from on-board manual observations. Calculation The variability (typically standard deviation or coefficient of variation) is calcu- lated for a route over a period. It can also be measured using a 95th percentile, 95th percentile divided by the mean, or a percentage within a specified absolute or relative range. Analysis High variability indicates that bus arrival times will be less predictable, forcing customers to allow extra time for their trips. Use of the CV, 95th percentile divided by the mean, or a percentage within a relative range allows comparisons between routes with different running times. Usage This measure was used by a majority of agencies surveyed. Statistical measures of running time reliability may not be easy to communicate to the public but can be informative for agency staff. Generally not effective for identifying underlying causes of unreliability. Evaluation Measuring the variability of running times addresses the definition of reliability as consistent travel times. It represents customer impacts only to an extent since most passengers do not ride from end to end on only one bus route. With AVL/APC systems, the data are easy and inexpensive to obtain and

Bus Transit Reliability Menus 79 usually easy to report. Without AVL/APC, the data are more limited and can be moderately expensive to obtain. Measuring running time variability with either CV, the 95th percentile divided by the mean, or as a percentage of running time within a relative range allows easy comparison of routes within an agency. Comparisons between agencies would require agreement on the exact measure to be compared. Comparisons to nontransit modes could be possible using data from commercial travel time data sets, which are becoming widely available. Statistical measures of running time reliability may not be easy to communicate to the public but can be somewhat informative for agency staff, although they do not generally in themselves provide much indication of specific corrective actions needed. Definition of Reliability very good Customer Impact good Cost/Ease very good Transit Comparisons good Multimodal Comparisons poor Corrective Actions poor Communicating Results good 7.4.3 Measure: Dwell Time Variability Category Travel time variability Orientation Agency Data/Source(s) Time spent at bus stops over the entire length of a bus route. Typically measured for a particular time of day, either a period or an individual scheduled trip. Obtained from APC systems or from on-board manual observations. May also be analyzed with corresponding ridership counts from the APC system. Calculation The variability (typically standard deviation or coefficient of variation) is calculated for a route over a period of time. Can also be measured using a 95th percentile, 95th percentile divided by the mean, or a percentage within a specified absolute or relative range. Can also be used to develop a regression model relating dwell times to boardings, alightings, and onboard passenger loads. Analysis High variability indicates that the time buses spend picking up and discharging passengers may be affecting the overall variability of running time. Stop- level dwell time can be compared to ridership (boarding, alighting, and on board) to understand whether the variation is related only to the number of boarding and alighting passengers or is due to the existing level of crowding on board the bus. Usage This measure is not commonly used, most likely due to the expense of collecting manual data or the difficulty of extracting the information from existing automated systems. It is most useful as a second-level measure to narrow down potential causes of unreliability once a high variability of over- all running times is observed. Evaluation Measuring the variability of the dwell time component of running times partially addresses the definition of reliability as consistent travel times. It only weakly represents customer impacts because most passengers will not

80 Minutes Matter: A Bus Transit Service Reliability Guidebook distinguish between the different components of running time when consid- ering the reliability of service. APC systems can distinguish the time that the door is open from the time that the door is closed. Although door-open time is not a perfect measure of dwell time, these data can provide a fair comparison between dwell (door open) time and in-motion (door closed) time. Data on variability of dwell times and the ridership served during those times can be obtained if enough buses are APC equipped. Reporting features may not be available, requiring considerable effort for the analysis. Without APCs, expensive manual data collection would be needed. Any comparison of routes within an agency or between agencies would require a consistent methodology. Statistical measures of running time component variability would not be easy to communicate to the public but would be informative for agency staff and could provide some indication of corrective actions to be explored. Definition of Reliability good Customer Impact fair Cost/Ease fair Transit Comparisons good Multimodal Comparisons poor Corrective Actions fair Communicating Results fair 7.4.4 Measure: Customer Travel Time Variability Category Travel time variability Orientation Customer Data/Source(s) Data on the actual length of a customer’s trip are much more difficult to obtain than the running time on a trip a bus makes. A customer’s trip includes all or just part of one or more bus trips and includes wait time and transfer time as well as time spent walking to and from the initial boarding stop and the destination stop. Sometimes the walk time is not included when measured by a transit agency, and so that the travel time is measured from a customer’s initial access to the system until the customer leaves the system. Data on customer travel times are more difficult to obtain than simple bus running times. Typical customer travel times can be obtained through customer surveys or regional model runs, although these will not yield a lot of data on variability. To obtain measures of variability, estimates can be made through a combination of boarding counts, AFC/ODX tools, O/D survey data, AVL/APC data, and travel demand modeling simulations. Calculation First, customer O/D data are needed. Customer surveys can be a starting point (supplemented by detailed ridership counts) to estimate the number of customers traveling from one origin stop, or set of stops, to a set of destina- tion stops, over a given period. In lieu of new data collection, trip tables from a regional model (typically developed in the same manner) can be substi- tuted. This yields ridership for each possible O/D combination. Next, AVL data are used to estimate the variability of travel time for each O/D pair, which can be a very extensive calculation, especially for trips involving transfers. To be able to combine the estimates over the entire

Bus Transit Reliability Menus 81 system, a measure such as the percentage of trip travel times within a speci- fied relative range of the mean (for example, within +25 percent of the mean) would be used, applied to the O/D ridership, and summed for the system. Alternatively, the calculation can be done for a sample of O/D pairs. Analysis High variability indicates that customer trip times will be less predictable, forcing customers to allow extra time for their trips. Usage While providing a much richer depiction of reliability as experienced by the customer, this measure is not practical for use on a routine basis and may best be left for special, one-time studies. Evaluation Measuring the variability of customer travel times most directly addresses the definition of reliability as consistent travel times. It most accurately repre- sents customer impacts. Even with AVL/APC data available, the additional requirements for data on passenger travel patterns are extensive, as is the analysis process. Without AVL/APC systems, calculating reliability would be nearly impossible. Measuring travel time variability with either CVs, the 95th percentile divided by the mean, or as a percentage of travel time within a relative range would allow comparison of different O/D patterns within an agency’s service area or between agencies. Customer travel time reliability measures, however, do not provide any indication of corrective actions needed. Comparisons to nontransit modes would be relatively easy since the measures are readily transferrable. Statistical measures of travel time reliability may not be easy to communicate to the public, although buffer time measures, discussed in the next subsection, may provide the best means to communi- cate the concept of travel time reliability. Definition of Reliability very good Customer Impact very good Cost/Ease poor Transit Comparisons very good Multimodal Comparisons very good Corrective Actions poor Communicating Results good 7.4.5 Measure: Buffer Time Indices Category Travel time variability Orientation Customer Data/Source(s) Buffer times make use of the same data as customer travel time variability. A customer’s trip includes all or just part of one or more bus trips and includes wait time and transfer time as well as time spent walking to and from the initial boarding stop and the destination stop. Customer O/D data from surveys or models are used in conjunction with detailed AVL data to model the variability for a representative set of customer O/D patterns. Calculation Buffer times relate the 95th percentile customer travel time to the mean or median travel time. Buffer times represent extra time a traveler must allow to account for variable travel times in order to arrive on time 95 percent of the time. First, customer O/D data are needed to understand ridership patterns, including transfers. Customer surveys can be a starting point (supplemented by detailed ridership counts) to estimate the number of customers traveling

82 Minutes Matter: A Bus Transit Service Reliability Guidebook from one origin stop, or set of stops, to a set of destination stops, over a given period. Next, AVL data are used to estimate the travel time for a sample of O/D pairs over a period. The 95th percentile travel time is determined and divided by the mean travel time for each pair. Several different buffer time measures are described in the literature. Varia- tions are described that are designed for different sources of data on travel patterns. One measure removes variability due to the characteristics and behavior of different travelers. Another separates normal variability due to random arrivals between buses on routes with short headways from variability due to variations in bus travel times, while another distinguishes normal variability from variability due to abnormal incidents. Analysis A high ratio indicates that customer trip times will be less predictable, forcing customers to allow extra time for their trips. Usage While providing a much richer depiction of reliability as experienced by the customer, this measure is not practical for use on a routine basis and may best be left for special, one-time studies. Evaluation Measuring buffer times directly addresses the definition of reliability as consistent travel times. It represents the additional time customers must budget for their trips to account for unreliability. Like other measurements of customer travel time, the requirements for data on passenger travel patterns are extensive, as is the analysis process. AVL/APC data are also essential. The various buffer time indices allow comparison of different O/D patterns within an agency’s service area or between agencies. Compari sons to nontransit modes would also be relatively easy for most of the various buffer time measurements. Buffer time measures may provide the best means to communicate the concept of travel time reliability to the public; however, buffer times do not provide any indication of corrective actions needed. Definition of Reliability very good Customer Impact very good Cost/Ease poor Transit Comparisons very good Multimodal Comparisons very good Corrective Actions poor Communicating Results very good 7.4.6 Measure: Headway Variability Category Wait time variability Orientation Agency Data/Source(s) Headways (time between consecutive buses on a route or corridor) measured at one or more locations along a route. Obtained from AVL systems or from manual data collection. Calculation The variability (typically standard deviation or coefficient of variation) is calculated for a route for a period over which the scheduled headway is constant. It can also be measured using a standard percentile, a standard percentile divided by the mean, or a percentage within a specified absolute or relative range.

Bus Transit Reliability Menus 83 Analysis High variability indicates bus bunching or long gaps in service. Use of the coefficient of variation or a percentage within a relative range allows comparisons between routes with different headways. Agencies need to set a standard for an acceptable level of variability. Standards The standards used to determine an acceptable headway vary. For example, NYCT and CTA both define the standard as a multiple of the scheduled headway (1.5 for NYCT and 2.0 for CTA), but both also apply an absolute maximum (no more than 3 or 5 minutes longer than the scheduled headway for NYCT, depending on time of day, and no longer than a 15-minute head- way, or less than 60 seconds, for CTA). VIA applies a standard of no more than 5 minutes longer than the scheduled headway. Usage This measure is commonly used by agencies, especially on routes with shorter headways (typically less than 10 or 15 minutes). The threshold values used vary from agency to agency. Among case study agencies, NYCT uses a threshold of 10-minute headways, while VIA and Transport for London use a threshold of 12-minute headways. Statistical measures of headway reli- ability may not be easy to communicate to the public but can be somewhat informative for agency staff. Not effective for identifying underlying causes of unreliability. Evaluation Using the variability of headways as a surrogate for wait times partially addresses the definition of reliability as short and consistent wait times but fails to account for the variation in the number of passengers per trip that can be a direct result of uneven headways. Thus, it represents customer impacts only to an extent, since longer headways tend to be experienced by a much larger share of customers. With AVL/APC systems, the data are easy and inexpensive to obtain for time points, but APC data that are simultaneously collected on all buses on a subject route would probably be needed to assess other stops. Ease of reporting depends on available reporting features. Without AVL/APC systems, the data are more limited and can be moderately expen- sive to obtain. Measuring headway variability with CVs, the 95th percentile divided by the mean, or as a percentage of headways within a relative range allows easy comparison of routes within an agency or between agencies. Headway measurement also allows comparison between schedule-based transit services and frequency-based services. Comparisons to nontransit modes are not possible because nontransit modes lack the concept of a headway. Statistical measures of headway reliability may not be easy to communicate to the public but can be somewhat informative for agency staff, although they do not generally in themselves provide an indication of corrective actions needed. Definition of Reliability good Customer Impact good Cost/Ease good Transit Comparisons very good Multimodal Comparisons poor Corrective Actions poor Communicating Results fair Source of Added Information: TCRP Report 165: Transit Capacity and Quality of Service Manual [24], Figure 5-22.

