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Suggested Citation:"Chapter 1 - Introduction." 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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Page 5
Suggested Citation:"Chapter 1 - Introduction." 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.
×
Page 5
Page 6
Suggested Citation:"Chapter 1 - Introduction." 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.
×
Page 6
Page 7
Suggested Citation:"Chapter 1 - Introduction." 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.
×
Page 7
Page 8
Suggested Citation:"Chapter 1 - Introduction." 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.
×
Page 8
Page 9
Suggested Citation:"Chapter 1 - Introduction." 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.
×
Page 9

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4This guidebook presents methods to measure, predict, and report travel time, delay, and reliability using data and analytical methods within the reach of a typical transportation agency. This analysis framework allows consideration of many, though not all, of the multiple dimensions of surface transportation system performance: time of day; transit and highway modes; passenger and freight vehicles; and levels of aggregation such as facility type and system/corridor/segment perspectives. An analytical framework oriented to the planner or analyst faced with typical questions about system performance, such as iden- tifying existing or future system deficiencies, spotting and reporting trends, evaluating the effectiveness of proposed or completed improvements, comparing alternative courses of action to address a problem or need, and improving the opera- tions and productivity of a fleet of vehicles such as transit buses or trucks, has been developed. The analysis framework and methods defined below will allow users to develop and apply measures of travel time, delay, and reliability that relate to the user’s perspective, but that also are valuable to the decision makers with responsibil- ity for planning and operating transportation facilities or serv- ices. While performance measures of all kinds are useful in management and performance reporting by the responsible agencies, travel-time-based measures are of special interest to the traveling public and elected decision makers because these measures relate directly to the user perspective, such as: • How long will a trip take? • How much longer/shorter will it take if I leave earlier/later? • How large a cushion do I need to allow if I cannot afford to be late at all? Similarly, these methods can be used by system planners to provide answers to decision maker’s questions, such as: • How much longer will a typical trip take if a particular trend continues? • Which of these competing improvement projects will most favorably affect system congestion and/or reliability? These methods and measures are useful in system plan- ning, corridor development, priority programming, and operations to improve transportation system performance and to enhance the customer’s experience and satisfaction with the system. The framework presents various data collection methods, analysis approaches, and applications that most effectively support transportation planning and decision-making for capital and operational investments and for quality-of-service monitoring and evaluation. The methods can be applied in settings with different levels of complexity, including agencies ranging from those with continuous data collection proce- dures and sophisticated data processing and analysis capabil- ities, to those with more limited resources. Data collection and processing techniques are provided that will allow calculation of travel time- and delay-based performance measures in a variety of agency settings. Estimating or forecasting the reliability of a transportation facility or system, defined here as the variability in travel time or delay, effectively requires continuous data collection sources. The guidebook does not provide a method for estimating travel-time reliability for data-poor situations. Research and analysis of available data conducted for this proj- ect concluded that agencies must have continuous surveillance capabilities, or nearly so, in order to provide useful estimates of reliability. 1.1 Why Measure Travel-Time Performance? State departments of transportation (DOT), metropolitan planning organizations (MPO), transit authorities, and other transportation stakeholders are increasingly turning to per- formance measures to gain and sustain public and legislative C H A P T E R 1 Introduction

5support for the management and stewardship of transporta- tion systems. This trend responds to calls for increased accountability for expenditure of public funds, better consid- eration of user and stakeholder priorities in selecting from among competing project opportunities, and a rational desire to improve the quality of information upon which such deci- sions are based. At the same time, system users—the traveling public, as well as commercial operators—are increasingly sensitive to delay and unreliable conditions. By measuring travel-time performance, and related system metrics based on travel time, agencies will be better able to plan and operate their systems to achieve the best result for a given level of investment. At the same time, travelers, shippers, and other users of those systems will have better information for plan- ning their use of the system. Agencies are seeking to develop and employ system performance measures that express congestion and mobility in terms that decision makers and system users can appreci- ate and understand. Interest specifically in measures of travel time, delay, and reliability is increasing, as system users seek to gain more control over their trip making