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Cost-Effective Performance Measures for Travel Time Delay, Variation, and Reliability (2008)

Chapter: Chapter 2 - Selecting Appropriate Performance Measures

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Suggested Citation:"Chapter 2 - Selecting Appropriate Performance Measures." National Academies of Sciences, Engineering, and Medicine. 2008. Cost-Effective Performance Measures for Travel Time Delay, Variation, and Reliability. Washington, DC: The National Academies Press. doi: 10.17226/14167.
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Suggested Citation:"Chapter 2 - Selecting Appropriate Performance Measures." National Academies of Sciences, Engineering, and Medicine. 2008. Cost-Effective Performance Measures for Travel Time Delay, Variation, and Reliability. Washington, DC: The National Academies Press. doi: 10.17226/14167.
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Suggested Citation:"Chapter 2 - Selecting Appropriate Performance Measures." National Academies of Sciences, Engineering, and Medicine. 2008. Cost-Effective Performance Measures for Travel Time Delay, Variation, and Reliability. Washington, DC: The National Academies Press. doi: 10.17226/14167.
×
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Suggested Citation:"Chapter 2 - Selecting Appropriate Performance Measures." National Academies of Sciences, Engineering, and Medicine. 2008. Cost-Effective Performance Measures for Travel Time Delay, Variation, and Reliability. Washington, DC: The National Academies Press. doi: 10.17226/14167.
×
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Suggested Citation:"Chapter 2 - Selecting Appropriate Performance Measures." National Academies of Sciences, Engineering, and Medicine. 2008. Cost-Effective Performance Measures for Travel Time Delay, Variation, and Reliability. Washington, DC: The National Academies Press. doi: 10.17226/14167.
×
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Suggested Citation:"Chapter 2 - Selecting Appropriate Performance Measures." National Academies of Sciences, Engineering, and Medicine. 2008. Cost-Effective Performance Measures for Travel Time Delay, Variation, and Reliability. Washington, DC: The National Academies Press. doi: 10.17226/14167.
×
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Suggested Citation:"Chapter 2 - Selecting Appropriate Performance Measures." National Academies of Sciences, Engineering, and Medicine. 2008. Cost-Effective Performance Measures for Travel Time Delay, Variation, and Reliability. Washington, DC: The National Academies Press. doi: 10.17226/14167.
×
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Suggested Citation:"Chapter 2 - Selecting Appropriate Performance Measures." National Academies of Sciences, Engineering, and Medicine. 2008. Cost-Effective Performance Measures for Travel Time Delay, Variation, and Reliability. Washington, DC: The National Academies Press. doi: 10.17226/14167.
×
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Suggested Citation:"Chapter 2 - Selecting Appropriate Performance Measures." National Academies of Sciences, Engineering, and Medicine. 2008. Cost-Effective Performance Measures for Travel Time Delay, Variation, and Reliability. Washington, DC: The National Academies Press. doi: 10.17226/14167.
×
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Suggested Citation:"Chapter 2 - Selecting Appropriate Performance Measures." National Academies of Sciences, Engineering, and Medicine. 2008. Cost-Effective Performance Measures for Travel Time Delay, Variation, and Reliability. Washington, DC: The National Academies Press. doi: 10.17226/14167.
×
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Suggested Citation:"Chapter 2 - Selecting Appropriate Performance Measures." National Academies of Sciences, Engineering, and Medicine. 2008. Cost-Effective Performance Measures for Travel Time Delay, Variation, and Reliability. Washington, DC: The National Academies Press. doi: 10.17226/14167.
×
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Suggested Citation:"Chapter 2 - Selecting Appropriate Performance Measures." National Academies of Sciences, Engineering, and Medicine. 2008. Cost-Effective Performance Measures for Travel Time Delay, Variation, and Reliability. Washington, DC: The National Academies Press. doi: 10.17226/14167.
×
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Suggested Citation:"Chapter 2 - Selecting Appropriate Performance Measures." National Academies of Sciences, Engineering, and Medicine. 2008. Cost-Effective Performance Measures for Travel Time Delay, Variation, and Reliability. Washington, DC: The National Academies Press. doi: 10.17226/14167.
×
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Suggested Citation:"Chapter 2 - Selecting Appropriate Performance Measures." National Academies of Sciences, Engineering, and Medicine. 2008. Cost-Effective Performance Measures for Travel Time Delay, Variation, and Reliability. Washington, DC: The National Academies Press. doi: 10.17226/14167.
×
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Suggested Citation:"Chapter 2 - Selecting Appropriate Performance Measures." National Academies of Sciences, Engineering, and Medicine. 2008. Cost-Effective Performance Measures for Travel Time Delay, Variation, and Reliability. Washington, DC: The National Academies Press. doi: 10.17226/14167.
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10 2.1 Introduction This chapter helps the user to understand the range of performance measures or metrics available to measure and monitor travel time, delay, and reliability, and to identify appropriate metrics for a given application, taking into ac- count factors such as data availability and the intended use or audience for the results. We have adopted the terms “mobil- ity” and reliability, because these are the desirable outcomes sought for the transportation system user. “Travel time” and “delay” and the variability in those two quantities are key determinants of mobility and reliability. A system of mobility and reliability measures should be developed only after an examination of the uses and audiences to be served, the consideration of program goals and objectives, and identification of the nature or range of likely solutions. This chapter illustrates a system of travel-time-based measures to estimate mobility and reliability levels. These procedures are useful for roadway systems, person and freight move- ment modes, and transportation improvement policies and programs. The user should consider the way that measures might be used before selecting the appropriate set of mo- bility and reliability measures. The following sections describe techniques for measuring mobility and reliability on various portions of a transportation network. Some of the material in this chapter has been excerpted from the Keys to Estimating Mobility in Urban Areas: Applying Definitions and Measures That Everyone Understands, and the reader is encouraged to review that source for more detailed background information (2). 2.2 Measure Selection Given a basic understanding of the performance measure- ment process as described in Chapter 1, this section provides several considerations that can be used to identify the most appropriate mobility and reliability measures for a situation. Because of the wide range and diversity of available measures, it is important to have a clear basis for assessing and compar- ing mobility and reliability measures. Such an evaluation makes it possible to identify and separate measures that are useful for an analytical task from measures that are either less useful or inappropriate for certain analyses. 2.2.1 Choosing the Right Mobility and Reliability Measures The ideal mobility and reliability measurement technique for any combination of uses and audiences will include the features summarized in Exhibit 2.1. These issues should be examined before data are collected and the analysis begins, but after the analyst has considered all reasonable responses to the problem or issue being studied. Having an idea of what the possible solutions are will produce a more appropriate set of measures. 2.2.2 The Data Collection Issue Concerns about the cost and feasibility of collecting travel- time data are frequently the first issues mentioned in discus- sions of mobility and reliability measures. There are many ways to collect or estimate the travel time and speed quantities; data collection should not be the determining factor about which measures are used. While it is not always possible to separate data collection issues from measure selection, this should be the goal. Chapter 3 discusses data collection in more detail. 2.2.3 Aspects of Congestion, Mobility, and Reliability The selection of a proper set of mobility and reliability measures includes an assessment of what traveler concerns are most important. This assessment can be drawn from experiences with measuring congestion in roadway systems. C H A P T E R 2 Selecting Appropriate Performance Measures