84 Minutes Matter: A Bus Transit Service Reliability Guidebook 7.4.7 Measure: Customer Wait Time Variability Category Wait time variability Orientation Customer Data/Source(s) Headways (time between consecutive buses on a route or corridor) measured at one or more locations along a route. Obtained from AVL systems or from manual data collection. Ridership by trip obtained either from actual ridership counts from AVL/APC systems or, for headway-based ser- vices, from an assumed constant arrival rate for a known number of pas- sengers over a period of consistent scheduled headways. AFC/ODX tools can also provide more accurate estimates of wait times for transferring passengers. Calculation The estimation of customer wait times is an attempt at a more accurate repre- sentation of wait time experienced by customers than that provided by simple headways. With random arrivals of customers on high-frequency services, as wait times vary, longer intervals between buses will be experienced by a larger share of customers. The average wait time for each observed trip is assumed to be half the observed headway. The number of boardings on each trip (if not actually observed) is estimated as the observed headway, divided by the length of the period, times the total ridership in the period. Each assumed wait time is weighted by the estimated number of riders on that trip in calculating variability. Excess wait time is a related measure that can be measured by sub- tracting the expected wait time (usually half of the headway for headway-based services, or a fixed value for schedule-based services) from the observed wait time per passenger. Wait time variability can be measured using a coefficient of variation, a standard percentile, a standard percentile divided by the mean, or a percentage within a specified absolute or relative range. Analysis High variability indicates bus bunching or long gaps in service. Use of the coefficient of variation or a percentage within a relative range allows com- parisons between routes with different headways. Agencies need to set a standard for an acceptable level of variability. Usage This measure provides a better assessment of the wait time experienced by customers than does headway variability. Not commonly used due to the stop-level ridership data required. Used on routes with shorter headways (typically less than 10 or 15 minutes). Statistical measures of headway reliability may not be easy to communicate to the public but can be somewhat infor- mative for agency staff. Not effective for identifying underlying causes of unreliability. Evaluation Measuring the variability of customer wait times most directly addresses the definition of reliability as short and consistent wait times and most accurately represents customer impacts. Assessing wait times using actual bus arrival times from AVL/APC data and assuming random arrivals of passengers requires a moderate amount of data manipulation. (Using actual passenger arrival times would require a more considerable amount of APC data manipulation. To do so would require all buses on a subject route to be APC-equipped while the data are collected.) Measuring wait time variability with CVs, the 95th percentile divided by the mean, or as a percentage of scheduled wait time within a relative range would allow

Bus Transit Reliability Menus 85 comparison of different origin/destination patterns within an agency or between agencies. Comparisons are possible to nontransit modes. How- ever, only some nontransit modes have wait times. For example, driving one’s car or cycling typically does not involve waiting, while taxis and many of the newer ride sourcing options provided by transportation network companies require the user to wait for the vehicle to arrive. Statistical measures of wait time reliability may not be easy to communicate to the public; how- ever, route-level measures of excess wait time caused by unreliability could be easily understood by the public. Customer wait time reliability measures do not provide any indication of corrective actions needed. Definition of Reliability very good Customer Impact very good Cost/Ease fair Transit Comparisons very good Multimodal Comparisons poor Corrective Actions poor Communicating Results good 7.4.8 Measure: Pullouts Missed Category Operation Orientation Operator Data/Source(s) Dispatcher reports and schedules Calculation The number of scheduled bus pullouts from the garage or depot that fail to operate is divided by the number of scheduled pullouts for a particular period of days, weeks, or months. Analysis Any missed service results in longer customer wait times, particularly on low-frequency routes. A high percentage of missed pullouts indicates a need to examine vehicle and operator availability. Usage Missed pullouts are most commonly examined at the system or depot level and, somewhat less commonly, at the route level. Evaluation Missed pullouts do not directly address most definitions of reliability that are customer oriented since they only indirectly measure customer impacts. This measure is, however, routinely collected by most agencies and provides easy comparison across routes and agencies, but it does not provide any basis for a multimodal comparison. It may provide clear indication on the causes of some cases of unreliability, although identifying corrective actions would require additional investigation. Missed pullouts may not be as easily under- stood by the public as trips cancelled, although the measure is meaningful to those directly involved in transit operations. Definition of Reliability fair Customer Impact fair Cost/Ease very good Transit Comparisons very good Multimodal Comparisons poor Corrective Actions fair Communicating Results fair

86 Minutes Matter: A Bus Transit Service Reliability Guidebook 7.4.9 Measure: Missed Hours of Service Category Operation Orientation Operator Data/Source(s) Dispatcher reports, supervisor logs, and schedules Calculation The number of hours of service is determined from agency reports and divided by the number of scheduled hours of service, either for a route or system wide, for a particular period. Analysis Any missed service results in longer customer wait times, particularly on low- frequency routes. Missed hours of service may be the most accurate measure of missed service, although the measure may not be routinely calculated by most agencies. A high percentage of missed hours of service indicates a need to examine vehicle and operator availability. Usage The measure of missed hours of service is most commonly examined at the system or depot level and, somewhat less commonly, at the route level. Evaluation The measure of missed hours of service does not directly address most defi- nitions of reliability that are customer oriented since it only indirectly mea- sures customer impacts. It does, however, provide easy comparison across routes and agencies, but it does not provide any basis for a multimodal comparison. It can provide clear indication of the causes of some cases of unreliability, although identifying corrective actions would require addi- tional investigation. It may be understood, to some extent, by members of the public, but is probably not as easily understood as missed trips. Definition of Reliability fair Customer Impact fair Cost/Ease very good Transit Comparisons very good Multimodal Comparisons poor Corrective Actions fair Communicating Results fair 7.4.10 Measure: Scheduled Trips Cancelled Category Operation Orientation Operator Data/Source(s) Supervisor logs and schedules Calculation The number of trips cancelled (or otherwise not made) is divided by the number of scheduled trips, either for a route or system wide, for a particular period. Analysis Any missed service results in longer customer wait times, particularly on low-frequency routes. Canceled trips can be an accurate measure of missed service, and this measure is routinely calculated and reported by most agen- cies, typically as percentages of scheduled service. A high percentage of missed or cancelled trips indicates a need to examine vehicle and operator availability and may also indicate excessive running times that result in fewer trips provided with the same number of hours of service.

Bus Transit Reliability Menus 87 Usage The measure of cancelled trips is most commonly examined at the system level and route level and, somewhat less commonly, at the trip level. Evaluation The measure of canceled trips does not directly address most definitions of reliability that are customer oriented since it only indirectly measures customer impacts. It is, however, routinely collected by most agencies and provides easy comparison across routes and agencies, but it does not provide any basis for a multimodal comparison. It can provide clear indication of the causes of some cases of unreliability, although identifying corrective actions would require additional investigation. This measure can be easily under- stood by the public and is useful for transit operations. Definition of Reliability fair Customer Impact fair Cost/Ease very good Transit Comparisons very good Multimodal Comparisons poor Corrective Actions fair Communicating Results fair 7.4.11 Measure: Crashes Category Operation Orientation Operator Data/Source(s) Crash reports and reports of scheduled miles or hours of service. Calculation The number of crashes reported over a period is divided by the number of scheduled miles or the hours of service. Analysis Crashes result in delays and missed service, which in turn result in longer customer wait times. A high crash rate indicates a significant number of substantially delayed trips as well as a need to examine operator performance and training. It may also indicate difficult operating conditions that should be addressed. Usage Crash counts and rates are most commonly examined at the system level, although they are likely also used to examine specific operator performance. Examination of route- or period-level data would be useful in identifying difficult operating conditions. Evaluation Counts of crashes do not directly address the definition of reliability, nor do they directly measure customer impacts. They are, however, routinely collected by most agencies and provide easy comparison between agencies, agency divisions, and sometimes between routes. Crashes occur in all modes of travel, so it is possible to complete a multimodal comparison of crash- related disruptions. Crash reports may provide a clear indication of the causes of some cases of unreliability, and may, depending on the actual data collected, identify the types of corrective actions that may be needed. The impact that crashes have on reliability may not be directly understood by the public. Definition of Reliability fair Customer Impact fair Cost/Ease very good

88 Minutes Matter: A Bus Transit Service Reliability Guidebook Transit Comparisons very good Multimodal Comparisons good Corrective Actions good Communicating Results fair 7.4.12 Measure: Mean Distance Between Failures Category Operation Orientation Operator Data/Source(s) Maintenance reports and reports of scheduled miles or hours of service. Calculation The number of mechanical or other failures reported over a period is divided by the number of scheduled miles or the hours of service. Analysis Mechanical failures result in delays and missed service, which in turn result in longer customer wait times. A high failure rate indicates a significant number of substantially delayed trips as well as a need to examine mainte- nance practices. Usage Failure counts and rates are most commonly examined at the system or depot level or for specific fleets of vehicles. Evaluation The measure of mean distance between failures does not directly address the definition of reliability and does not directly measure customer impacts. It is, however, routinely collected by most agencies and provides easy comparison between agencies and agency divisions. It can provide clear indication of the causes of some cases of unreliability, and may, depending on the actual data collected, identify the types of corrective actions that may be needed. The measure’s impact on reliability may not be easily understood by the public and may only be meaningful to those directly involved in transit operations. Definition of Reliability fair Customer Impact fair Cost/Ease very good Transit Comparisons very good Multimodal Comparisons poor Corrective Actions good Communicating Results fair 7.4.13 Measure: Passenger Ratings of Reliability Category Multiple Orientation All Data/Source(s) On-board or bus-stop customer surveys, telephone and online surveys, social media platforms, and public meetings. Calculation Ratings can be calculated as the percentage of responses with a certain rating or above or below a certain rating value. Analysis Passenger surveys can be designed to address the overall travel experience or specific elements of service reliability. Feedback obtained through social media is a growing source of data on customer perceptions of reliability. Reliability and the perception of reliability are not the same. While data

Bus Transit Reliability Menus 89 measure reliability, it is customers’ perceptions of reliability that affect their travel choices. Passenger ratings provide insight into customers’ perceptions of reliability rather than measure reliability directly. Multiple surveys over a given period can provide insight into whether reliability improvement treat- ments are being noticed by customers and, therefore, have the potential to affect ridership. Usage Surveys are generally conducted at the system level but can also be focused on specific routes or corridors. Evaluation Customer surveys can be designed to directly assess the perceived impacts on customers of all components of reliability. When combined with data collection for other measures, the difference between actual and perceived reliability can be observed. Passenger surveys can require extensive data col- lection efforts, although Internet-based survey techniques can reduce data collection costs. Analysis of survey data can be straightforward, although comparison to actual observed reliability can be more complex. Comparisons within an agency would be straightforward, but comparisons to other agencies would require standardized survey instruments. Multimodal comparisons of perceptions are possible. Survey instruments can be designed to identify areas where the most impact can be achieved, although specific corrective actions are not likely to be apparent. Survey results can generally be understood by the public. Definition of Reliability very good Customer Impact very good Cost/Ease fair Transit Comparisons good Multimodal Comparisons good Corrective Actions fair Communicating Results very good 7.5 Reliability Treatment Information Sheets This section contains information sheets on each of the reliability treatments noted in Chapter 6. The menus in Section 7.3.2 may be used to identify appropriate treatments for specific observed causes of unreliability. 7.5.1 Operational Treatment: Enhanced Route Operational Control Description: The most fundamental strategy to improve reliability is effective operational controls. This can be accomplished either by street supervision, well-trained personnel in a command center, or both. Supervisors will be able to identify and re-instruct bus operators, respond to incidents such as crashes, establish detours around utility work, assist customers, manage road relief, and confirm that schedules are achievable. Following are some of the basic strategies available to supervisors: • When street supervisors are faced with an immediate service issue such as a fire or utility work that is causing delays to bus service, unscheduled short turns may need to be implemented. A trip that is short turned does not complete the full route; rather, the bus turns around at a logical location. • When a bus is operating ahead of schedule, supervisors may direct the bus operator to hold for time to maintain even spacing with the vehicle ahead and the vehicle following.