decisions and outcomes. Interest also is increasing in measurements that individuals can use to reduce the uncertainty and loss of productivity that occur when system reliability is low. This growing demand for available measures of mobility and congestion that are travel time-based and user-friendly has pointed out the need for improved monitoring and ana- lytical procedures to generate the measures. These methods need to be able to measure and predict how individual trav- elers and goods movements will be affected by incidents and other sources of nonrecurring delay, as well as by capital and operational improvements to different components of the transportation system. Use of travel time, delay, and reliability as performance meas- ures is hampered by complex data requirements, data accuracy issues, and inadequate procedures for incorporating these measures into the transportation planning process. One reason these measures have not been more widely implemented is they can be expensive and difficult to generate. A relatively small per- centage of public transportation planning agencies have the data collection programs or analytical forecasting capabilities to generate reliable estimates of these measures. In many states, travel-time data are available for relatively few corridors. The high costs associated with more comprehensive data collection programs deter many states from investing in such programs. States and MPOs are using loop detector data and other data collected by intelligent transportation systems (ITSs) or traffic management systems (TMCs) to develop travel time, delay, and reliability measures, but these efforts too are fairly sophisticated, limited in extent, and at present, costly. As a result, agencies are in need of methods for generating travel-time-based performance measures that are relatively straight-forward to use and can be driven with existing and readily available data sources. To date, much of the work on travel-time-based measures has focused on utilizing relatively comprehensive and deep data sets generated for traffic man- agement systems via continuous, automatic data collection processes. This guidebook strives to present methods for generating similar measures using data that are more likely to be readily available to the typical transportation planning or operating agency. Much work previously has been conducted to develop effective measures of congestion, and to present the data collection and analysis methods required to generate the meas- ures. More recently, measures of reliability have similarly been studied and published, making better use of continuous data sources. References to these other excellent resource docu- ments are made where additional detail and context would be useful to some users. We find, however, that most of the exist- ing published work on congestion and reliability measurement focuses on monitoring and reporting existing values and historical trends, and not on application of the measures to the “what-if” type of questions prevalent in system planning. This guidebook, and NCHRP Project 7-15 on which it is based, strive to help fill the need for practical advice on use of relevant mobility and reliability measures in typical planning applica- tions. The main objective of these applications is to inform a planning process (e.g., to identify needs and suggest appropri- ate solutions) and support decision-making about some future action or investment in the transportation system. Thus, this guidebook places more emphasis on estimating and forecast- ing future values of performance measures and comparative analysis of hypothetical situations. 1.2 How to Use the Guidebook This guidebook is intended for use by analysts familiar with various forms of quantitative analysis, including basic statistical analysis. The information presents the fundamen- tal steps necessary to conduct the most common planning analyses for which travel-time-based measures can be useful. The remainder of Chapter 1 presents an orientation to the process of measuring mobility and reliability. While the material in Section 1.4 may be familiar to many readers, it is useful to repeat the logical sequence of activities that describe performance-based planning analysis. This process starts with the guiding vision or goals, and proceeds through such essential steps as identifying the audience; considering possi- ble solutions; selection and calculation of performance meas- ures; testing alternatives; and summarizing results. This discussion provides a point of departure for more detailed material that follows. The common elements of typical planning applications are explained in detail in Chapters 2 through 7, where specific

6guidance is given, formulas for calculating measures are provided, and references made to other well-accepted, pub- lished sources of guidance. These steps include selection of appropriate measures, data collection and processing, and specific fundamental or “building block” applications, such as deficiency analysis or alternatives analysis. These steps can be applied in varying combinations to address a high percentage of the planning applications and decisions an analyst is likely to confront for which travel-time, delay, and reliability information will provide useful decision support. Chapter 8 provides additional guidance on reporting performance results and incorporating those results into plan- ning processes. Six typical planning applications are illustrated, covering a large spectrum of likely applications for travel-time and reliability measures in planning. The approach to each ap- plication is described in terms of the building blocks contained in Chapters 2 through 7. 