11 Checklist Item Short Discussion Relate to goals and objectives The measures must indicate progress toward transportation and land use goals that the project or program attempts to satisfy. Measuring transportation and land use characteristics that are part of the desired future condition will provide a continual check on whether the area is moving toward the desired condition. Clearly communicate results to audiences While the technical calculation of mobility and reliability information may require complicated computer models or estimation techniques, the resulting information should be in terms the audience can understand and find relevant. Include urban travel modes Mobility and reliability are often a function of more than one travel mode or system. At least some of the measures should contain information that can be calculated for each element of the transportation system. The ability to analyze the system, as well as individual elements, is useful in the selection of alternatives. Have consistency and accuracy Similar levels of mobility and reliability, as perceived by travelers, should have similar mobility and reliability measures. This is important for analytical precision and also to maintain the perception of relevancy with the audiences. There also should be consistency between levels of analysis detail; results from relatively simple procedures should be similar to those obtained from complex models. One method for ensuring this is to use default factors for unknown data items. Another method is to frequently check expected results with field conditions after an improvement to ensure that simple procedures – those that use one to three input factors – produce reasonable values. Illustrate the effect of improvements The improvements that may be analyzed should be consistent with the measures that are used. In relatively small areas of analysis, smaller urbanized areas, or portions of urban areas without modal options, this may mean that vehicle-based performance measures are useful. Using a broader set of measures will, however, ensure that the analysis is transferable to other uses. Be applicable to existing and future conditions Examining the need for improvements to current operations is a typical use of mobility and reliability measures that can be satisfied with data collection and analysis techniques. The ability to relate future conditions (e.g., design elements, demand level, and operating systems) to mobility and reliability levels also is required in most analyses. Be applicable at several geographic levels A set of mobility and reliability measures should include statistics that can illustrate conditions for a range of situations, from individual travelers or locations to subregional and regional levels. Using quantities that can be aggregated and averaged is an important element of these criteria. Use person- and goods- movement terms A set of measures should include factors with units relating to the movement of people and freight. In the simplest terms, this means using units such as persons and tons. More complex assessments of benefits will examine the different travel patterns of personal travel, freight shipping, and the intermodal connections for each. Use cost-effective methods to collect and/or estimate data Using readily available data or data collected for other purposes is a method of maximizing the usefulness of any data collection activities. Focusing direct data collection on significant problem areas also may be a tactic to make efficient use of data collection funding. Models and data sampling procedures also can be used very effectively. Exhibit 2.1. Checklist of considerations for mobility and reliability measure selection (1). A set of four aspects of congestion was discussed at the Work- shop on Urban Congestion Monitoring (4) in May 1990, as a way to begin formulating an overall congestion index. These four components provide a useful framework for mobility and reliability estimation procedures as well. 2.2.4 Summarizing Congestion Effects Using Four General Components While it is difficult to conceive of a single value that will describe all travelers’ concerns about congestion, there are four components that interact in a congested roadway or sys- tem (1). These components are duration, extent, intensity, and variation. They vary among and within urban areas. Smaller urban areas, for example, usually have shorter duration than larger areas, but many have locations with relatively intense congestion. The four components and measurement concepts that can be used to quantify them are discussed below. 1. Duration. This is the length of time during which conges- tion affects the travel system. The peak hour has expanded to a peak period in many corridors, and mobility and

12 Volume of the box is a measure of magnitude of congestion; smaller volume is better. Variation in volume of the box is an indication of reliability. Duration Extent Intensity Exhibit 2.2. Components of congestion (2). reliability studies have expanded accordingly. The meas- urement concept that illustrates duration is the amount of time during the day that the travel speed indicates con- gested travel on a system element or the entire system. The travel speed might be obtained in several ways depending on data sources or travel mode being studied. 2. Extent. This is described by estimating the number of people or vehicles affected by congestion and by the geographic dis- tribution of congestion. The person congestion extent may be measured by person-miles of travel or person-trips that occur during congested periods. The percent, route-miles, or lane-miles of the transportation system affected by con- gestion may be used to measure the geographic extent of mobility and reliability problems. 3. Intensity. The severity of congestion that affects travel is a measure from an individual traveler’s perspective. In con- cept, it is measured as the difference between the desired condition and the conditions being analyzed. 4. Variation. This key component describes the change in the other three elements. Recurring delay (the regular, daily delay that occurs due to high traffic volumes) is rel- atively stable. Delay that occurs due to incidents is more difficult to predict. The relationship among the four components may be thought of as a three-dimensional box describing the magni- tude of congestion. Exhibit 2.2 illustrates three dimensions— duration, extent, and intensity—of congestion. These pre- sent information about three separate issues: 1) how long the system is congested, 2) how much of the system is af- fected, and 3) how bad the congestion problem is. The vari- ation in the size of the box from day to day is a measure or indicator of reliability, i.e., the more extreme and un- predictable the variation from one time period to another, the poorer the reliability of the facility or system being measured. 2.2.5 Summarizing Mobility and Reliability Effects Using Four General Components Developing a summary of mobility and reliability using concepts similar to those used for congestion will ensure that the appropriate measures are used. A similar typology uses different terms; there is a positive tone in the phrasing of the definitions and a slightly different orientation from conges- tion, but the aspects are basically the same. The image of a box also is appropriate to the description of the amount of mobility and reliability provided by a transportation and land use system. The axes are time, location, and level. Reliability is now the change in box volume. • Time. The time that mobility and/or reliability is provided or available is an expression of the variation of mobility and/or reliability through the day, week, or year. It can be a function of the existence of congestion or the presence of transit service, operational improvements, or priority treatments. It can be measured as the times when travelers can get to their destinations in satisfactory travel times. • Location. The places or trips for which mobility and relia- bility are available is an important aspect of measurement for transportation and land use analyses, as well as for other issues such as economic development and social eq- uity. It can be described by accessibility maps and statistics and travel time contours that illustrate the areas that can be traveled to in a certain period of time. Descriptions of transit routes or special transportation services also can be used to identify locations where mobility and reliability are possible by more than private auto modes. • Level. The amount of mobility and reliability provided is analogous to the intensity of congestion. The amount of time it takes to travel to a destination and whether this is satisfactory are the key elements of the level of mobility and