90 Minutes Matter: A Bus Transit Service Reliability Guidebook • The real-time deadheading strategy directs bus operators to terminate their trip mid-route and immediately head to a time point or terminal or to leave a terminal empty and run express to a time point farther downstream. This treatment must be handled by supervision or a command center; it should not be initiated by bus operators. This treatment is useful when there are big gaps in service due to a vehicle breakdown or special events. Causes of Unreliability Addressed: Excessive running time, travel time variability, special events Companion Treatments: Route network adjustments, divide very long bus routes, introduce scheduled short turns, enhanced route operational control Treatment Trade-Offs: Unscheduled short turns and partial deadheading can improve system- wide reliability, but local service delivery as observed by customers will suffer in the area. While such strategies can help to address short-term operational challenges, they should be applied with discretion because bypassing stops causes profound distress for customers. For example, in the instance where a fire or utility work has resulted in three buses all being in the same vicinity, it is prudent to send one or two buses to operate nonstop to downstream time points. This should not be done as an everyday practice. Attempts to meet established operational performance goals should never result in impaired service to customers. Expected Effect: High; effectively addresses irregular delays in service Capital Cost: None Operating Cost: None, if a supervisory mechanism is in place on the route Ease of Implementation: Easy. These techniques are regular tools that should be deployed by road supervisors. 7.5.2 Operational Treatment: Introduce Standby Buses Description: Many agencies deploy spare buses (known in the industry by various terms such as “gap,” “standby,” “loop,” or “run-as-directed” buses; see Figure 7.3) at critical locations— a transit center, a downtown core, a peak load point, and so forth—to be deployed by supervisors in the event of an interruption in service. This can be done on a regular basis in peak periods or for special events such as the end of a game or parade. Typically, if a service problem does not arise, the bus operator will be asked to make a revenue trip on a busy bus route. Source: WSP USA. Figure 7.3. Standby buses.

Bus Transit Reliability Menus 91 Causes of Unreliability Addressed: Non-operation, early/late start Companion Treatments: Enhanced route operational control Treatment Trade-Offs: There can be trade-offs between scheduling a bus and operator as part of the regular schedule to offer higher frequency of service versus holding a bus and operator in reserve to be used to improve reliability. Expected Effect: Moderate; can effectively address unexpected gaps/delays in service Capital Cost: None Operating Cost: There is a cost for keeping a bus and bus operator on standby. Ease of Implementation: Easy; this is completely under agency control. 7.5.3 Operational Treatment: Introduce Scheduled Short Turns (Cut-Routes) Description: A trip that is short turned does not complete the full route; rather, the bus turns around at a logical location. When buses are not able to go the full route because of recurring heavy traffic or heavy boarding, some transit agencies will introduce a pattern of scheduled short turns (also called “cut-routes” or “turn-backs”). It may be that the schedule has half of the trips on a route going end-to-end and half of the trips tuning around at a hospital, college, or another major trip generator. Causes of Unreliability Addressed: Variable travel speed Companion Treatments: Route network adjustments, divide very long bus routes Treatment Trade-Offs: Introducing scheduled short turns can improve system-wide reliability, but local service delivery as observed by customers will suffer in the area beyond the short-turn point. In one study, short turning improved running times but made headway variation worse [24]. A further challenge with introducing short turns is that buses on the full-length trips are inevitably more crowded than the bus on the short-turned trip because they serve more destina- tions [25]. Expected Effect: High; can effectively address regular delays in service Capital Cost: None Operating Cost: None Ease of Implementation: Easy. Introducing scheduled short turns involves changing the schedule, which is typically done only 3 to 4 times per year during a regular system-wide schedule update. 7.5.4 Operational Treatment: Limited-Stop Service Description: Limited-stop service is the practice of introducing alternate services that only stop at principal bus stops. These services usually operate in companion with the regular all- stop service. The purpose of limited-stop service is to provide an express-type service that better serves longer-distance trips. Buses travel faster because they save the dwell time associated with each local stop. Causes of Unreliability Addressed: Variable travel speed Companion Treatments: Transit signal priority, bus stop consolidation

92 Minutes Matter: A Bus Transit Service Reliability Guidebook Treatment Trade-Offs: Customers traveling longer distances and customers traveling between principal bus stops will benefit from limited-stop service. However, customers traveling between lightly used local bus stops will see less-frequent service. It is important to confirm that everyone is served with an appropriate level of service. Expected Effect: Moderate. The results of a study in Montreal, Quebec, indicated that imple- mentation of limited-stop service along a heavily used bus route could improve running time for both the regular and express routes. The authors attributed the time savings to a shift in passenger activity toward the express service [5]. Another study of the same system revealed that limited-stop service decreased the likelihood of being late by 66 percent [26].Generally, the introduction of limited-stop service on a busy urban bus route can achieve time savings in the order of 10 to 15 percent [6]. This results from making fewer stops, of course, but also, by stop- ping less frequently, buses can take advantage of traffic signal progression. Capital Cost: None Operating Cost: If the existing service is divided, with half the buses operating all-stop and half the buses operating limited-stop, then there is no cost increase. If a local route is converted to limited-stop service, there could be a reduction in cost. However, if limited-stop service is implemented as an overlay above all-stop service, then there would be a significant operating cost increase. Ease of Implementation: Limited-stop service is moderately easy to implement. It involves changing the schedule, which is typically done only 3 to 4 times per tear during a regular system- wide schedule update. Determining which stops should be limited-stop requires accurate trip O/D data. There needs to be robust public engagement to explain the difference in stopping patterns to the public. 7.5.5 Operational Treatment: Bus Stop Consolidation Description: Where bus stops are very close together or have very low patronage (or both), combining two or more bus stops into one can reduce the number of times that a bus must stop on a given trip. Causes of Unreliability Addressed: Variable travel speed, variable dwell times Companion Treatments: Right-sizing bus stops Treatment Trade-Offs: Eliminating bus stops, even those that are very lightly used, will likely result in customer complaints and opposition. Eliminating stops can increase the walking distance required for customers to access buses, which can be problematic in areas where side- walks are lacking or for customers with limited mobility. Expected Effect: Moderate; depending on the extent of consolidation, could improve reliability by reducing the variability of running time. Capital Cost: Low; mostly sign removal unless shelters must be relocated Operating Cost: None Ease of Implementation: Easy. This is an inexpensive administrative action. All bus stop consolidations require public engagement to ensure that sensitive populations are not hurt. Transit agencies should have bus-stop spacing guidelines in place before embarking on a stop reduction program. Sources of Additional Information: TCRP Report 117: Better On-Street Bus Stops [28], TCRP Report 165: Transit Capacity and Quality of Service Manual [24], TCRP Report 183: A Guidebook on Transit-Supportive Roadway Strategies [29]

Bus Transit Reliability Menus 93 7.5.6 Operational Treatment: Right-Sizing Bus Stops Description: Particularly in downtown areas where curb space is scarce, some transit agen- cies are forced to operate with bus stops that are too short to accommodate the number of buses that call there. When bus stops are too short, dwell times increase dramatically; even worse, however, is when buses cannot get to the curb at all, and customers must board from the street. This has the effect of reducing street capacity, which slows bus travel speeds further. Where it is physically impossible to lengthen stops, it may become necessary to introduce a downtown stopping pattern where not every bus route calls at every stop. In extreme cases, it may be necessary to reroute some services to a parallel street. Figure 7.4 shows an enlarged bus stop. Causes of Unreliability Addressed: Variable travel speed, variable dwell times Companion Treatments: Far-side bus stops Treatment Trade-Offs: Allocation of scarce curb space involves trade-offs with other uses, such as parking, deliveries, bike share, and curb extensions. Stops that are too short can delay buses, while those that are too long invite abuse by other street users. Expected Effect: Low; could provide improvement in dwell time and reliability for the area Capital Cost: None, unless shelters must be relocated Operating Cost: None Ease of Implementation: Easy, if the municipality is agreeable. Where curb space is tight, getting the municipality to agree to lengthen stops can be difficult. If it can be demonstrated that queuing buses are delaying all traffic, then the argument is easier to make. In some instances, bus stops may be too long; when this is the case, the stop signage may be ignored, and delivery trucks may end up using the stop as a loading zone. Sources of Additional Information: TCRP Report 117: Better On-Street Bus Stops [28], TCRP Report 165: Transit Capacity and Quality of Service Manual [24], TCRP Report 183: A Guidebook on Transit-Supportive Roadway Strategies [29] Source: WSP USA. Figure 7.4. An enlarged bus stop.

94 Minutes Matter: A Bus Transit Service Reliability Guidebook 7.5.7 Operational Treatment: Route Network Adjustments Description: There are minor route or network changes that could be implemented to improve system performance. These changes could be minor adjustments to address spot issues. Transit agencies could improve reliability by being proactive to move bus stops and make minor route adjustments to avoid intersections or locations that contribute to unreliability. On the other hand, the changes could involve neighborhood route restructuring initiatives or even complete system redesigns. An early study by Turnquist and Bowman found through modeling and simulation that grid networks are less disrupted by transfers than radial networks. Nevertheless, on-time arrival of vehicles at major transfer stations was also found to be important, especially for radial networks [19]. Yao and collaborators proposed a network optimization model that took travel time reli- ability into account. The results indicated that this method could help to improve transit net- work reliability while reducing customer travel times [30]. Reducing the number of branches or different paths on a route can have a notable improve- ment in reliability. First, it is likely that different branches will have different travel times and different loading profiles. Thus, when buses from different branches merge onto the trunk corridor, they may not be evenly spaced, and customer boarding is also likely to be uneven. Introducing special route paths for needs such as a factory shift change or school dismissal makes good sense. To have such paths operate all day introduces the same types of issues as route branches. Causes of Unreliability Addressed: Variable travel speed, variable dwell times, inconsistent transfer times Companion Treatments: Limited-stop service, introduce scheduled short turns Treatment Trade-Offs: Making broad changes to network structure is a lengthy process involving extensive data collection, customer input, and robust public engagement with many groups of stakeholders. It is understood that effective public engagement will result in a far better network redesign. Expected Effect: Low/moderate, depending on the complexity of the route network changes. (Bus stop relocations would be expected to have a minor effect, while straightening routes and reducing branches would be expected to have a major effect.) Capital Cost: None, unless bus stops and shelters need to be relocated Operating Cost: Low; if service is rationalized in an effective manner, operating costs can be reduced. Ease of Implementation: Easy/difficult, depending on the complexity of the changes. Relo- cating bus stops is straightforward but requires public engagement. Complete network redesign projects are time-consuming and require extensive data collection and analysis. A continuous, open-door public engagement process with customers, employers, chambers of commerce, elected officials, and labor is needed. 7.5.8 Operational Treatment: Divide Very Long Bus Routes Description: Many North American transit agencies have improved reliability in particular corridors by dividing very long bus routes into two services. In some cases, the route division is done with an overlapping segment. The overlap—typically through the busiest route segment— limits the impacts on customers by reducing the number of customers who would otherwise have to transfer to complete their trips.