1.3 Limitations of the Guidebook The focus of this guidebook and its procedures are plan- ning applications. These applications generally involve the assessment of current or future performance for a large regional system of facilities or significant individual compo- nents of such a system. The emphasis is on procedures that provide no more precision in the results than is commensu- rate with the precision with which current measurements or future forecasts can be made for large systems of facilities and whose data needs and analytical requirements are similarly consistent with planning-level applications. These procedures are not intended to replace or be equal in precision to those procedures commonly used for the evalua- tion of individual intersections or road segments or even individual facilities. Rather, these procedures are intended to support a higher-level screening process used to identify defi- ciencies in existing and future system performance, and to identify types of improvements that would be most cost- effective at correcting these deficiencies. When the decision is made to proceed with a specific project to correct a deficiency, the agency designing the project will want to use more specific and precise procedures for assessing whether the improve- ments meet agency performance objectives, engineering stan- dards, cost constraints, and other relevant considerations. Where results of a systems planning-level assessment conflict with the results of a detailed facility-specific analysis, the analysis using more precise data is generally more accu- rate and reliable. However, the analyst should recognize the possibility of procedural or technical errors, regardless of the extent and detail of the data employed in the analysis. Professional judgment and experience should be applied to the interpretation and validation of the results, regardless of the level of detail of the analysis. Although several of the recommended performance meas- ures presented are derived from the perspective of the indi- vidual traveler (e.g., delay per traveler and several of the travel-time-based indexes), the analytical methods defined are not intended to drive traveler information (TI) systems or programs. While travel-time measures are becoming more common components of TI programs, the methods in this report are specifically designed to be applied using less com- prehensive, less real-time data than is typically used for TI. In order for reports or estimates of travel time to be useful to system users en route or planning an imminent trip, they need to be based on near real-time and historic data. In con- trast, planning applications will be more reliable and useful if they are based on trends and on predictive relationships between commonly available data and system performance. 1.4 Measuring Mobility and Reliability The need for meaningful mobility and reliability informa- tion is best satisfied by travel-time measures. Travel-time measures do not preclude the use of other data, procedures, surrogates, or models when appropriate. The key is that the set of mobility and reliability measures should satisfy the needs of analysts and decision makers, and the presentation of that information should be tailored to the range of audiences. The decision process used by travelers to select trip modes and routes, and by the transportation or land use professional analyzing alternatives, is influenced by travel time, conven- ience, user cost, dependability, and access to alternative travel choices. Travel time also is used to justify capital and operating improvements. A system of performance measurement techniques that uses travel-time-based measures to estimate the effect of im- provements on person travel and freight movement offers a better chance of satisfying the full range of potential needs than conventional level of service (LOS) measures. Techni- cal procedures and data used to create the LOS measures can be adapted to produce time-based measures. The proce- dures were developed in a time when construction was typically the selected option. Operational improvements generally were implemented on a smaller scale and cost level. The more complicated situation that transportation professionals face in the 21st century means that new tech- niques and data are available, but the analysis needs are broader, must address transportation system management and operations, and often cross traditional modal and fund- ing category boundaries. Measuring mobility and reliability is a task performed in a variety of ways, in several different types of analysis, and for many purposes. While the measures often are dictated by

7Define the Problem and Identify Preliminary Scope of Solutions STAGE 2A: Identify the Measures Consider Possible Solutions Develop a Set of Mobility Measures STAGE 3: Perform Analysis and Evaluate Alternatives Collect or Estimate Data Elements Identify Problem Areas Test Solutions STAGE 2B: Identify Analysis Procedures Develop Analysis Procedures Identify the Uses and Audiences STAGE 1: Identify the Vision and Goals Lomax, T., et al. (1). Exhibit 1.1. Illustration of mobility and reliability analysis process (2). legislative or regulatory mandates, it is useful to view the selection of the measure or measures as an important task to be accomplished before the data are collected and the estimation or calculation procedures begin. This section identifies key elements necessary for a complete analysis that includes travel time, speed, and reliability measures. As with any process, the continuous evaluation of assumptions, methods, and techniques will lead to improvement; it is important to compare the measures with the uses throughout the process and adjust the measures as necessary. It also is important to recognize that there are many analytical tech- niques that relate to mobility and reliability measurement. The steps outlined in this section are part of many of those procedures. Exhibit 1.1 provides an overview of the three- stage process to measure mobility and reliability. Each stage contains one to three considerations that are described in more detail in the following subsections. For additional information on each of the sections described in this chapter, the reader is encouraged to review NCHRP Report 398, Quantifying Congestion (1). 