13 reliability. It can be measured with a congestion index or accessibility statistics. • Reliability. The changing times, locations, and levels of mobility and reliability are important characteristics for mobility and reliability measurement. This is particularly important to freight movement operations that rely on the transportation system as an element of their productivity and to measuring the frustration level of travelers faced with an unexpected loss of mobility or reliability. The total amount of mobility and reliability provided to travelers in an area is the volume of a box with axes of time, location, and level. The reliability of the mobility provided to travelers and residents is the change in the volume of the box from time period to time period or from day to day. Exhibit 2.3 illustrates the description of mobility and reliability with the four aspects. These answer the key questions of travelers and residents: 1) When can I travel in a satisfactory amount of time? 2) Where can I travel in a satisfactory amount of time? 3) How much time will it take? 4) How much will my travel time vary from trip to trip? Answering the key questions with measures of the four components of mobility and reliability will encompass the needs of residents and travelers, as well as transportation and land use professionals. 2.3 Performance Measure Summary The overriding conclusion from any investigation of mo- bility and reliability measures is there is a range of uses and audiences. No single measure will satisfy all the needs, and no single measure can identify all aspects of mobility and re- liability—there is no “silver bullet” measure suited to every application or question. Mobility and reliability are com- plex and, in many cases, requires more than one measure, more than a single data source, and more than one analysis procedure. Mobility and reliability measures, when com- bined in a process to uncover the goals and objectives the public has for transportation systems, can provide a frame- work to analyze how well the land use and transportation systems serve the needs of travelers and businesses and provide the basis for improvement and financing decisions. Exhibit 2.4 provides a quick reference to selected mobility and reliability measures discussed in more detail in this chapter. It illustrates the measures, the input data required, and the general format of the equation required to calculate each measure. 2.4 Individual Measures Travel time, speed, and rate quantities are somewhat more difficult to collect and may require more effort than the traf- fic volume counts that currently provide the basis for most roadway analysis procedures. Travel speed-related measures can, however, be estimated as part of many analysis processes currently used. The ultimate implementation of a set of time- related mobility and reliability measures in most urban areas will probably rely on some estimating procedures along with archived data. These measures may include current Highway Capacity Manual-based analysis techniques (5), vehicle density measures estimated from detectors in the pavement or from aerial surveys or relationships that estimate travel rate, or speed from generally available volume and roadway characteristics. The use of estimating procedures will be particularly important in setting policy and the prioritization of transportation improvement projects, pavement design- ing, responding to developer requests for improvement, and performing many other analyses. The focus of this section is those measures most applicable to the individual traveler. Key characteristics about each mobility and reliability measure are summarized after the measures are presented. Summarizing the measure characteristics illustrates the flexibility of mobility and reliability measures based on time and person or freight movement. The delay per person or delay per peak-period traveler (in daily minutes or annual hours) can be used to reduce the travel delay value to a figure more useful in communicating to nontechnical audiences. It can normalize the impact of mobility projects that handle much higher person demand than other alternatives, where a measure of total delay might lead to different conclusions about the benefits of a solution. Delay for the primary route or road, in these alternatives, may be higher due to this higher volume, but this also indicates the need to examine the other facilities or operations within the corridor included in the “before” case. To the extent possible, the initial analysis should include as much of the demand that might move to the improved facility, route, or road. Time Level Location: The volume of the box is the amount of mobility and reliability provided. A change in volume of the box indicates the reliability of the system. Larger volume is better. Exhibit 2.3. Components of mobility (2).

14 Individual Measures 1 Delay per Traveler 60 minutes hour year 250 weekdays minutes Travel Time FFS or PSL inutes m Travel Time Actual annual hours Delay per Traveler Travel Time persons/vehicles Vehicle Occupancy vehicles Vehicle Volume miles Length minutes per mile Actual Travel Rate minutes person Travel Time Travel Time Index 2 minutes per mile FFS or PSL Travel Rate minutes per mile Actual Travel Rate Travel Time Index Buffer Index 2 100% minutes Average Travel Time minutes Average Travel Time minutes 95th Percentile Travel Time % Buffer Index Planning Time Index 2 minutes FFS or PSL Travel Time minutes 95th Percentile Travel Time no units Planning Time Index Area Measures 1 Total Delay persons/vehicle Vehicle Occupancy vehicles Vehicle Volume minutes FFS or PSL minutes Travel Time - Travel Time Actual = person - minutes Total Segment Delay Congested Travel vehicles Vehicle Volume miles Segment Length Congested = vehicle - miles Congested Travel Percent of Congested Travel 100 hicle persons/ve Occupancy icle eh V vehicles Volumei Vehicle miles Lengthi mile per minutes Ratei Travel Actual persons/vehicle Occupancyi icle eh V vehicles Volumei Vehicle minutes Timei Timei Travel FFS or PSL - minutes Travel Actual Travel Congested of Percent n i All segments i Each congested segment m 1 i 1 Area Measures 1 Congested Roadway miles Lengths Congested Segment = miles Congested Roadway Accessibility Target Travel Time Travel Time , Where e.g., jobs Objective Fulfillment Opportunities = opportunities Accessibility 1 “Individual” measures are those measures that relate best to the individual traveler, whereas the “area” measures are more applicable beyond the individual (e.g., corridor, area, or region). Some individual measures are useful at the area level when weighted by Passenger Miles Traveled (PMT) or Vehicle Miles Traveled (VMT). 2 Can be computed as a weighted average of all sections using VMT or PMT. Note: FFS = Free-flow speed, and PSL = Posted speed limit. Exhibit 2.4. Quick reference guide to selected mobility and reliability measures.