Bus Transit Reliability Menus 95 Through simulation and a case study of the Land Transport Authority in Singapore, Lee et al. [33] found that unreliability increased with bus line travel distance in a positive linear fashion. Simulation was used to show that the level of service was improved with shorter operating distances in terms of customers’ average waiting time and bus occupancy. A study in Beijing, China, found that shorter route lengths [less than 30 km (18.6 miles)] yielded better reliability than longer routes for three measures of reliability [31]. There are few local bus routes in North America that exceed this route length, but it stands to reason that very long bus routes would be more prone to variability. Causes of Unreliability Addressed: Variable travel speed Companion Treatments: Route network adjustments, introduce scheduled short turns, limited-stop service Treatment Trade-Offs: Van Nes and van Oort explored the trade-offs between long routes that avoid the need for transfers and short routes that reduce the opportunity for delay propaga- tion [75]. Their paper modeled the impact of splitting routes into shorter segments and evalu- ated the impact on waiting time. They found that the benefit of splitting routes was maximized at those stops with few passengers riding through. Expected Effect: Moderate, since reliability has been shown to increase when bus line travel distance decreases [31] Capital Cost: There is no capital cost involved with splitting long routes into two shorter routes. If the route division includes a section of overlap to reduce transfers, there could be an increase in the number of buses required in the peak hours. Operating Cost: Splitting one long route into two routes will generally involve a small increase in operating costs. If there is a route overlap, the increase in operating costs will be greater. If one end of a very long route is much less busy than the other end of the route, breaking the service into two routes could result in cost savings. This could happen, for instance, if one end of the route requires a bus every 10 minutes, and the other end of the route only needs a bus every 30 minutes. Ease of Implementation: Moderate. This is an administrative action, but dividing a route into two shorter routes can be met with significant opposition. Extensive public engagement is required to accomplish this in a manner that does not harm sensitive populations. 7.5.9 Operational Treatment: Schedule and Headway Optimization Description: Every transit agency makes routine schedule and headway adjustments to reflect changing ridership levels and travel times. Sometimes travel time adjustments are only needed between a handful of time points or at a particular time of day. There are instances, however, where conditions have changed so dramatically that an entire route, or family of routes, must be completely rescheduled. Adjusting schedules to reflect actual travel times can result in operators being better able to stay on schedule, while allowing adequate recov- ery times at route endpoints allows each trip to start on time even if the previous trip was delayed. Causes of Unreliability Addressed: Variable travel speed, variable dwell time Companion Treatments: Limited-stop service, divide very long bus routes Treatment Trade-Offs: Research has found that shortening the distance between time points seems to be an effective method for improving bus service reliability [33]. If, however, buses are frequently held at time points, it will slow operating speeds and lead to customer

96 Minutes Matter: A Bus Transit Service Reliability Guidebook dissatisfaction. An analysis of the Translink system in Brisbane, Australia, showed that the route segments found to be at highest risk for reliability incidents were long, highly produc- tive bus segments [34]. TCRP Report 135: Controlling System Cost: Basic and Advanced Scheduling Manuals and Contemporary Issues in Transit Scheduling [35] highlights the conflicting objectives of main- taining short scheduled running times and reliability. The report suggests setting the sched- uled running time at the 93rd percentile of observed values [36]. Turnquist and Bowman found through modeling and simulation that variability in time associated with making a transfer, which is directly influenced by frequency of service, has a major impact on transit system reliability. They stated that, in general, transit agencies should avoid providing excess buffer time in their schedules except where many customer transfers could benefit from having enough time to ensure successful connections [19]. More recently, Hong noted many trade- offs in the scheduling process. He found that headway decisions affect the trade-off between operational cost and service quality, both of which increase with smaller headways. Increasing schedule time and the number of time points can reduce deviation at time points, thereby improving schedule adherence. While this may help to reduce out-of-vehicle waiting times, it may slow in-vehicle travel times [37]. Expected Effect: Low/moderate, depending on feasibility. (If optimized schedule/headway is feasible, reliability improvements can be expected, but if optimized schedule/headway is not feasible, no reliability improvements can be expected.) Capital Cost: Typically none, but if additional peak buses are needed, then there will be a corresponding increase in capital cost. Operating Cost: Very low. If, however, significant improvements in headway are necessary, then there would be an increase in operating costs. Ease of Implementation: Easy. Schedule adjustments are administrative actions and are easy to implement. Sources of Additional Information: TCRP Report 135: Controlling System Costs: Basic and Advanced Scheduling Manuals and Contemporary Issues in Transit Scheduling [35]. 7.5.10 Operational Treatment: Coordinate Schedules at Transfer Points Description: Coordinating schedules among different routes is meant to facilitate connec- tions for customers transferring between routes. A common approach to schedule coordina- tion is to pulse departures on multiple routes simultaneously from a hub station. Transit connection protection (TCP) is a related technique. It is a real-time adjustment allowing buses to wait for each other at hub stations where many customers are known to transfer. TCP typically uses real-time information to decide whether to hold connections for a late-arriving bus. At some transit agencies, the control center informs all buses at a transit center to wait for a late-arriving bus on one route. Likewise, connecting customers should be informed about late-arriving buses. Causes of Unreliability Addressed: Inconsistent transfer times Companion Treatments: Schedule and headway optimization, enhanced route operational control Treatment Trade-Offs: Coordinating schedules may require holding vehicles to wait for connecting vehicles, which may cost scarce revenue hours.

Bus Transit Reliability Menus 97 Expected Effect: Varying; could be detrimental to bus operations but positive on the predict- ability of travel times for customers Capital Cost: None Operating Cost: Holding buses at transit centers could result in a minor increase in operat- ing costs. Ease of Implementation: Easy; this is an administrative action, which is easy to implement. Sources of Additional Information: TCRP Report 135: Controlling System Costs: Basic and Advanced Scheduling Manuals and Contemporary Issues in Transit Scheduling [35]. 7.5.11 Operational Treatment: Bus Operator Training, Incentives, and Monitoring Description: Bus operator training, incentives, and monitoring can help improve bus operators’ skill, customer interactions, and desire to offer reliable service. Training can address the lack of experience among bus operators. Two critical issues in public transportation today are fatigue and distraction. Obviously, bus operators must never use personal electronic devices while driving, but enforcement can be difficult. Even if no crashes occur, if bus operators are distracted, they will not drive as effectively as they should, and reliability will suffer. Fatigue, on the other hand, is much harder to define and control. Federal rules limit the number of hours that bus operators may drive in a day and further specify time off between shifts, but what mechanisms are in place to ensure that bus operators have had adequate rest before coming to work? As is the case with distracted driving, if bus operators are fatigued, performance will suffer, and reliability may also be affected. Given the vehicle diagnostic tools available on today’s buses, it is possible to remotely monitor certain aspects of bus operator performance. While such techniques should be used with care, in an instance where there may have been a complaint about hard braking or overly fast accelera- tion, such tools can be valuable. Additional street supervision normally results in improved reliability. Bus operators, like most employees, perform better when observed, and given instruction, by a supervisor. It is expected that actions taken by supervisors will improve reliability, but it is first necessary for supervisors to be properly trained so that the actions taken (e.g., short-turning buses, directing operators to skip certain stops) are beneficial to customers. Causes of Unreliability Addressed: Non-operation, early/late start, variable travel speed Companion Treatments: Employ more full-time bus operators Expected Effect: Minor. Enhanced bus-operator training will yield improvements in safety, reliability, and customer satisfaction. Bus operator training, support, and incentives have been shown to have a positive impact on bus service reliability [16, 18, 20, 34, 38, 39]. Capital Cost: None, unless the transit agency determines that it needs a bus simulator (or similar tool) to help with training Operating Cost: Operating cost is low. It is expected that all transit agencies have a training department. Ease of Implementation: Moderate. These are administrative actions, but buy-in from labor is necessary. Sources of Additional Information: APTA Report: Recommended Practice for Transit Bus Operator Training [76], TCRP Synthesis 108: Transit Bus Operator Distraction Policies [40]

98 Minutes Matter: A Bus Transit Service Reliability Guidebook 7.5.12 Operational Treatment: Route Contingency Plans Description: Route contingency plans address temporal disruptions such as crashes, weather, and special events. Contingency plans are processes that can be applied from the stop to the agency level. Contingency plans can make bus operations more resilient and safe in cases of emergency. A route contingency plan can address practically any circumstance, but typically address items such as: • Standard detours for annual special events such as parades, street festivals, or footraces; • Standard detours for heavy snow when buses may not be able to operate up or down steep grades; • Revised operating procedures for sporting events; • Special procedures at dismissal times at certain schools or large houses of worship; and • Procedures for operation during blackouts (no traffic signals), floods, or other emergencies. Causes of Unreliability Addressed: Non-operation, variable travel speed Companion Treatments: Enhanced route operational control Treatment Trade-Offs: Increased staff effort for developing plans and keeping them updated Expected Effect: Varying; minimal impact expected on day-to-day system operations, but high impact expected on special events or problems Capital Cost: None Operating Cost: Minimal cost to create the plans Ease of Implementation: Easy, but participation and consensus is needed from all depart- ments. All parties must know where the plans reside in hard copy and electronic formats. 7.5.13 Operational Treatment: Increase Fleet Size Description: The number of vehicles available is a factor in reliability because it determines the amount of service that can be provided at one time. An old fleet (average age over 10 years) is prone to technical failure, and the fleet size can be a constraining factor in providing sufficient service to fulfill reliability expectations. Increasing the number of buses in the fleet (Figure 7.5) will allow for a greater spare factor and thus make it easier to meet daily bus requirements. Transit agencies typically maintain a spare ratio in the range of 15 percent. (If 100 peak-hour buses are required, the fleet size should be approximately 115.) If dedicated fleets are required (e.g., a small fleet of articulated buses), then the spare ratio for a small fleet may need to be 20 percent. Causes of Unreliability Addressed: Non-operation, early/late start Companion Treatments: Employ more full-time bus operators Source: WSP USA. Figure 7.5. An expanded bus fleet.

Bus Transit Reliability Menus 99 Treatment Trade-Offs: Buying additional buses to improve vehicle availability involves trade- offs with maintenance efforts and costs. A bigger fleet means more buses to maintain. A larger bus fleet would necessitate additional maintenance personnel and resources. Expected Effect: High; could improve reliability if shortage of buses is causing unreliability. However, increasing fleet size should not be used to mask maintenance problems because a larger fleet will only make maintenance issues more profound. Capital Cost: Substantial. Buying buses is the biggest cost for many transit agencies Operating Cost: An increase in operating cost will be required to maintain the larger fleet. Ease of Implementation: Difficult. Increasing fleet size is expensive and time-consuming. 7.5.14 Operational Treatment: Employ More Full-Time Bus Operators Description: The availability of bus operators can be a factor affecting reliability. Conventional wisdom suggests that full-time employees will be more dependable than part-time employees. Full-time bus operators are also available for more scheduled and on-call shifts. The availability of on-call (spare) bus operators conditions the transit agency’s ability to respond to absenteeism. Transit agencies typically have a list of spare bus operators at each depot/division to fill in for sick, absent, or vacationing employees. The spare list (also called the extra list or spare board) should be large enough to cover absences on most days. An associated strategy is to confirm that the size of the transit agency’s spare list is adequate to cover typical daily absenteeism. Typically, the number of spare bus operators is set forth in the labor contract. If the number of spare operators is too high, staff resources are wasted. If the number is too low, then the agency will not be able to respond effectively to daily absences. Causes of Unreliability Addressed: Non-operation, early/late start Companion Treatments: Increase fleet size Treatment Trade-Offs: In most instances when part-time bus operators are employed, it is because service is heavily peaked and thus it is effective to have employees who just work in the morning or afternoon peak periods. Using part-time bus operators normally yields significant financial savings to the transit agency. Switching to more full-time bus operators may increase reliability but would typically result in increased operating costs. Expected Effect: Low; optimizing the size of the spare/extra list will result in improved reliability. Capital Cost: None Operating Cost: Increased costs Ease of Implementation: Difficult. Hiring and training staff are time-consuming and expensive. 7.5.15 Operational Treatment: Coordinate with Roadway Agencies to Anticipate Construction Impacts Description: Coordination with the appropriate departments in the jurisdictions that control the roadways can allow transit agencies to anticipate problems that could result from lane closures or construction projects. Agencies can establish routine coordination meetings or conference calls at regular intervals or can participate in regularly scheduled meetings that may already occur among city or state departments. Coordination can be most effective when there is only a single (or just a few) jurisdiction involved. Coordination can be more difficult for regional transit agen- cies that cover many jurisdictions. When potential delay-causing activities are identified, agencies