1.4.1 Identify the Vision and Goals The long-range plan for an area or system ideally contains a description of the situation the public wishes to create through investment, operation, and maintenance. As an im- portant element of that plan, existing transportation facilities must be analyzed, and improvements (if any) identified. In order for the selected programs and projects to move the area toward the vision, the measures must enable the selection of transportation improvements of the type and scale appropri- ate to the situation. A similar line of thinking applies at the detailed level (e.g., street, bus route, or demand management program). While the improvement options may not be as broad, and the financial investment may not be as great, it is always instructive to think about desirable outcomes or adverse impacts before beginning the analysis. Not only will this ensure proper consideration of all options, it also will lead to selection of measures that can fairly evaluate the range of alternatives. It is this step where the expectations of the public and policy makers can be formulated into a set of statistics that can be used at the project or program evaluation level. The “agreed upon norms” of the stakeholders are used to identify broad outcome goals to be considered by the engineer, planner, economist, or other professionals who must evalu- ate the need for an improvement. It is essential, therefore, that performance measures be consistent with the goals and objectives of the process in which they are being employed. Performance measures are key to controlling process outcome, whether the process is alternative selection, congestion management, growth management, or system management and operation. For example, within congestion management, performance measures are used for problem identification and assess- ment, evaluation and comparison of alternative strategies, demonstration of effectiveness, and ongoing system monitoring. Variations of the same measure may satisfy a range of uses. 1.4.2 Identify the Uses and Audiences The analyses and potential targets of the measurement process must be determined before the proper mobility and

8reliability measures can be selected. The set of measures must be technically capable of illustrating the problems and the effect of the potential improvements. They also must be able to be composed into statistics useful for the variety of poten- tial audiences. Increasing the flexibility of the measures also may improve the ability to use the information beyond the particular analysis. Corridor statistics also may satisfy annual reporting requirements, for example. Cost and schedule also are key considerations in the per- formance measure development process. Different uses and audiences frequently have different timelines for the delivery of performance measure results. The available budget is a related consideration. For example, consider the situation if your state legislature were to mandate the development and implementation of a statewide performance measurement program for all state facilities within six months. Clearly, the timeline is established (and short). The quality of the answer will depend upon the available budget for person- nel to develop the measures and accompanying estimation procedures. In contrast to such a legislative directive, con- sider an MPO that would like to fund a regional congestion management program that will develop and implement performance measures over a three-year period. Assuming adequate funding and all else is equal, certainly this exam- ple provides more opportunity for delving deeper into po- tential estimation methods, working with the public to iden- tify performance measures that work for both technical and nontechnical audiences, and perhaps even identifying and improving data sources than a three-month time frame. 1.4.3 Consider Possible Solutions Before measure selection and data collection begins, it is useful to reflect on the problem areas and consider possible solutions. Possible solutions include potential projects, oper- ational programs, and policies. Understanding the possible solutions will help ensure that key considerations are vetted and understood as measures and procedures are established in the next step. The following questions should be given ini- tial consideration at this stage and should be fully evaluated with prototype results of the analysis. • Can all the improvement types be accounted for with the typical measures? • Will the measures be able to illustrate the effect of the im- provements by mode? • Are there aspects of the projects, programs, or policies that will not be covered by the measures? • Are the measures understandable to all the potential audiences? • Are the uses of the measures appropriate, and will the procedures yield reliable information? 1.4.4 Develop a Set of Mobility and Reliability Measures Many analyses, especially multimodal alternatives or re- gional summaries, require more than one measure to de- scribe the problem. Analyses of corridor improvements might require travel time and speed measures to be expressed in person and freight movement terms. Some analyses are rel- atively simple, and it may be appropriate to use only one measure. Analyses of traffic signal timing, where carpool and bus treatments are not part of the improvement options, might not require person movement statistics—vehicle vol- ume and delay information may be sufficient. Poor selection of measures has a high probability of lead- ing to poor outcomes. In contrast, goals and objectives that are measured appropriately can guide transportation profes- sionals to the best project, program, or strategy; analysts and policy-makers can then check (using evaluation results) that the goals and objectives are best served by the solutions offered (3). 