15 Equations 2.1.a and 2.1.b illustrate the computation of delay per traveler in annual hours. Equation 2.1.a is appropriate for a single section of highway where the delay (i.e., actual travel time minus free-flow travel time) for a number of travelers over the same segment can be averaged and then expanded to annual hours. Equation 2.1.b applies the same concept to a situation involving multiple highway segments of different lengths, and can be used to estimate average delay per trav- eler over a number of segments, routes or a system. In this case, the number of vehicles and occupants per vehicle is used in the numerator to expand and sum the total individual traveler delay over the various segments, and again in the de- nominator to reduce the summed traveler delay to an average amount per traveler. The Travel-Time Index (TTI) is a dimensionless quantity that compares travel conditions in the peak period to travel conditions during free-flow or posted speed limit conditions. For example, a TTI of 1.20 indicates that a trip that takes 20 minutes in the off-peak period will take 24 minutes in the peak period or 20 percent longer. The TTI can be quickly and easily interpreted by most users in both an absolute sense (e.g., a TTI of 1.5 means a free-flow 200-minute trip will take 30 minutes) or a relative sense (the trip will take 50 percent longer.) This dual mode is useful because for a very short trip even a rela- tively large percent increase in travel time may be insignificant. Conversely, for a longer trip, a relatively small percent increase in travel time may be significant in terms of late arrival. TTI reflects travelers’ perceptions of travel time on the roadway, transit facility, or other transportation network element. This comparison can be based on the travel time increases relative to free-flow conditions (or PSL) and com- pared to the target conditions. Thus, the same index formula can be applied to various system elements with different free-flow or posted speeds. Travel rate (in minutes per mile) is a direct indicator of the amount of travel time, which makes it relevant to travelers. The measure can be averaged for freeways and arterial streets using the amount of travel on each portion of the network. An average corridor value can be developed using the number of persons using each facility type (or modes) to calculate the weighted average of the conditions on adja- cent facilities. The corridor values can be computed for hourly conditions and weighted by the number of travelers or person-miles traveled to estimate peak period or daily index values. The TTI in Equation 2.2 compares measured travel rates to free-flow or PSL conditions for any combination of freeway and arterial streets. Index values can be related to the general public as an indicator of the length of extra time spent in the transportation system during a trip. Equation 2.2 illustrates a relatively simple version of the calculation using VMT, but PMT also could be used, as could a value of time calculation that incorporates person and freight travel. Travel Rate Index (TRI) is similar to the TTI in that it also is a dimensionless quantity that compares travel conditions in the peak period to travel conditions during free-flow or PSL conditions. The TRI measure is computed in the same way as the TTI, but does not include incident conditions. A typical ap- plication of the TRI would be calculating congestion levels from a travel demand forecasting model, because incident con- ditions are not considered in the model’s forecasts. In contrast, continuous data streams allow for the direct measurement of a TTI that includes incidents. For some analysis applications, however, incident conditions would intentionally be excluded. (Eq. 2.1.a) (Eq. 2.1.b) (Eq. 2.2)Travel Time Index Freeway TravelRate Freeway = Free-flow or Posted Speed Limit Rate Freewa × y Peak Period VMT ⎡ ⎣ ⎢⎢⎢ ⎤ ⎦ ⎥⎥⎥ + Principal Arterial Street TravelRate Principal Arterial Street Free-flow or PostedSpeedLimit Rate × Principal ArterialStreet PeakPeriod VMT ⎡ ⎣ ⎢⎢⎢⎢⎢ ⎤ ⎦ ⎥⎥⎥⎥⎥ Freeway Peak Period VMT +Principal Arterial Street Peak Period VMT Delay per Traveler (annual hours) Actual Travel T = ime (minutes) FFS orPSL Travel Time (minutes) − ⎛ ⎝ ⎜⎜⎜ ⎞ ⎠ ⎟⎟⎟ × × Vehicle Volume (vehicles) Vehicle Occupancy (persons /vehicle) 250week days year × × hour 60 minutes Vehicle Volume(vehicles) Veh× icle Occupancy (persons /vehicle) Delay per Traveler annual hours Actual Trave( ) = l Time minutes( ) − FFS or PSL Travel Time minutes 250 weekdays year hour 60 minu( ) ⎛ ⎝ ⎜⎜ ⎞ ⎠ ⎟⎟ × × tes

16 For example, when travel time runs are performed for a corri- dor study, those runs affected by incident conditions are nor- mally removed. This provides an estimate of the nonincident travel time along the corridor. In these conditions, the com- puted measure would be a TRI rather than a TTI. Buffer Index (BI) is a measure of trip reliability that expresses the amount of extra buffer time needed to be on time for 95 percent of the trips (e.g., late for work on one day out of the typical 20-work-day month.) As with the TTI, indexing the measure provides a time- and distance-neutral measure, but the actual minute values could be used by an individual traveler for a particular trip length or specific origin-destination (O-D) pair. With continuous data, the index is calculated for each road or transit route segment, and a weighted average is calcu- lated using vehicle-miles or, more desirably, person-miles of travel as the weighting factor. Travel rates for approximately 5-mile sections of roadway provide a good base data element for the performance measure. The BI can be calculated for each road segment or particular system element using Equation 2.3. Note that a weighted average for more than one roadway sec- tion could be computed using VMT or PMT on each roadway section. The measure would be explained as “a traveler should allow an extra (BI) percent travel time due to variations in the amount of congestion and delay on that trip.” (Eq. 2.3) The buffer time concept appears to relate particularly well to the way travelers make decisions. Conceptually, travel decisions proceed through questions, such as: “How far is it?” “When do I need to arrive?” “How bad is the traffic likely to be?” “How much time do I need to allow?” “When should I leave?” In the time allowance stage, there is an assessment of how much extra time has to be allowed for uncertainty in the travel conditions. This includes weather, incidents, construc- tion zones, holiday or special event traffic, or other disrup- tions or traffic irregularities. Planning Time Index represents the total travel time that should be planned when an adequate buffer time is included. Planning Time Index differs from the BI in that it includes typical delay as well as unexpected delay. Thus, the Planning Time Index compares near-worst case travel time to light or free-flow traffic travel time. For example, a planning time index of 1.60 means, for a 15-minute trip in light traffic, the total time that should be planned for the trip is 24 minutes (15 minutes * 1.60 = 24 minutes). The Planning Time Index is useful because it can be directly compared to the travel-time index on similar numeric Buffer Index (%) 95thPercentile Travel Time (min = utes) AverageTravel Time (minutes) AverageTra − vel Time (minutes) ⎡ ⎣ ⎢⎢⎢⎢⎢ ⎤ ⎦ ⎥⎥⎥⎥⎥ ×100% scales. The Planning Time Index is computed as the 95th percentile travel time divided by the free-flow travel time as shown in Equation 2.4. (Eq. 2.4) On-Time Arrival estimates the percentage of time that a traveler arrives on time based on an acceptable lateness threshold. A value in excess of the travel rate mean, say 10 percent to 15 percent, is used to identify the threshold of acceptable lateness or being “on time.” Required data include a sample distribution of trip times, whether for transit or highway trips. The On-Time Arrival percent is computed according to the following formula: %OnTime = PercentTripTimes <[1.10 * MeanTime] (Eq. 2.5) where %OnTime = Percent On-Time Arrivals; PercentTripTimes = Percent of measured trip times; and MeanTime = The computed mean of the measured travel time. Percent Variation is closely related to the Planning Time Index. It is expressed as a percentage of average travel time and is distance/time neutral. Multiplying the average travel time by the percent variation yields the total travel time needed to be on time 85 percent of the time (one standard deviation above the mean). Higher values of percent variation indicate less reliability. It is computed according to the fol- lowing formula: (Eq. 2.6) where %V = Percent Variation; Std.dev. = The standard deviation of measured travel time; and Mean = The computed mean of the measured travel time. The 90th or 95th percentile travel time is perhaps the sim- plest measure of travel-time reliability for specific travel routes or trips, which indicates how bad delay will be on the heaviest travel days. The 90th or 95th percentile travel times are reported in minutes and seconds and should be easily un- derstood by commuters familiar with their trips. For this rea- son, this measure is ideally suited for traveler information. This measure has the disadvantage of not being easily com- pared across trips, as most trips will have different lengths. It % * %V = std.dev. Mean 100 Planning Time Index no units 95th Percenti ( ) = le Travel Time minutes Travel Time Based on ( ) Free-Flow or PostedSpeed (minutes)