100 Minutes Matter: A Bus Transit Service Reliability Guidebook can employ one or more treatments, such as executing route contingency plans, increasing opera- tional controls during the construction period, introducing standby buses, and increasing the attention given to affected routes by bus control center personnel. Causes of Unreliability Addressed: Excessive running time, on-time performance, travel time variability Companion Treatments: Enhanced route operational control, introduce standby buses, route contingency plans, more effective use of bus control center Treatment Trade-Offs: Increased administrative coordination activities, which may vary with the number of jurisdictions involved Expected Effect: Low Capital Cost: None Operating Cost: Minor increase to cover coordination activities Ease of Implementation: Easy to medium 7.5.16 Operational Treatment: Coordinate with Traffic and Parking Enforcement Description: Coordination with the appropriate departments that are tasked with enforc- ing traffic and parking regulations can lead to more effective enforcement targeted to motorist behaviors that are impeding bus service. Enforcement can be for moving infractions such as bus lane violations, failure to yield to buses, and turn-restriction violations. It can also include park- ing violations such as parking in bus stops and bus lanes and double parking. Transit agencies and traffic and parking enforcement departments can cooperate in public education programs to alert the public to behaviors that impede bus service. Causes of Unreliability Addressed: Excessive running time, on-time performance, travel time variability Companion Treatments: Bus stop consolidation, right-sizing bus stops, queue-jump lanes, far-side stop placement, curb extensions at bus stops, yield-to-bus laws, public education Treatment Trade-Offs: Increased administrative coordination activities, which may vary with the number of jurisdictions involved Expected Effect: Medium Capital Cost: None Operating Cost: Minor increase to cover coordination activities Ease of Implementation: Medium 7.5.17 Physical Treatment: Dedicated Transitways and Bus Lanes Description: Dedicated rights-of-way for buses can take many forms. The greater the degree of exclusivity, the greater the improvement in service. There can be curb bus lanes (Figure 7.6), bus lanes that are one lane away from the curb (offset bus lanes), physically separated bus lanes in the median of a roadway, and bus transitways on completely separated rights-of-way. An exclusive transitway on a separate right-of-way can help reduce running time and travel time variability by limiting the delay and uncertainty caused by traffic congestion. Reducing running time and reducing travel time variability are key ways to improve reliability. Running

Bus Transit Reliability Menus 101 time reduction allows the transit agency to deliver more trips per time, thereby reducing the scheduled headway. Addressing travel time variability helps reduce the uncertainty in bus arrival times at bus stops, which relates to passenger waiting time. The influence of using a busway versus a highway or arterial road is heavily context-dependent. The right-of-way category is an important factor in determining the impacts of the treatment. Even a low level of conflict with mixed traffic can interfere with the reliability improvements by creating uncertainty in running time and requiring additional buffer time. In some instances, where there are frequent delays at a particular intersection but not along a lengthy route segment, it may be sufficient to remove a few parking spaces upstream from the intersection to help buses to reach the intersection. In the transit agency survey conducted as part of this project, exclusive bus lanes were defined for respondents as a roadway dedicated exclusively or primarily to the use of buses. Fourteen out of 71 respondents indicated that their agencies had implemented exclusive bus lanes. Of this group, 11 indicated that this strategy improved the reliability of their fixed-route bus service. Agen- cies that had implemented exclusive bus lanes were asked what type of lane(s) had been used. Ten agencies had concurrent bus lanes, where the lane operates in the same direction as general traffic flow. Six of these agencies found this was a successful strategy, while the remaining four experienced mixed results. Only three agencies had installed contraflow bus lanes, where the lane operates in the opposite direction to the general traffic flow. All three found that this was a successful strategy. It is worth noting that years ago, in both Chicago and New York City, contra- flow bus lanes were implemented and ultimately removed due to safety concerns for pedestrians. Only two of the respondent agencies had used a bidirectional bus lane, where a single lane serves buses operating in both directions. Both agencies found this strategy successful. Bus lanes with intermittent priority (BLIPs) are shared traffic lanes that detect oncoming buses and give priority through dynamic signage. The bus lanes were found to not reduce street capacity nearly as much as dedicated bus lanes, but they can be effective in reducing the impact of traffic congestion on bus operations. The amount of traffic disruption of a BLIP depends on the TSP strategies used, among other factors. BLIPs can also help to reduce bus travel times, but this is dependent on traffic saturation level, bus frequency, the improvement in bus travel time achieved by the special lane, and the ratio of bus and car occupant flows [41]. Xie et al. developed an analytical model of BLIPs and found they could yield positive results when associated with TSP [42]. In a study in Montreal, Quebec, a reserved bus lane was found to decrease the probability of being late for a route by 65 percent [26]. Similarly, the New York City MTA reported success with arterial and expressway bus-only lanes in combination with several other reliability improvement Source: WSP USA. Figure 7.6. Example of an on-street bus lane.

102 Minutes Matter: A Bus Transit Service Reliability Guidebook strategies [43]. In a study of the Translink system in Brisbane, Australia, busway corridors showed clear benefits over general traffic on expressways and arterial road segments [44]. In a more recent study of the same system, the use of busways was found to decrease average travel time, buffer time, and coefficient of variation of travel time compared to municipal streets and county roads, but not as much as on arterial roads or expressways [6]. Causes of Unreliability Addressed: Variable travel speed Companion Treatments: Transit signal priority, limited-stop service, queue-jump lanes Treatment Trade-Offs: An exclusive transitway on a separate right-of-way can significantly help to reduce running time and travel time variability by limiting the delay and uncertainty caused by traffic congestion. Implementing dedicated transit running ways is one of the most effective strategies for improving reliability. Bus lanes increase travel speeds by 10 to 30 percent, depending on the degree of exclusivity. Almost any bus priority treatment, of course, can be challenging to implement because it typically involves taking roadway space away from mixed traffic. Bus lanes of any sort require extensive public engagement and are quite expensive to install, but this cost is sometimes shared with the host municipality. The greater the degree of exclusivity, the greater the cost to implement, but the greater the benefits. Expected Effect: High; dedicated bus lanes may be the single most effective physical treatment for improving reliability. Capital Cost: Dedicated bus lanes can cost as much as $10 million/mile. Bus lanes defined by signs and markings typically cost less than $1 million/mile. Operating Cost: Bus lanes typically require little if any additional operating cost for the transit agency. Signs and markings require maintenance, which could be the responsibility of the juris- diction. Camera enforcement of bus lanes can be an additional operating cost. Ease of Implementation: Medium-difficult, depending on the type of bus lane. Bus lanes defined by signs and markings require traffic analysis, curb utilization studies, and public outreach. If construction of physically separated lanes is required, extensive traffic analysis, public outreach, and environmental review will be required. In commercial districts, direct interaction with local merchants and institutions will be needed. Sources of Additional Information: TCRP Synthesis 83: Bus and Rail Transit Preferential Treatments in Mixed Traffic [45], TCRP Synthesis 110: Commonsense Approaches for Improving Transit Bus Speeds [46], TCRP Report 118: Bus Rapid Transit Practitioner’s Guide [47], TCRP Report 165: Transit Capacity and Quality of Service Manual [24], TCRP Report 183: A Guidebook on Transit-Supportive Roadway Strategies [29], NACTO Transit Street Design Guide [48] 7.5.18 Physical Treatment: Queue-Jump Lanes Description: Queue jumps are a treatment where buses—or in some applications, buses and right-turning vehicles—are provided an opportunity to move around queued through- and general-traffic vehicles at a signalized intersection and, in many cases, to proceed into the inter- section in advance of through traffic (Figure 7.7). This treatment is particularly effective at inter- sections where the number of lanes is reduced. This allows the buses to move ahead of general traffic without conflict. In some cases, a leading bus indicator could be installed to allow buses to make a left turn from a near-side bus stop. In the survey conducted for this project, about 20 percent of respondents (11 agencies) had implemented queue jumps in some form. Of this group, eight agencies reported that the strategy was successful, and two reported mixed results.

Bus Transit Reliability Menus 103 Causes of Unreliability Addressed: Variable travel speed Companion Treatments: Dedicated transitways and bus lanes, bus-on-shoulder operation, transit signal priority Treatment Trade-Offs: Few negative effects. The treatment must be designed so as not to impair pedestrian crossings in the intersection. Expected Effect: High, but specific to delay-prone intersections Capital Cost: Queue jumps typically require an additional signal head and often some construc- tion to give the bus a continuous lane through the intersection. The traffic signal work typically costs approximately $50,000 on each side of the street. Creating a continuous lane can involve sig- nificant construction, or no construction at all, depending on the characteristics of the intersection. Operating Cost: None for the transit agency; the highway agency will have recurring main- tenance costs. Ease of Implementation: Moderate to difficult. If the roadway is being reconstructed, it could be easy to include some queue jumps as part of the project. To build a stand-alone queue jump at a single intersection might prove more difficult. Sources of Additional Information: TCRP Synthesis 110: Commonsense Approaches for Improving Transit Bus Speeds [46], TCRP Report 183: A Guidebook on Transit-Supportive Roadway Strategies [29] 7.5.19 Physical Treatment: Level Boarding and Low-Floor Buses Description: The amount of time it takes customers to board the bus can be reduced by making it easier to board. This treatment reduces the difference in height between the sidewalk and the floor of the bus by raising the height of the boarding area at the bus stop, lowering the floor of the bus, or both. Wheelchair lifts (Figure 7.8) are replaced by easy-to-deploy ramps. Causes of Unreliability Addressed: Variable dwell time Companion Treatments: Fare innovations for dwell time Expected Effect: Medium to high, depending on the busyness of the bus stop. (Busier stops would see greater benefits.) Improvements in reliability would be most significant where transit agencies no longer need to deploy wheelchair lifts. Capital Cost: The cost to replace a fleet is very high unless done through a normal replacement cycle. Building bus stops with level boarding in dense downtown areas can be very costly—up to Source: WSP USA. Figure 7.7. Bus queue-jump lane.

104 Minutes Matter: A Bus Transit Service Reliability Guidebook $1 million per stop if utility locations are required. Outside of downtown areas, building a bus stop with level boarding is significantly easier and less costly. Operating Cost: Low-floor buses will not increase operating costs except in large cities where the lower capacity of the bus may require additional buses to accommodate all customers. Where high-floor buses typically can accommodate 60 passengers, low-floor buses accommodate about 10 percent fewer. Replacing wheelchair lifts with wheelchair ramps will reduce maintenance costs. Ease of Implementation: Moderate to difficult. Replacing the bus fleet is under the control of the transit agency. Building bus stops with level boarding requires the approval and support of the municipality and can be costly. Public engagement at stop locations is necessary. Sources of Additional Information: TCRP Report 165: Transit Capacity and Quality of Service Manual [24] 7.5.20 Physical Treatment: Articulated Buses Description: Switching from the use of 40-foot-long (12-meter) standard buses to 60-foot- long (18-meter) articulated buses typically happens when there is a clear need for additional capacity. Low-floor articulated buses with three doors can help to reduce dwell time by providing more space for customers to board and alight. When paired with off-board fare collection, significant reductions in dwell time can result. Articulated buses typically operate at slower speeds than standard buses because a greater number of customers board and alight. Therefore, articulated buses are most effectively deployed on BRT or limited-stop services. Causes of Unreliability Addressed: Variable dwell times, variable travel speed Companion Treatments: Level boarding and low-floor buses, bus stop consolidation. Treatment Trade-Offs: It is necessary to lengthen bus stops so that buses can easily maneuver in and out of stops so as not to incur severe dwell time increases. The differences between regular and articulated buses appear to be mostly due to the physical and performance characteristics of these vehicles, including speed of boarding and alighting (related to the number and width of doors as well as floor height) and rates of acceleration and deceleration. In a study in Montreal, Quebec, Diab and El-Geneidy found that the introduction of articulated buses increased running times but reduced running time variation [21]. Switching from standard buses to articulated buses is an effective strategy for carrying more customers with the same number of bus operators. In most cases, however, transit agencies may reduce frequency when introducing a fleet of articulated buses. Thus, while operating costs may be reduced, customers are often faced with longer headways and longer waits. Source: WSP USA. Figure 7.8. Wheelchair lift on bus.