1.4.5 Develop Analysis Procedures While the set of mobility and reliability measures is deter- mined by what we want to know, the accompanying analysis procedures are determined by what data are available or can be obtained. As shown in Exhibit 1.1, identifying the analysis procedures is often done at about the same time as identify- ing the performance measures. Analysis procedures vary based upon several factors, including the use and/or audi- ences and how this affects the level of accuracy or precision required; budget and schedule; data formats; and data types. When continuous data sources are available, the estimation procedures typically comprise software programs that compute the performance measures from archived data. Alternatively, in the absence of continuous data, performance measures can be estimated by post-processing the output from transportation models (e.g., travel demand models, economic analysis models). All estimation methods include quality control and quality assurance of the input data, as well as reasonableness checks of the output. Analysis procedures can be expected to improve over time as the performance measurement program receives feedback from analysts and users of the results and as data collection and/or data elements improve. 1.4.6 Collect or Estimate Data Elements Data collection can proceed after an analysis of potential sources of information. The level of precision and statistical reliability must be consistent with the uses of the information and with the data collection sources. Estimates or modeling

9processes may be appropriate additions to traffic count, travel time, and speed data collection efforts. Statistical sampling procedures may be useful for wide area analyses, as well as for validating models and adapting them to local conditions. Direct data collection may be available from a variety of sources, including specific corridor studies, real-time data collection, and annual route surveys of travel times. An areawide travel monitoring program will consist of both travel speed data collection and estimated speed infor- mation obtained from equations or models. The directly collected data may be more expensive to obtain; statistical sampling techniques will decrease the cost and improve the reliability of the information. It may be possible to focus the data collection on a relatively small percentage of the road- way system responsible for a large percentage of the travel delay. Such a program would be supplemented with travel- time studies on a few sections of road and estimation procedures on the remainder of the system. 1.4.7 Identify Problem Areas The collected data and estimates can be used to develop measures that will illustrate the problem areas or situations. These should be compared to observations about the system to make a reasonableness check; the measures should identify well-known problem areas. The data will provide informa- tion about the relative size of the mobility and reliability problems so that an initial prioritization for treatment can be made. 1.4.8 Test Solutions Testing the potential solutions against the mobility and reliability measures during the data collection process may improve the data collection effort and the ultimate results. After data collection and estimation are complete, testing so- lutions for effect will be another chance to determine the need to modify mobility and reliability measures. Even after the analysis is complete, the measures should be evaluated before similar projects are performed. Inconsistencies or irregulari- ties in results are sometimes a signal that different procedures or data are required to generate the needed products. 1.4.9 Summary of Implementing Mobility and Reliability Measures The use of a set of mobility and reliability measures may mean more computer-based analyses, which might be per- ceived as a move away from direct measurement for some levels of analysis. This does not mean that travel-time data will be less useful or less cost-effective to collect. On the contrary, direct measurement of travel time can be used to not only quantify existing conditions, but also to calibrate wide-scale models of traffic and transportation system operation and to perform corridor and facility analyses. Incorporating the important process elements into a sequence of events leading up to a public discussion of alternative improvement plans might result in a series of steps like the following: • Existing traffic and route condition data are collected directly. • Measures are calculated. • Results are compared to target conditions determined from public comments during long-range plan discussion. • Trip patterns, areas, and modes that need improvement are identified. • Solutions are proposed. Areawide strategies should guide the selection of the type and magnitude of specific solutions. • A range of the amount and type of improvements is tested. • Mobility and reliability measures are estimated for each strategy or alternative, including forecasts of future values of measures as appropriate to the application. • Measures are compared to corridor, subarea, and regional goals. • Individual mode or facility improvements that fit with the areawide strategy are identified for possible inclusion in the plan, subject to financial analyses.

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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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