17 also is difficult to combine route or trip travel times into a subarea or citywide average. Several other statistical measures of variability have been suggested to quantify travel-time reliability, such as standard deviation and coefficient of variation. These are discouraged as performance measures, as they are not readily understood by nontechnical audiences nor easily related to everyday commuting experiences. The 90th or 95th travel time, or indexes such as the BI or Planning Time Index, are recom- mended as simpler ways to express the variability of expected travel time in a way that travelers can relate more directly to their travel expectations or experience. 2.5 Area Measures The mobility and reliability measures described in the pre- vious section mainly relate to the individual traveler making a particular trip. The measures described in this section are area measures where the area may be a corridor or region. These measures may be better suited to large scale system planning analysis. The total delay (in person- or vehicle-hours) for a transit or roadway segment is the sum of time lost due to congestion. Delay can be expressed as a value relative to free-flow travel or relative to the posted speed limit. Total delay in a corridor or an urban area is calculated as the sum of individual segment delays. This quantity is used to estimate the impact of im- provements on transportation systems. The values can be used to illustrate the effect of major improvements to one portion of a corridor that affects several other elements of the corridor. The quantity is particularly useful in economic or benefit/cost analyses that use information about the magnitude of the mo- bility improvement for cost-effectiveness decisions. Equation 2.7 shows the computation of delay in person- hours. In addition, using a delay measure of hours per mile of road, hours per 1,000 miles traveled, or hours per 1,000 travelers might be more meaningful to agencies at the corri- dor level, but the public may not understand these measures since it is difficult to relate to key travel decisions or travel experience. Congested travel is a measure that captures the extent of congestion. It estimates the extent of the system affected by the congestion. Equation 2.8 illustrates the computation of congested travel in vehicle-miles as the product of the con- gested segment length and the vehicle volume summed across all congested segments. The percent of congested travel is an extension of the con- gested travel measure. It also measures the extent of congestion. When speed and occupancy data are available for each roadway segment, this measure can be computed. It is computed as the ratio of the congested segment person-hours of travel to the total person-hours of travel. Equation 2.9 shows the computation. Congested roadway is another measure of the extent of congestion. It is the sum of the mileage of roadways that op- erate under free-flow or posted speed limit conditions. This is shown in Equation 2.10. (Eq. 2.10) Accessibility is a measure that often accompanies mobility measures. It quantifies the extent that different opportunities can be realized. These might be accessibility to jobs, a transit station, or other land use or trip attractor of interest. Acces- sibility is satisfied if the travel time to perform the desired ac- tivity is less than or equal to the target travel time as indicted in Equation 2.11. (Eq. 2.11) Accessibility opportunities Objective F ( )= ∑ ulfillment Opportunities e.g., jobs , Whe( ) re Travel Time Target Travel Time≤ Congested Roadway miles Congested Segm ( ) ∑ = ent Lengths miles( ) (Eq. 2.7) (Eq. 2.8) (Eq. 2.9) Percent of Congested Travel Actual Travel Time = i i minutes FFS or PSL Travel Time minutes( ) − ( ) ⎛ ⎝⎜ ⎞ ⎠⎟ × ( ) × Vehicle Volume vehicles Vehicle Occi upancy persons/vehicle i i ( ) ⎛ ⎝ ⎜⎜ ⎞ ⎠ ⎟⎟ ⎛ ⎝ ⎜⎜ ⎞ ⎠ ⎟⎟=1 Each congested segment Actual Travel Rat m ∑ e minutes per mile Length miles Vehicl i i( ) × ( ) × e Volume vehicles Vehicle Occupancy person i i( ) × s/vehicle All segments ( ) ⎛ ⎝ ⎜⎜ ⎞ ⎠ ⎟⎟ ⎡ ⎣ ⎢⎢⎢⎢ = ∑ i n 1 ⎢⎢⎢ ⎤ ⎦ ⎥⎥⎥⎥⎥⎥⎥ ×100 Congested Travel (vehicle miles) Congested Se − = gmentLength (miles) Vehicle Volume (vehicles) × ⎛ ⎝⎜ ⎞ ⎠⎟∑ Total Delay (persons hours) Actual Travel Time − = (minutes) FFS orPSL Travel Time (minutes) − ⎡ ⎣ ⎢⎢ ⎤ ⎦ ⎥⎥ × × Vehicle Volume (vehicles) VehicleOccupancy (persons /vehicle) 1hour 60minutes ×

18 Performance Measure Congestion Component Addressed Geographic Area Addressed Delay per Traveler Intensity Region, Subarea, Section, Corridor Travel-Time Index Intensity Region, Subarea, Section, Corridor Buffer Index Intensity, Variability Region, Subarea, Section, Corridor Planning Time Index, Percent Variation Intensity, Variability Region, Subarea, Section, Corridor Percent On-Time Arrival Variability Facility, Corridor, System Total Delay Intensity Region, Subarea, Section, Corridor Congested Travel Extent, Intensity Region, Subarea Percent of Congested Travel Duration, Extent, Intensity Region, Subarea Congested Roadway Extent, Intensity Region, Subarea Misery Index Intensity, Variability Region, Subarea, Corridor Accessibility Extent, Intensity Region, Subarea Exhibit 2.5. Key characteristics of mobility and reliability measures. Misery Index seeks to measure the length of delay of only the worst trips. The metric is computed by subtracting the average travel rate from the upper 10 percent (or 15 or 20 percent) of travel rates. This yields the time difference (as a proportion or percent) between the average trip and the slowest 10 percent of trips. It is computed according to the following formula: (Eq. 2.12) where MI = Misery Index; Mean(Top20%Times) = The mean of the highest 20 per- cent of measured travel times; and MeanTime = The computed mean of the measured travel time. For example, if the mean travel time of the slowest 20 percent of trips in a corridor is 90 minutes and the mean travel time of all trips in the same corridor is 60 minutes, the Misery Index is calculated as (90/60) – 1, or 1.5 – 1.0 = 0.5 (i.e., the slowest trips are 50 percent longer than the average trip). Exhibit 2.5 summarizes key characteristics of the primary mobility and reliability measures described in this section. The “components of congestion” have been defined as duration, extent, intensity, and variability or variation (2). Duration is the length of time during which congestion affects the system or facility. Extent can describe either the geographic distribution of congestion, or the number of people/vehicles/freight-tons affected by congestion. Intensity is the severity of the congestion, preferably from the traveler’s perspective, and is frequently expressed as the difference MI Mean(Top20%Times) MeanTime = −1 between desired conditions and the conditions being ana- lyzed. Variability refers to both regular and irregular changes in the other three components, and is a distinguishing com- ponent of reliability measures versus mobility measures. If enough is known about the variation in these other three components, for example, knowing the statistical distribu- tion of travel times on a given facility, then reliability meas- ures can be calculated that indicate, for example, the likeli- hood of arriving on time, the incremental amount of time required to be on time 95 percent of the time, etc. 2.6 Basic Data Elements This section describes the basic data elements used to de- fine the mobility and reliability measures described previ- ously. The units are noted for typical urban analyses. Travel time (in minutes) is the time required to traverse a seg- ment or complete a trip. Times may be measured directly using field studies or archived data from traffic management centers, or can be estimated using empirical relationships with traffic vol- ume and roadway characteristics, computerized transportation network models, or the projected effects of improvements. Segment or trip length (in miles) is the distance associated with the travel time. Length can be measured directly with a vehicle odometer or scaled from accurate maps but is typically an established item in a transit or roadway inventory database. Average speed (in miles per hour) for a segment can be used to calculate travel rate or travel times if field data are not readily available. Average travel rate (in minutes per mile) is the rate a segment is traversed or a trip is completed (Equation 2.13). Travel rates may be determined directly using travel-time