Bus Transit Reliability Menus 105 Expected Effect: Minor; could generate some reliability improvements, but overall travel times could increase. Capital Cost: There is a significant capital cost for the new bus fleet and parts inventory. Capital expenditures are normally required to retrofit bus garages to accommodate the longer buses. Operating Cost: Carrying the same number of customers with articulated buses requires fewer bus operators than with standard buses because the buses have greater capacity. Training will be required for bus maintainers with a new fleet. In addition, there are components on articulated buses, such as the articulation joint, that are not present on standard buses and will increase maintenance costs per bus. Ease of Implementation: Difficult. Buying a new fleet of buses is costly and time- consuming. In addition, depot modifications are needed. Bus stops need to be lengthened and possibly consolidated. Sources of Additional Information: TCRP Synthesis 75: Uses of Higher Capacity Buses in Transit [49] 7.5.21 Physical Treatment: Right-Sized Terminals and Layovers Description: Often, transit agencies cannot get sufficient space at terminals to stage service properly. If there is not enough space, buses may leave late since they may have to make compli- cated maneuvers to get into position. The worst situation is where buses must keep moving up in a queue and the bus operator does not have an opportunity to leave the bus. More commonly, the amount of recovery time built into schedules is insufficient due to the lack of space at the route endpoint to accommodate sufficient layover time. With on-street terminals, there are often neighborhood concerns about the number of buses waiting. The typical municipal response when receiving complaints is to give the transit agency less curb space, which of course makes the problem worse. With off-street terminals, service may have expanded since the facility was built so that it is now inadequate. It can be difficult and expensive to acquire more property. Allowing one or more services to lay over on the street is often not an option in the neighborhood. Providing terminal facilities that are sufficient to accommodate the amount of layover time needed to absorb running time variability will improve reliability. Figure 7.9 shows a terminal with multiple bus bays. Causes of Unreliability Addressed: Variable travel speed, early/late start Companion Treatments: Right-sizing bus stops, route network adjustments Source: WSP USA. Figure 7.9. Multiple bus bays at terminal.

106 Minutes Matter: A Bus Transit Service Reliability Guidebook Treatment Trade-Offs: The trade-offs typically involve neighborhood opposition. The only solution is to have bus operators avoid excess noise and unsocial behaviors. Buses should be parked at the curb and never be allowed to idle. Allowing customers to board the bus before it is ready to depart can build support in the neighborhood for the layover zone. If some area residents are benefiting from the layover zone, that can build support among neighbors. Expected Effect: Moderate where inadequate space at layover zones impairs service delivery Capital Cost: There is no capital cost to resize on-street terminals unless shelters must be moved. Expanding off-street terminals can be expensive. Operating Cost: None Ease of Implementation: Easier for on-street terminals, difficult for off-street terminals in urban areas Sources of Additional Information: TCRP Synthesis 117: Better On-Street Bus Stops [28] 7.5.22 Physical Treatment: Far-Side Stop Placement Description: Far-side bus stops are placed immediately beyond an intersection. In a dense urban environment, far-side bus stops are superior in almost every instance. Far-side stops tend to avoid the occurrence of a double stop, where a bus stops for a red signal, then serves a near-side stop when the signal changes to green, but them must wait through a red signal again before clearing the intersection. At far-side stops, buses can use gaps in traffic caused by signals at the intersection to reenter the flow of traffic when leaving bus stops. Far-side stop placement is recommended by Boyle, especially since these stops facilitate TSP [50]. Far-side stops also make it easier for buses to maneuver into stops because the intersection provides additional space for approaching the curb. Far-side stops avoid the common occurrence at near-side stops where customers may walk in front of the bus when boarding and alighting, thus slowing service. Far-side stops also avoid conflicts with right-turning vehicles, which can lead to crashes and can also delay service. Causes of Unreliability Addressed: Variable travel speed, variable dwell time Companion Treatments: Transit signal priority, bus stop consolidation Treatment Trade-Offs: The travel time and reliability benefits of far-side stops must be weighed against customer convenience benefits at near-side locations, such as closer access to a major destination or less need to cross the adjacent street, as well as physical characteristics of the locations such as space for a shelter and the grade of the sidewalk. Expected Effect: Likely to improve reliability; minor reductions in travel time can be expected. Capital Cost: There is no capital cost to move bus stops unless shelters must be moved. Operating Cost: There is no operating cost involved with switching to far-side stops. Ease of Implementation: Easy. This strategy is easy to implement, but public engagement is needed when relocating bus stops. Sources of Additional Information: TCRP Synthesis 117: Better On-Street Bus Stops [28], TCRP Report 183: A Guidebook on Transit-Supportive Roadway Strategies [29] 7.5.23 Physical Treatment: Curb Extensions at Bus Stops Description: Curb extensions, also known as bus bulbs, are sidewalk extensions at bus stops extending the sidewalk out to the edge of the parking lane. This strategy allows the bus to stop

Bus Transit Reliability Menus 107 without pulling to the curb and then back out into moving traffic, thereby reducing delays and improving reliability. In addition, if street conditions permit, the extension can be built to a height of 10 inches or even 13 inches to allow for truly level boarding, thus further reducing dwell time. At busy bus stops, the extension allows more room for customers to queue and congregate, and there are fewer conflicts between waiting bus riders, pedestrians on the street, and people destined for stores on the block. About 14 percent of agencies responding to the project survey had deployed curb extensions at stops. Of this group, 66 percent reported that the strategy was successful, while 33 percent indicated mixed results. In busy commercial areas where sidewalk traffic is high and there are sidewalk cafes, for example, the extension of the sidewalk can be particularly beneficial. Likewise, if the block in question is plagued by many curb deliveries, then bus bulbs can be enormously helpful since delivery trucks are much less likely to stop in the bus lane to make deliveries. Causes of Unreliability Addressed: Variable dwell time Companion Treatments: Dedicated transitways and bus lanes Treatment Trade-Offs: If curb extensions at bus stops are deployed using prefabricated devices, they can be quite inexpensive. However, if they are built to be true sidewalk extensions, with landscaping and attractive street furniture, then the cost will be higher. Depending on the slope of the sidewalk and crown of the street, these could prove to be difficult to engineer. It is critical to maintain drainage on the block, which sometimes requires a channel for water along the line of the original curb. In addition, if utility relocations are needed, then costs can get quite high. Curb extensions can also impede snow removal and make it difficult to incorporate a bike lane on the same street. Expected Effect: Moderate; could be high at certain intersections that serve high-frequency bus routes; possibly a slight reduction in travel time Operating Cost: No change in operating costs Ease of Implementation: Difficult. Curb extensions require significant capital funding and time. They seem straightforward but can be complex to build in a dense urban environment. If utilities must be relocated, then costs can rapidly increase. On the other hand, many transit agen- cies have deployed prefabricated units, which can function very effectively. Public engagement is necessary in the immediate neighborhood. Sources of Additional Information: TCRP Report 65: Evaluation of Bus Bulbs [51], TCRP Synthesis 117: Better On-Street Bus Stops [28], TCRP Report 183: A Guidebook on Transit-Supportive Roadway Strategies [29] 7.5.24 Physical Treatment: Coordinate with Roadway Agencies to Incorporate Bus-Supportive Features Description: Early involvement by transit agencies in the planning process for new, expanded, or reconstructed roadways can allow for the incorporation of bus-supportive features such as many of the physical treatments described in this document. Treatments such as bus stop consolidation, right-sizing bus stops, far-side stop placement, and traffic signal optimization could be made part of a project at essentially no additional cost. Others, such as queue-jump lanes, curb extensions at bus stops, and transit signal priority, could be added at much lower cost than if they were imple- mented as stand-alone projects. Causes of Unreliability Addressed: Excessive running time, travel time variability, variable dwell time

108 Minutes Matter: A Bus Transit Service Reliability Guidebook Companion Treatments: Bus stop consolidation, right-sizing bus stops, queue-jump lanes, right-sized terminals and layovers, far-side stop placement, curb extensions at bus stops, traffic signal optimization, transit signal priority Treatment Trade-Offs: Increased administrative coordination activities Expected Effect: High Capital Cost: None for coordination activities. Construction costs may be only moderate if elements can be integrated with roadway reconstructions and improvements. Operating Cost: Moderate cost to cover coordination activities and participation in the design process Ease of Implementation: Medium 7.5.25 Technological Treatment: More Effective Use of Bus Control Center Description: Bus control centers (Figure 7.10) can give instructions to bus operators in real time to maintain global stability on a route. The staff working in the control centers can assist bus operators in cases of severe bunching, a missed run, or a special event. With access to real- time information, they can coordinate bus operators on the entire route to act in synchroniza- tion when the schedule is impossible to maintain due to special conditions. Control center staff can also alert bus operators of late connections, utility work, and so forth. While some transit agencies make excellent use of their control centers, other agencies are still perfecting techniques in this regard. When real-time bus information is available, transit agencies should strive to make the most effective use of control center personnel to regulate service. Causes of Unreliability Addressed: Variable travel speed, non-operation, early/late start, inconsistent transfer times Companion Treatments: Introduce scheduled short turns Treatment Trade-Offs: There are no disadvantages to making better use of command center staff. Expected Effect: Moderate; could improve communication and service control and, therefore, reliability Source: WSP USA. Figure 7.10. Bus control center.

Bus Transit Reliability Menus 109 Capital Cost: Where a working bus command center is in place, making better use of the facility will involve little if any capital cost. If a transit agency does not have command center, then the capital cost of establishing one would be significant since it involves setting up a network radio system as well as building a physical space for the command center. Operating Cost: Where a working bus command center is in place, making better use of the facility will involve a minor operating cost. If no command center exists, or if the command center is not set up for effective service control, then there will be an increase in operating costs. Ease of Implementation: Easy to difficult. Where a working bus command center is in place, making better use of the facility is easy. If no command center is in place, then implementation is difficult. 7.5.26 Technological Treatment: Traffic Signal Optimization Description: Optimization of traffic signals involves retiming signals to improve the flow of traffic. The objective of the optimization program could be to improve traffic flow for all traffic, or it could be specifically to improve travel times for buses. (The latter is also known as passive TSP.) In either case, extensive traffic data must be collected, and it is necessary to review the signal timing for every intersection in the corridor. Signal timing could be consistent at every intersection, or it could vary from intersection to intersection. In New York City, traffic signals were optimized before TSP was implemented in a corridor. Bus and general-traffic speeds were analyzed before implementation, after signals were opti- mized, and then again after TSP was implemented. While results varied among corridors, generally the travel time improvements for buses were attributable half to signal optimization and half to TSP. Causes of Unreliability Addressed: Variable travel speed Companion Treatments: Transit signal priority, dedicated transitways and bus lanes, queue- jump lanes, limited-stop service Treatment Trade-Offs: The costs for traffic data collection and analysis Expected Effect: Moderate; can be very beneficial to bus speed/reliability Capital Cost: None if the traffic signal controllers in the host municipality are modern Operating Cost: None, but traffic data collection and analysis involve a cost. Ease of Implementation: Easy if the host municipality is in agreement Sources of Additional Information: TCRP Synthesis 110: Commonsense Approaches to Improving Transit Bus Speeds [46], TCRP Report 183: A Guidebook on Transit-Supportive Road- way Strategies [29] 7.5.27 Technological Treatment: Transit Signal Priority Description: TSP expedites or extends the green phase for transit vehicles to limit inter- section delay for transit. There are three types of signal priority: passive, active, and signal preemption. Passive priority consists of timing signal phases at a speed suitable for transit vehicles. Active priority can dynamically extend the green phase or truncate the red phase when detecting an oncoming bus. Signal preemption allows the normal operations of traffic signals to be preempted for transit. Preemption is normally only used for emergency vehicles and not for transit.

110 Minutes Matter: A Bus Transit Service Reliability Guidebook Research has demonstrated the potential for TSP to improve transit running times and reli- ability in several cases. Signal preemption is more effective than active TSP but causes much greater disruption to general traffic on intersecting streets. Skabardonis found greater benefits from signal preemption than from active priority, but tests showed major negative impacts to general traffic [52] impacts to general traffic. Most deployments of TSP in North America are active or passive priority. Conditional signal priority is a variant of active priority that actuates green phases to buses only if they are operating behind schedule. Furth and Muller developed a model based on its use in Eindhoven in the Netherlands and demonstrated significant improvement in schedule adherence after the implementation of conditional signal priority for buses at signalized inter- sections. Signal preemption (when priority is always given for transit vehicles) significantly increased general traffic delays compared to the no-priority scenario, while conditional priority had little impact on general traffic conditions [53]. Causes of Unreliability Addressed: Variable travel speed Companion Treatments: Traffic signal optimization, queue-jump lanes, limited-stop service, dedicated transitways and bus lanes Expected Effect: Moderate. The results of a survey conducted for TCRP Synthesis 83: Bus and Rail Transit Preferential Treatments in Mixed Traffic [45] revealed that TSP was the most popular preferential treatment on urban streets but that standard warrants were needed for when and how to apply the treatment. The analysis revealed that the greatest benefit was typically realized from the systematic application of one or more preferential treatments along a corridor, with median transitways, exclusive lanes, and TSP estimated to provide the most significant positive results. TSP should also be coordinated with service planning. Kimpel et al., in a study of TriMet in Portland, Oregon, found that on-time performance declined in some cases after TSP was implemented. More early trips were made and roughly the same rate of late trips. The authors recommended adjusting bus schedules when implementing TSP strategies [54]. Generally, for TSP to work effectively, bus stops should be located on the far side of (after) a TSP-equipped intersection. In some cases, buses could get priority if they could get to the intersection but were stuck in traffic. When this is a regular occurrence, the addition of a short segment of bus lane or the removal of several parking spaces can make a big difference by allowing buses at the intersection to then take advantage of signal priority. TSP, where traffic signal timing is altered in response to a request from a bus, had been imple- mented by 40 percent of agencies responding to the project survey. The benefits to reliability are small quantitatively, but the customers’ perception of improved reliability is significant. Stopping at several fewer red signals makes the trip feel faster and smoother. Of this group of agencies, 66 percent found that the strategy successfully improved reliability, while 33 percent experienced mixed results. Respondents whose agencies had used TSP were asked to further identify the specific type they had used. About 56 percent of this group had used early green (changing the light to green before it would have otherwise changed to allow the bus to proceed through the intersection without needing to stop). Of respondents, 88 percent experienced success, and 12 percent reported mixed results. More agencies (71 percent) had used green extension (keeping the light green longer to allow the bus to proceed through the intersection without stopping). Half of these respondents reported successful implementation, and the other half reported mixed results. Green extension allows the bus to avoid stopping at a red signal and thus saves a bus 30 to 60 seconds on each call, depending on traffic signal timing.

Bus Transit Reliability Menus 111 About 32 percent of this group had used an actuated signal phase, with 86 percent reporting successful results and 14 percent (or one agency) reporting mixed results. Only three agencies of this group had used phase insertion, with all three agencies reporting successful results. Phase insertion consists of adding a green phase for the oncoming bus to the current cycle. Only two agencies had used adaptive/real-time control and, of this group, one agency found the strategy successful, and one agency did not have an opinion. No agencies surveyed had used phase rotation. Phase rotation consists of shifting the phase cycle to the next green phase for the oncoming bus. TSP was shown to decrease the standard deviation of arrival time deviation from schedule by 3.2 percent on average across 30 simulation cases in Arlington, Virginia [55]. Bus services in Beijing, China, using TSP showed improved reliability compared to services without it [31]. Diab and El-Geneidy quantified the impacts of TSP on running times, using a model of a high- frequency bus route in Montreal, Quebec. They estimated that running times decreased by 18.32 seconds (1.2 percent) [56]. Lehtonen and Kulmala performed a case study in Helsinki, Finland, where TSP and real-time customer information were implemented. Their results indi- cated a more than 40 percent reduction in delays at intersections, with noticeable improvements to service regularity and punctuality. Customer volumes increased by 10 to 12 percent after implementation of TSP and real-time information improvements for the bus system [57]. In their handbook on TSP, Smith, Hemily, and Ivanovic demonstrated a 10 percent reduction in travel times and about 19 percent less travel time variability after implementing TSP on TriMet routes in Portland, Oregon, allowing the agency to reduce scheduled recovery time and avoid adding another peak bus to the route [58]. More recently, Ma, Yang, and Liu developed a model to generate the optimal combination of priority strategies for intersections through corridors. The resulting passive and conditional bus priority approach was demonstrated in the field through a case study in China, which led to significant reductions in bus delays (35 percent per bus compared to no priority) and headway deviations (62 percent reduction compared to no priority, 51 percent reduction compared to unconditional priority) with minimal impacts on general traffic. The proposed strategy was deemed to be useful for improving bus service reliability. While a 9 percent increase in motor vehicle delay was noted, this was small in comparison to the delay increases measured for the unconditional priority approach [59]. Capital Cost: Implementing a TSP system from scratch is expensive and challenging. Traffic signal controllers must be modern, and much coordination is needed among multiple municipal highway jurisdictions. In some instances, transit agencies have had to pay to upgrade signal controllers. Highway agencies may insist on robust traffic data before agreeing to implement TSP. On-bus hardware and software are also expensive. In some cases, it might be prudent to bring in a vendor to supply hardware and software for signals and buses. Operating Cost: There is a minor ongoing cost to keep TSP hardware functioning properly. Ease of Implementation: Difficult. Where a working bus command center is in place, making better use of TSP is not easy to implement since it requires the buy-in from one or more municipal traffic engineering groups. Detailed traffic engineering studies are required to determine appro- priate changes to signal timing. Depending on the need to upgrade traffic signal controllers and bus hardware, this strategy can be costly. Transit agencies should pursue TSP only if funding and local conditions permit it. Sources of Additional Information: TCRP Synthesis 110: Commonsense Approaches to Improving Transit Bus Speeds [46], TCRP Report 183: A Guidebook on Transit-Supportive Roadway Strategies [29]

112 Minutes Matter: A Bus Transit Service Reliability Guidebook 7.5.28 Technological Treatment: Real-Time Information Systems Description: With AVL on buses, transit agencies can track their vehicles in real time. From the survey conducted for this project, 78 percent of transit agencies indicated that they used AVL technology to track their vehicles. AVL data can be provided to customers through display screens (Figure 7.11), text messaging, or mobile device applications to help reduce perceived and actual waiting time. Providing real-time information to customers can improve reliability by reducing perceived waiting time and affecting route choice. Several research projects have studied the impact on reliability of real-time information displays at stations. Hickman and Wilson found that, when provided real-time information at stations, customers were likely to divert their route plans to reduce total travel time [60]. Dziekan and Kottenhoff found that real-time information displays reduced the perceived waiting time at stations [61]. An APTA survey found that about two-thirds of larger transit agencies and one-third of small transit agencies provided real-time information to customers through mobile devices [62]. These numbers would be much higher now due to the rapid deployment of such systems across North America. In Seattle, real-time information has been shown to reduce perceived waiting time by close to 30 percent. Furthermore, real-time information reduced actual wait time because customers would coordinate their arrival times at bus stops with the real-time predictions [7]. The improvements in reliability have been shown to significantly increase ridership and overall satisfaction [9, 63]. These data can also be used to create customer-focused performance metrics [64, 65, 66]. Tribone et al. used AVL data to create a set of metrics that quantify reliability for customers [67]. Causes of Unreliability Addressed: Variable travel speed Companion Treatments: Enhanced route operational control Treatment Trade-Offs: Implementing a AVL-based real-time information system has no disadvantages. Expected Effect: Moderate; can improve reliability by reducing perceived/actual waiting time for passengers, and can improve customer satisfaction Capital Cost: Implementing AVL systems is costly, as is developing data analysis tools and the capability to use the data. If a working AVL system is already in place, introducing tools for customers is not expensive. Source: WSP USA. Figure 7.11. Real-time information display at a bus stop.

Bus Transit Reliability Menus 113 Operating Cost: Maintaining, using, and analyzing data require trained personnel. Many agencies have underestimated the complexity of deploying such systems. Ease of Implementation: Difficult. Building a AVL system from scratch is a costly, time- consuming process. However, providing real-time bus information is critical to being able to make real-time service control adjustments. Agencies that have the hardware in place for managing operations can make the data available to customers. The cost of implementation varies greatly, depending on whether an agency purchases a complete system from a vendor or develops a system in house with open-source software and minimal outside technical support. Providing real-time information to customers can be left to outside developers if data are made publicly available in GTFS (general transit feed specification) real-time format. Sources of Additional Information: TCRP Report 48: Integrated Urban Models for Simulation of Transit and Land Use Policies: Guidelines for Implementation and Use [68], TCRP Report 91: Economic Benefits of Coordinating Human Service Transportation and Transit Services [69] 7.5.29 Technological Treatment: Fare Innovations for Dwell Time Description: Transit agencies spend a considerable amount of money to collect fares; at the same time, fare collection can lead to excessive dwell times at busy stops. Many fare collec- tion systems are awkward for customers to learn and use. Where the fare medium is outdated, introducing better fare collection systems can reduce costs for the transit agency, improve the experience for customers, and increase travel speeds. Simply reducing cash use can provide some improvement, while strategies such as off-board fare collection (Figure 7.12) and all-door boarding can significantly affect travel speed and reliability. Off-board fare collection reduces dwell time by reducing the time it takes for customers to pay fares on board buses. All-door boarding can further reduce dwell time by effectively doubling (or tripling in the case of articulated buses) the number of customers who can board in a given amount of time. The two strategies are often applied together. Some agencies use all-door boarding without off-board fare collection, but only at the busiest stops, to reduce dwell time where many customers normally board. Other agencies permit all-door boarding in the downtown area on commuter express bus routes to speed the boarding process and keep buses moving. For such services, customers pay when they exit the bus. All-door boarding can also be applied without off-board fare collection if fare-card readers are installed at every door. Source: WSP USA. Figure 7.12. Off-board fare collection.