19 field studies, or can be estimated using transit schedules or empirical relationships (e.g., Bureau of Public Roads formula) between traffic volume and roadway characteris- tics (e.g., capacity). (Eq. 2.13) Person volume is the number of people traversing the segment being studied. The person volume can be collected for each travel mode or estimated using average vehicle occupancy rates for different types or classes of vehicles. Freight volume is the amount of goods moved on a transport segment or system. It can be measured in units of ton-miles if the data are available, or it can be described more simply from truck percentages in the traffic stream. Freight volume may be particularly important in analyses dealing with travel-time reliability due to the sensitive nature of “just-in-time” manufacturing processes and goods delivery services. Person-miles of travel is the magnitude of travel on a sec- tion of the transportation system or on several elements of the system. It is a particularly useful measure in corridor and areawide analyses where total travel demand is used in calculations. Equation 2.14 indicates it is the product of distance and person volume. Person volume can be esti- mated as the product of vehicle volume and average vehi- cle occupancy. (Eq. 2.14) Target travel time (in minutes) is the time that indicates a system or mode is operating according to locally determined performance goals. It focuses on the door-to-door trip time from origin to destination. The target travel time can be differentiated by the purpose of the travel, the expectation for each mode within the transportation system, the type of activity, and the time of day. It should be influenced by com- munity input, particularly on the issue of the balance between transportation quality, economic activity, land use patterns, and environmental issues. Target travel rate (in minutes per mile) is the maximum rate (slowest speed) a segment is traversed or a trip is completed without experiencing an unsatisfactory level of mobility. The target travel rate is based on factors similar to the target travel time. This is similar to the process used by many states and cities where a target level of service (LOS) is used to determine the need for additional transportation improvements. In practice, there also will be a need for a corridor average travel rate value. This would be used as the target for facility Person-miles of Travel PMT Person Volume pe( ) = rsons Distance miles( ) × ( ) Travel Rate (minutes per mile) Travel Time min = utes Segment Length miles 60 Average Spee ( ) ( ) = d mph( ) expansions, operating improvements, program enhance- ments, or policy implementations. The facility/mode target travel rates can be used for evaluation, but improvement strategies and amounts should be based on corridor-level decisions. 2.7 Definition and Discussion of Speed Terms This section provides definitions of primary speed meas- ures and guidance on their use in mobility and reliability analyses. FFS is the average speed that can be accommodated under relatively low traffic volumes (i.e., no vehicle interactions) on a uniform roadway segment under prevailing roadway and traffic conditions. It can be calculated or estimated in a number of ways, with a common approach being to use the 85th percentile speed in the off-peak period. The off-peak periods can be defined by time period (e.g., overnight = 10:00 p.m. to 6:00 a.m., or midday = 9:00 a.m. to 4:00 p.m.) or vehicle volume. Vehicle headways of 5 seconds or more could be used to define FFS operating conditions (i.e., traffic volumes of approximately 700 vehicles per hour per lane [vphpl]). Ideally, a continuous data source (e.g., ITS, Weigh-in-motion [WIM], Automatic Traffic Recorder [ATR], etc.) could be used to identify the FFS using at least one year of valid data. PSL is the posted speed of the roadway. For specific facilities or sections thereof this value is obtained by field data collec- tion. Posted speed is a typical roadway inventory data element; therefore, posted speeds can be obtained from such roadway inventories, particularly for a system-level analysis that includes numerous facilities. Target speed is the speed associated with the target TTI. The target speed can be computed given the target TTI and the free-flow travel rate or the PSL travel rate. 2.7.1 Threshold Speed Values Many analyses begin with the question, “What should we compare to?” The issue usually can be framed as a choice between using a desirable condition or using an achievable condition given the funding, approval, and other con- straints. It should be noted that PSLs are included in most roadway inventory files and should be readily available for analytical procedures. Computerized analysis procedures should be modified so that a negative delay value is not in- cluded in the calculations. If estimated FFS are used in the calculation of delay, the speed data collected from field studies may include values with very fast speeds (above the FFS). FFSs higher than the PSL may present an illegal

20 appearance problem when used in public discussions. In addition, it may be difficult to justify delay being calculated for travel at the PSL. 2.7.2 When Would I Use Free-Flow Speed in Mobility and Reliability Measure Computation? Delay and congestion index measure computations can be computed relative to FFS. Using FFS for these computa- tions is most appropriate when continuous data sources that allow for the computation of the 85th percentile speed in the off-peak period are available. The use of a FFS pro- vides an automated and consistent method for computing delay and index values across different metropolitan areas. The FFS also could be used when the analyst does not have ready access to posted speeds along the corridors included in a mobility and reliability analysis, particularly large areawide analyses. 2.7.3 When Would I Use a Posted Speed Limit in Mobility and Reliability Measure Computation? PSL also can be used to compute delay and index measures. PSL can be used when continuous data are not available for the mobility or reliability analysis. PSLs are an easy to com- municate threshold, are more stable than FFSs, and do not require value judgments of assessments of goals or targets. 2.7.4 How Can the ‘Maximum Productivity’ Concept be Used? Maximum productivity (i.e., the combination of relatively high vehicle volume and relatively high speed that provides the most efficient roadway operation) is a goal for traffic man- agement professionals. It is gaining a useful place in commu- nication with nontechnical audiences as the target for agencies moves from free-flow travel to reliable service at all times. This target reflects the general acceptance of congestion for a few hours each day in major metropolitan regions. The concept can be used in the same manner that a target condition is implemented by both planners and operators. 2.7.5 How Does the Target Travel-Time Index Relate to the Computed Measures? Target TTI values could be developed with input from citizens, businesses, decision makers, and transportation professionals. The target values represent the crucial link be- tween two objectives: 1) the vision that the community has for its transportation system, land uses, and its quality of life issues and 2) the improvement strategies, programs, and projects that government agencies and private sector interests can implement. Planners can use the targets to identify prob- lem areas and judge which strategy meets both objectives. The values are desirably the result of a process integrated with the development of the long-range plan, but they must be reasonable and realistic since overstatement or understate- ment could distort the assessment of congestion. Urban areas should approach the use of a target TTI with a corridor and system strategy. The target value may be devel- oped for every mode or facility as a way to identify individual performance levels, but the key application will be as a corri- dor or system target. Individual facility deficiencies can be addressed through improvements to that mode or route or by other travel mode improvements, strategies, or policies. For example, the freeway main lanes may not satisfy the target value, but if an HOV lane is successful in moving a large num- ber of people at high speeds, the average TTI, when weighted by person volume, may achieve the target value. Target TTI value can be “adjusted” appropriately irre- spective of whether a FFS or a PSL is used in the calculation of the TTI. For example, if FFS is used, the target TTI value might be 1.4, whereas the target TTI value might be 1.3 if the PSL is used. 2.7.6 Summary and Guidance FFS is better for matching how people drive given the roadway operating conditions (i.e., “I was traveling 5 mph over the PSL, and I was still being passed”). PSLs are some- times set for public policy reasons, rather than being tied to actual conditions making comparisons between regions or comparisons over several years difficult. PSLs could go down, reducing the apparent delay, and yet if peak-period speeds declined, which should show more congestion, there could be less reported delay. These considerations should be evaluated when determin- ing the appropriate reference (FFS or PSL) in delay and index computations for the community and stakeholders involved with the analysis. 2.8 Other Data Elements Several other factors are needed to perform mobility and reliability analyses, including the following: • Hourly volumes, expressed in vehicles or persons, may be very useful for the peak period or 24-hour periods. Many roadway and transit analyses focus on the peak hour, but in most large cities this is not enough information to assess the mobility and reliability situation or to analyze alternatives.