114 Minutes Matter: A Bus Transit Service Reliability Guidebook The replacement of flash passes by smart-card fare payment increased running times on a bus route in Montreal, Quebec, by 52.61 seconds per trip by the end of the implementation period [56]. Smart cards were also shown to significantly increase running time deviation, coefficient of variation of running time, and coefficient of variation of running time deviation in the authors’ regression models. Diab and El-Geneidy found smart-card fare payment to be less effective than flash passes regarding running time and reliability [21]. Strathman et al. found that the introduction of smart cards for fare payment increased the odds of being late by 69 percent when compared to the flash pass system [22]. The results of a study of Translink in Brisbane, Australia, indicated that average boarding time per customer was 3 seconds for smart-card users, 30 seconds for onboard top-up, and 15 seconds for paper ticket users [34]. Eliminating onboard top-up for smart cards resulted in a 15 to 18 percent improvement in reliability for the bus route in question [70]. On the other hand, the New York City MTA reported a 30 to 40 percent reduction in dwell time on BRT services with off-board fare collection in combination with all-door boarding, low-floor buses, and other strategies. Typically, introducing off-board fare collection can improve reliability. All-door boarding reduces dwell time by allowing several queues of customers to board simultaneously in parallel. Diab and El-Geneidy found rear-door boarding to be a significant factor in decreasing running times [21]. All-door boarding, however, should be part of a comprehensive policy to expedite the boarding process. All-door boarding and visual fare inspection coupled are characteristics of off-board fare collection. If the bus operator is not interacting with customers, the greatest reduc- tions in dwell time can be achieved. Visual fare inspection, however, can introduce operating cost increases for the agency. TCRP Report 165: Transit Capacity and Quality of Service Manual, 3rd Edition, offers insights into estimating the differences among various forms of fare payment. Visual fare inspection was estimated to be the fastest form of fare payment, followed by smart cards, then a single ticket or token, then exact change, and, lastly, magnetic stripe cards. To reduce dwell times and improve reliability, flash passes and smart cards were the preferred methods of payment [24]. The critical point regarding fare media is that in most cases, while there may be excellent business reasons to adopt a smart-card fare collection system, typically there are not significant improvements in reliability from adopting new fare media. Causes of Unreliability Addressed: Variable dwell time Companion Treatments: Level boarding and low-floor buses Treatment Trade-Offs: Off-board fare collection typically requires enforcement by a crew of fare inspectors making random inspections, which adds to operating costs. Fare-card readers installed at every door can add capital costs. Expected Effect: High Capital Cost: Introducing a new fare collection system will involve substantial capital cost. Introducing off-board fare collection will involve a capital cost for buying and installing fare machinery at bus stops. All-door boarding and pay on exit involve no capital cost. Operating Cost: A new fare collection system should decrease operating cost. Off-board fare collection coupled with all-door boarding will reduce dwell time and thus travel time, but typi- cally an enforcement mechanism is needed. Hiring and training a team of fare inspectors can be costly.

Bus Transit Reliability Menus 115 Ease of Implementation: Difficult. It is not easy to implement a new fare collection system. Banking protocols are complex. Likewise, introducing off-board fare collection can be quite involved since fare machinery must be purchased and installed. Sources of Additional Information: TCRP Report 94: Fare Policies, Structures, and Technologies: Update [71], TCRP Synthesis 96: Off-Board Fare Payment Using Proof-of-Payment Verification [72], TCRP Report 165: Transit Capacity and Quality of Service Manual [24], TCRP Report 183: A Guidebook on Transit-Supportive Roadway Strategies [29] 7.5.30 Technology Treatment: Improved Customer Communications Description: There is a wide range of communication techniques available to transit agencies. These range from high-tech solutions such as providing real-time information, to lower-tech solu- tions such as tweets for unexpected events causing service problems, to non-technical solutions such as posters or flyers informing customers of upcoming detours or other planned disruptions. Agencies can also monitor customer and third-party tweets, Facebook posts, and direct comments to the agency about reliability issues and respond, often in real time, with explanations for delays and disruptions. While actual reliability may not be improved, customers can feel informed and listened to. Causes of Unreliability Addressed: Customer perceptions of reliability Companion Treatments: Real-time information systems Treatment Trade-Offs: None Expected Effect: Medium (on perceptions) Capital Cost: None Operating Cost: Minor increase to cover communication activities Ease of Implementation: Medium 7.5.31 Policy Treatment: Yield-to-Bus Laws Description: Yield-to-bus laws require motorists to let buses merge back into traffic when they are signaling to leave a bus stop. Motorist compliance is often encouraged through signs mounted on the rear of buses. In the survey conducted for this project, 12 out of 79 respondents indicated that they had implemented yield-to-bus laws. Three of 12 respondents reported a successful implementation, four respondents reported mixed results, and two respondents reported unsuccessful implementation. It would be difficult to quantify the benefits of such legislation, but it is expected to improve reliability by facilitating the reentry of buses into traffic. Causes of Unreliability Addressed: Variable dwell times, variable travel speed Companion Treatments: None Treatment Trade-Offs: No drawbacks Expected Effect: Minor; can improve reliability by decreasing dwell time if followed Capital Cost: None Operating Cost: None Ease of Implementation: Easy, but state legislation is normally required

116 Minutes Matter: A Bus Transit Service Reliability Guidebook 7.5.32 Policy Treatment: Bus-on-Shoulder Operation Description: Bus-on-shoulder (BOS) operation is a strategy where buses operate on the shoulder of a limited-access roadway or arterial road to speed buses around congested roadway segments. Causes of Unreliability Addressed: Variable travel speed Companion Treatments: Dedicated bus transitways and bus lanes, queue-jump lanes Treatment Trade-Offs: There are few disadvantages for the transit operator. Extensive inter- action with the affected highway agency is required. Expected Effect: Moderate. About 13 percent of respondents to the project survey indicated that their agency employed the strategy of BOS operation during peak periods. Of this group, 67 percent indicated that the strategy was successful, 22 percent reported mixed results, and 11 percent (one agency) found that the strategy was not successful. In TCRP Synthesis 64: Bus Use of Shoulders Martin suggests the use of BOS operation as a cost-effective method for improving bus running times and reliability through bypassing congestion. This practice is said to be especially popular with bus customers [73]. Furthermore, he found that customer perception of schedule adherence and trip reliability is higher when buses make use of freeway shoulder lanes during congested periods. Many of the case studies included in his report indicated that reliability was a primary reason behind implementing BOS operations, as well as one of the key benefits of this practice. For example, Miami-Dade Transit in Florida reported that the three bus routes using BOS facilities improved their on-time performance. One route experienced a 2 percent improvement in on-time performance, the second route a 7 percent improvement, and the third route a 19 percent improvement. Another way of representing the results is that for the routes using the shoulder, there was a 50 percent reduction in late buses. Capital Cost: There could a substantial capital cost if a shoulder must be widened or strength- ened. Likewise, if bridges must be made wider, there would be a significant cost. In New Jersey, there was capital cost of $3 million/mile to launch BOS operation on US 1. Operating Cost: Generally, there is no operating cost; in some instances, a BOS lane may be demarcated by traffic cones or a movable barrier. If this is the case, then there would be notable operating costs. Ease of Implementation: Medium to difficult. This requires approval from the appropriate highway agencies, and all safety issues at entrance and exit ramps must be addressed. Sources of Additional Information: TCRP Synthesis 64: Bus Use of Shoulders [73], TCRP Report 151: A Guide for Implementing Bus On Shoulder (BOS) Systems [74] 7.5.33 Policy Treatment: Reliability-Based Fleet Maintenance Description: High-quality fleet maintenance and cyclical replacement of rolling stock help reduce vehicle failures, which can be an important source of unreliability. Aging fleets are prone to more frequent breakdowns. When a bus goes out of service, customers usually need to wait at least another headway until the next vehicle can pick them up. Vehicle breakdowns can cause great discomfort to customers and can happen at any time or place on the route. There is no substitute for an effective, reliability-based maintenance program. Today’s buses come with highly detailed vehicle diagnostic tools. It is necessary to develop maintenance reports that flag the key metrics to ensure continued reliable operation of the fleet. A bus maintenance facility is shown in Figure 7.13

Bus Transit Reliability Menus 117 Causes of Unreliability Addressed: Non-operation, early/late start Companion Treatments: Increase fleet size Treatment Trade-Offs: Requires some expertise in the use of vehicle diagnostic systems and monitoring of vehicle performance data Expected Effect: Moderate. Ultimately there is no substitute for an effective maintenance program. Capital Cost: The capital and operating costs to establish such a program will be high if no such program is already in place. Operating Cost: If additional maintenance personnel need to be hired to implement an effec- tive preventative maintenance program, then there will be an increase in operating costs. Insti- tuting a high-quality training program can add to operating costs. Maintaining a complete parts inventory can also add to operating costs. Ultimately, however, an effective preventative main- tenance program saves money by keeping buses on the road longer, reducing breakdowns, and limiting the times that parts must be ordered on an emergency basis. Ease of Implementation: Moderate. If no such program is in place, it will take time and money to devise and implement a program. It will take several years to establish protocols, train personnel, and catch up with deferred maintenance. 7.5.34 Policy Treatment: Boarding Limits Description: This treatment consists of refusing to board more customers once an established ridership limit is reached. Boarding limits can help avoid customer crowding. Causes of Unreliability Addressed: Variable travel speed, variable dwell time Companion Treatments: Increase fleet size, articulated buses, schedule and headway optimization Treatment Trade-Offs: This treatment can help avoid the unreliability associated with bus bunching and customer crowding, but it can create a great deal of unreliability for customers who are refused access to the bus. While such strategies can help to address short-term opera- tional challenges, they should be applied with discretion since bypassing stops causes distress for customers. Source: WSP USA. Figure 7.13. A bus maintenance facility, essential to a reliability-based fleet maintenance program.

118 Minutes Matter: A Bus Transit Service Reliability Guidebook Expected Effect: Minor system-wide, but moderate where overcrowding is a regular event. Limiting crowding on buses will improve reliability and travel time. However, if customers at downstream stops are regularly bypassed, they will seek another form of transportation. Attempts to meet established operational performance goals should be carefully implemented so as not to result in impaired service to customers. If this situation happens frequently, thresholds should be developed at the agency level to deploy additional vehicles. Capital Cost: None Operating Cost: None Ease of Implementation: Easy. This strategy is easy to implement but must be done with extreme caution. 7.5.35 Policy Treatment: Public Education Description: Public education can help shift customer behavior to promote operational effi- ciency. For example, signs asking customers have their fare media ready, to move to the back of the bus, or to exit through the rear door can expedite the boarding process. Likewise, customers can be reminded not to put their personal items on a seat and to vacate seating for the disabled when asked. Causes of Unreliability Addressed: Variable dwell time Companion Treatments: Public education (which can be used in combination with almost every treatment discussed herein) Treatment Trade-Offs: Staffing costs for developing and maintaining a public education program Expected Effect: Minor, but public education will improve the effectiveness of all treatments Capital Cost: None Operating Cost: If the agency has marketing staff, there is no cost. If there are no personnel assigned to a marketing activity, then a cost will be incurred. Ease of Implementation: Easy. This is an easy strategy to implement.

Bus Transit Reliability Menus 119 Treatment O pe ra tio na l Enhanced route operational control Introduce standby buses Introduce scheduled short turns Limited-stop service Bus stop consolidation Right-sizing bus stops Route network adjustments Divide very long bus routes Schedule and headway optimization Coordinate schedules at transfer points Bus operator training, incentives, and monitoring Route contingency plans Increase fleet size Employ more full-time bus operators Coordinate with roadway agencies to anticipate construction impacts Coordinate with traffic and parking enforcement Ph ys ic al Dedicated transitways and bus lanes Queue-jump lanes Level boarding and low-floor buses Articulated buses Right-sized terminals and layovers Far-side stop placement Curb extensions at bus stops Coordinate with roadway agencies to incorporate bus-supportive features Te ch no lo gy More effective use of bus control center Traffic signal optimization Transit signal priority Real-time information systems Fare innovations for dwell time Improved customer communications Po lic y Yield-to-bus laws Bus-on-shoulder operation Reliability-based fleet maintenance Boarding limits Public education Index of reliability treatments.