21 A range of improvements, including demand management, advanced traveler information systems, and HOV lanes, have an effect on other hours in the peak period. • Daily volume variation is the variability in person or vehi- cle volume from day to day. These data are particularly im- portant in analyses that examine mobility and reliability levels on particularly heavy volume days (e.g., Fridays or days before holidays) or days/time periods with different travel patterns (e.g., special events or weekends). • Incident information includes the number and duration of crashes and vehicle breakdowns that occur on roadway segments and transit routes. This information is used in analyses of the variation in mobility and reliability. The re- liability of transportation systems is a particular concern in analyses of incident management programs, value pricing projects, and freight movement studies. • Weather information can explain a significant amount of the variation in travel conditions. Snow, ice, fog, and rain can be noted in a database used for mobility and reliabil- ity analyses. • Road work information includes construction and main- tenance activities and their location. This includes the lo- cation, number of lanes affected, and time period. • Peak direction hourly travel demand and volume are two measures of person or vehicle travel used in system analy- ses. The two may be the same for uncongested corridors. Demand is higher than volume in congested corridors, however, and the “excess” volume travels on the main route in hours adjacent to the peak hour and on alternate routes. Improvements to primary routes or travel modes may result in higher traffic volumes in the peak hour that can be predicted if demand is estimated. 2.9 Time Periods for Analysis Selecting the appropriate time period is an important part of building the data collection plan and analysis frame- work. Considerations include the nature of the problem(s) to be addressed through the analysis, the geography of the study area, and the presence of any special seasonal events or conditions that could dramatically alter data or interpre- tation of results. 2.9.1 Peak and Off-Peak Period Analysis Peak period is the time period most often used for urban mobility and reliability analyses. Off-peak periods may be of interest to study the extent of peak spreading at one area com- pared to another area. The TTI is computed relative to the FFS or PSL. If the analyst is investigating the TTI of an off- peak period that is beginning to experience congestion, the TTI could be used to illustrate the increased congestion if the actual travel rate during the off-peak is higher than the target value. The BI and delay measures also could be useful in the off-peak period in locations that may be experiencing some congestion in the off-peak. 2.9.2 Daily Analysis Analysis using daily averages is often less useful with the TTI and BI. Using 24-hour speeds for computing the TTI is not meaningful because the measure is meant to com- pare peak and off-peak travel conditions. Likewise, the BI is intended to be a measure of reliability during a peak period. Daily values “wash out” the effect of congestion in peak periods with the longer off-peak periods. Total delay is more meaningful as a daily congestion measure. Though the total delay in person- or vehicle-hours is less meaning- ful to an individual driver, it is a good measure for analyz- ing trends from year to year. Daily delay is used in this manner in the FHWA-sponsored Mobility Monitoring Program (MMP). 2.9.3 Seasonal Analysis Investigating variations in mobility and reliability over the seasons of the year also may be of interest. Many areas have unique peaking characteristics due to seasonal events (e.g., academic calendars, sporting events, and tourism). These ac- tivities can alter the length and extent of the peak period. All of the measures discussed in this chapter can be used in a mobility or reliability analysis that compares peak or off-peak period measure changes by month of year. 2.9.4 Urban or Rural Analysis The preceding discussion has assumed an urban mobility or reliability analysis. Rural locations also can be the subject of mobility and reliability analyses. For example, there might be an interest in freight movements in rural areas. Special events and tourism activities also are situations that may generate interest in a rural analysis. As mentioned previously, continuous data sources provide speed (travel time), volume, and classification information in some urban areas. Point-to-point travel-time information also is of interest for rural freight operations. As with travel conditions on an urban congestion map, such point-to-point travel-time information would allow insight into rural freight operations. Transponders could be used to provide the continuous information. The University of Washington is in- vestigating such applications in rural areas in the state of Wash- ington. Of the primary measures discussed in this chapter, TTI and delay measures could be used for this rural application. The TTI could be used to compare current travel rates to a

22 Mobility and Reliability Measures Analysis Area Tr av el T im e Tr av el R at e A nn ua l D el ay Pe r Tr av el er Tr av el -T im e In de x Bu ffe r In de x To ta l D el ay C on ge st ed Tr av el Pe rc en t o f C on ge st ed Tr av el C on ge st ed R oa dw ay A cc es sib ili ty Individual Locations S S P P S Short Road Sections P P S P P S Long Road Sections, Transit Routes or Trips S S P P S Corridors S S P P P S Subareas S P P P P P P P P Regional Networks S P P P P P P P P Multimodal Analyses S P P P P P P = Primary measure, and S = Secondary measure. Note: Measures with delay components can be calculated relative to free-flow or posted speed conditions. Exhibit 2.6. Recommended mobility and reliability measures for analysis levels (1). target travel rate for goods movement over the corridor of in- terest. If continuous data sources are available (e.g., toll tags or cellular telephone), the BI also could be computed for freight carriers. Prior to real-time systems, estimation measures could be used to estimate delay for goods movement. Special events and tourism also may invite mobility and reliability analyses in a rural area. If real-time equipment already is installed, it could be used to obtain travel rate infor- mation to compare to a target travel rate. Delay also could be computed. For a special event, and possibly for a tourism activity/season, portable readers also could be installed to monitor mobility and reliability along rural corridors of interest. 2.10 The Right Measure for the Analysis Area Exhibit 2.6 summarizes the mobility and reliability meas- ures that should be used for several types of analyses and for different size areas or modal combinations (6, 1). Individual traveler measures such as travel rate and the TTI are very use- ful for analysis up to the corridor level. At higher levels of analysis, magnitude statistics such as delay and accessibility also are useful. Examples of the application of these measures to situations based on the level of analysis are included in the following sections. Most mobility and reliability studies should be conducted at geographic areas higher than individual locations and short sec- tions of roadway. At relatively small areas, the studies will typi- cally be limited to near-term analysis of operational improve- ments where new modes or facilities are not realistic options and even the operational improvements will be limited. These analyses may proceed using HCMl-type procedures. Total delay, delay per person, and travel-time difference are most use- ful for intersections or individual locations due to problems identifying the length needed for the rate-based measures. Larger scale analyses, where more detailed analytical tools are used and a wider choice of improvement options is con- sidered, are more frequently identified as mobility or relia- bility studies. The analysis and presentation of mobility and reliability data can be accomplished by the TTI, BI, TRI, total delay, and accessibility as primary measures. Secondary measures also may be used for cumulative analyses of several improvements and estimation of benefits. Mobility and reliability for larger areas of analysis, such as long roadway sections and corridors can be quantified with some individual statistics if the roadways are of the same type. But if freeways, streets, and/or other travel modes are in- cluded, cumulative statistics, TTI, and BI are very appropri- ate. Index statistics become useful at this higher level of analy- sis when multiple roadways and large numerical values (e.g., statistics expressed in thousands or millions of hours) make interpretation of relative conditions difficult. 2.11 The Right Measure for the Type of Analysis The recommended uses in Exhibit 2.7 are another illustra- tion of how the mobility and reliability measures vary by the scope of the analysis, but not by mode or facility included in

23 the analysis (1). Travel time and speed measures, and data and estimating techniques used to create them, are flexible analysis tools. When combined with person and freight movement quantities, they illustrate a range of mobility and reliability situations. Different values will be used for the tar- get travel rate or target travel time depending on the facility type or travel mode, but the calculation and application of the measures are identical. While it is difficult to cover every type of mobility and reliability analysis, Exhibit 2.4 illustrates recommended measures for many common types of studies and informa- tion requirements. As with Exhibit 2.6, the analyses where small areas are analyzed or quick answers are needed use simple measures. More complex analyses, those that typi- cally cover larger areas or multiple modes and those target- ing nontechnical audiences, use index measures and sum- mary statistics. 2.12 Index Measure Considerations Following are a few additional considerations to take into account when using performance measures, particularly those dimensionless indexes such as the TTI or BI that are not expressed in familiar units such as minutes or miles per hour. Setting targets or benchmarking to a regional or national standard is one possible approach. Expressing targets and performance results in a user-familiar context such as the door-to-door trip time is another. Mobility and Reliability Measures Uses of Mobility and Reliability Measures Tr av el T im e Tr av el R at e D el ay p er Tr av el er Tr av el -T im e In de x Bu ffe r In de x To ta l D el ay C on ge st ed Tr av el Pe rc en t o f C on ge st ed Tr av el C on ge st ed R oa dw ay A cc es sib ili ty Basis for government investment or policies P P P P P P P P Basis for national, state, or regional policies and programs P P P P P P P P Information for private-sector decisions P P S P P S P P P Measures of land development impact P P P P P P S S S P Input to zoning decisions P P P P P Inputs for transportation models P P P Inputs for air quality and energy models P P P P Identification of problems P P P P P S S S S Base case (for comparison with improvement alternatives) S P P P S S S P Measures of effectiveness for alternatives evaluation P P P P P S S S P Prioritization of improvements P P P P S Assessment of transit routing, scheduling, and stop placement P P P P P S Assessment of traffic controls, geometrics, and regulations P P P Basis for real-time route choice decisions P P P P P P = Primary measure; and S = Secondary measure. Exhibit 2.7. Recommended mobility and reliability measures for various types of analyses (1).

24 2.12.1 How Much Congestion Is Too Much? Analyses of system adequacy, the need for improvements, or time-series analyses conducted in a corridor or area can benefit from comparisons using target conditions. Free-flow conditions will not be the goal of most large urban transportation improvement programs, but using them provides a consistent benchmark relevant for year-to- year and city-to-city comparisons. The attainment of goals standard also might be used at the national or state level, but will be used more often during a discussion of planning and project prioritization techniques. The use of a target travel rate can improve the guidance pro- vided to system planners and engineers. If the target travel rates are a product of public discussion, they will illustrate the bal- ance the public wishes to have between road space, social ef- fects, environmental impacts, economic issues, and quality of life concerns. Areas or system elements where the performance is worse than the target can be the focus of more detailed study. A corridor analysis, for instance, might indicate a problem with one mode, but the solution may be to improve another mode or program that is a more cost-effective approach to raising the corridor value to the target. The amount of corridor or area- wide person-travel that occurs in conditions worse than the locally determined targets can be used to monitor progress toward transportation goals and identify problem areas. 2.12.2 Relationship to Door-to-Door Travel-Time Measures The measure of system performance closest to the concern of travelers is door-to-door travel time. Any performance measure should relate to door-to-door travel time as closely as possible. Calibrating the user view of system performance with measures that can be more readily collected from existing data sources is the key to the efficient and effective presentation of mobility and reliability information. Periodic updates of public opinion can be used to adjust corridor and areawide determinations of service quality. Ten pairs of O-D trip pat- terns, for example, could be used to show the change in travel time. The information for these key travel patterns can be updated daily, monthly, or annually with system monitoring equipment. Every five years the key patterns could be reexam- ined for relevance to the existing and future land use develop- ment patterns and transportation system. Using target conditions as the comparison standard pro- vides the basis for a map or table showing system deficien- cies in a way readily understood and uniquely relevant to improvement analyses. A map showing the target travel rates on the system links would accompany such a presen- tation. This approach also could be easily used in a multi- modal analysis, with a target TTI for the corridor. Future travel rates for the corridor can be changed by improving a facility or service, or by shifting travel to other modes/ facilities. The target comparison standard would be broader than simply a mobility or reliability measure since it would directly incorporate the idea that the goal for a corridor is not always high-speed travel. It could be used in conjunc- tion with an areawide planning effort to relate the link speeds, used in estimating the TTI, to the outcome measures of door-to-door trip satisfaction. 2.12.3 Impact on Data Collection One outcome of a move to the travel-time-based measures would be the ability to include directly collected travel-time data from the various transportation system elements. Many areas do not collect this information, but the initial statistics can be developed from estimates of travel speed. As travel- time studies are conducted or archived data systems devel- oped, the actual data can be used to replace the estimates in the index, as well as to improve the estimation processes. The information derived from systems that automatically collect and analyze travel speed over sections of freeways provide a significant resource for travel-time-based performance meas- ure calculation.

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TRB's National Cooperative Highway Research Program (NCHRP) Report 618: Cost-Effective Performance Measures for Travel Time Delay, Variation, and Reliability explores a framework and methods to predict, measure, and report travel time, delay, and reliability from a customer-oriented perspective.

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