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Suggested Citation:"Report Contents." National Academies of Sciences, Engineering, and Medicine. 2014. Guide to Establishing Monitoring Programs for Travel Time Reliability. Washington, DC: The National Academies Press. doi: 10.17226/22614.
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Suggested Citation:"Report Contents." National Academies of Sciences, Engineering, and Medicine. 2014. Guide to Establishing Monitoring Programs for Travel Time Reliability. Washington, DC: The National Academies Press. doi: 10.17226/22614.
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Suggested Citation:"Report Contents." National Academies of Sciences, Engineering, and Medicine. 2014. Guide to Establishing Monitoring Programs for Travel Time Reliability. Washington, DC: The National Academies Press. doi: 10.17226/22614.
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Suggested Citation:"Report Contents." National Academies of Sciences, Engineering, and Medicine. 2014. Guide to Establishing Monitoring Programs for Travel Time Reliability. Washington, DC: The National Academies Press. doi: 10.17226/22614.
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Suggested Citation:"Report Contents." National Academies of Sciences, Engineering, and Medicine. 2014. Guide to Establishing Monitoring Programs for Travel Time Reliability. Washington, DC: The National Academies Press. doi: 10.17226/22614.
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Suggested Citation:"Report Contents." National Academies of Sciences, Engineering, and Medicine. 2014. Guide to Establishing Monitoring Programs for Travel Time Reliability. Washington, DC: The National Academies Press. doi: 10.17226/22614.
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Suggested Citation:"Report Contents." National Academies of Sciences, Engineering, and Medicine. 2014. Guide to Establishing Monitoring Programs for Travel Time Reliability. Washington, DC: The National Academies Press. doi: 10.17226/22614.
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Suggested Citation:"Report Contents." National Academies of Sciences, Engineering, and Medicine. 2014. Guide to Establishing Monitoring Programs for Travel Time Reliability. Washington, DC: The National Academies Press. doi: 10.17226/22614.
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Suggested Citation:"Report Contents." National Academies of Sciences, Engineering, and Medicine. 2014. Guide to Establishing Monitoring Programs for Travel Time Reliability. Washington, DC: The National Academies Press. doi: 10.17226/22614.
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Suggested Citation:"Report Contents." National Academies of Sciences, Engineering, and Medicine. 2014. Guide to Establishing Monitoring Programs for Travel Time Reliability. Washington, DC: The National Academies Press. doi: 10.17226/22614.
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Suggested Citation:"Report Contents." National Academies of Sciences, Engineering, and Medicine. 2014. Guide to Establishing Monitoring Programs for Travel Time Reliability. Washington, DC: The National Academies Press. doi: 10.17226/22614.
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Suggested Citation:"Report Contents." National Academies of Sciences, Engineering, and Medicine. 2014. Guide to Establishing Monitoring Programs for Travel Time Reliability. Washington, DC: The National Academies Press. doi: 10.17226/22614.
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Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

xiii 149 APPENDIX A Monitoring System Architecture 181 APPENDIX B Methodological Details 209 APPENDIX C Case Studies Case Study 1: San Diego, California Case Study 2: Northern Virginia Case Study 3: Sacramento–Lake Tahoe, California Case Study 4: Atlanta, Georgia Case Study 5: New York/New Jersey 499 APPENDIX D Use Case Analyses

1This guide describes how to develop and use a travel time reliability monitoring system (TTRMS). It explains why such a system is useful, how it helps agencies do a better job of managing network performance, and the actions a traffi c management center must take to establish a TTRMS. The Guide was prepared under Project L02 within the Strategic Highway Research Program 2 (SHRP 2) under the management of the Transportation Research Board. Travel time reliability is the absence of variability in travel times. If a system is reliable, people can get to where they want to go, when they want to be there, all the time. For example, if a freeway is reliable, then its travel times are the same for the same condition, all year long. It is similar to a vehicle that always starts when the key is turned on. Of course, in reality no system or roadway is perfectly reliable, and unex- pected events (e.g., incidents) sometimes signifi cantly reduce the reliability of a system. This executive summary describes the structure of the Guide; briefl y addresses the questions of the necessity, function, and structure of a TTRMS; and provides an illus- tration and overview of implementation. STRUCTURE OF THE GUIDE The Guide is organized into the following major parts: • The executive summary, which gives agency managers a description of a TTRMS explains why it is valuable and how it can be used. The summary is intended to prepare such individuals for the input they will receive from their staff and help them make informed decisions about future actions. EXECUTIVE SUMMARY

2GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY • A 5-chapter guide that describes the process of measuring, characterizing, identify- ing, and understanding the effects of recurrent congestion and nonrecurrent events that affect travel time reliability. • Four appendices that provide more detailed information on the functional speci- fications of a monitoring system, methodological details, a series of case studies, and a series of use cases (applications). Project L02 also has a separate final report that documents the research that led to the Guide. WHY IS A TRAVEL TIME RELIABILITY MONITORING SYSTEM NEEDED? Travel time reliability is effectively the absence of variation in travel times. The absence of reliability can be largely attributed to seven influencing factors that cause conges- tion and unreliable travel times (illustrated in Figure ES.1): • Incidents; • Weather; • Work zones; • Fluctuation in demand; • Special events; • Traffic control devices; and • Inadequate base capacity. Figure ES.1. The seven major sources (also called factors) of nonrecurrent congestion. Source: Strategic Highway Research Program 2.

3GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY System operators want to determine how to reduce variability and enhance reli- ability; system users want to avoid variability. When making trips, system users want to select routes with reliable travel times, and they want to leave at the right moment so they can arrive on time or minimize the probability of being late. A TTRMS should be created because it provides features and capabilities that most transportation management centers (TMCs) lack. A TTRMS can help operating agencies monitor the performance of their system, understand the impacts of the vari- ous influencing factors, provide credible information to system users about what travel time reliability to expect, and decide what actions to take to help improve reliability. Creating a TTRMS involves creating a new module that plugs into an existing TMC platform. The TTRMS relies on the TMC to gather sensor data, manage data processing and storage, and communicate the results of its findings to the outside world. The TTRMS focuses on using the incoming sensor data, along with supplemen- tal information about the influencing factors, to create a credible picture of how well the system is performing at the present time and how well it performed in the past. The payoff is better reliability. The TTRMS will ensure that the TMC team knows how reliability will suffer if certain events take place. It will let them understand the impacts of weather, incidents, and special events. It will also help the TMC team man- age the network’s reliability in real time by providing up-to-date information about how the variability in segment and route travel times is either increasing or decreasing in response to actions taken. WHAT SHOULD A TRAVEL TIME RELIABILITY MONITORING SYSTEM DO? Figure ES.2 shows the four key information flow steps a TTRMS must execute to fulfill its purpose as a decision support tool. First, the TTRMS needs to effectively measure travel times. This is a complex technical topic due to the variability of traveler behavior and the plethora of different measurement sensors. Correctly measuring travel times along a given route requires a great deal of systems development effort and statistical knowledge. This guide serves as a primer on how to measure travel times using available technologies and statistical techniques. Measuring an individual travel time is the foundational unit of analysis for reliability monitoring. Second, the TTRMS needs to clearly characterize the reliability of a given system. This process entails taking a set of measured travel times and assembling them into a statistical model of the behavior of a given segment or route. The statistical paradigm outlined in this guide uses probability density functions and cumulative density func- tions (CDFs) to characterize the performance of a given segment or route, usually specific to a particular operating regime (a combination of congestion level and non- recurring event). This guide gives specific advice on the statistical decisions required to effectively characterize the travel times. Characterizing the reliability of a segment or route is fundamental to making good decisions about how to improve the performance of that segment or route.

4GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY Third, the TTRMS needs to identify the sources of unreliability. Once the reli- ability of a segment or route has been characterized, transportation managers need to understand what caused the unreliability (and how to improve it). This guide follows the causal list used by the Federal Highway Administration (FHWA) to describe why congestion arises and breaks these sources into the seven major influencing factors listed above. It discusses how to pull in data for these influencing factors and effec- tively fuse them with travel time data. Identifying the travel times affected by these sources of congestion is required preparation for understanding system reliability. Finally, the TTRMS needs to help operators understand the impact of these sources of unreliability on the system. This final step in turning raw data into actionable deci- sions requires both quantitative and qualitative methodologies: operators need clear visualizations of data, as well as quantifications. This dual approach supports both data discovery and final decision making about a given route. Understanding reliabil- ity is the key to good decision making about improving system reliability. Once in place, a TTRMS that accurately and consistently executes these four steps becomes a powerful tool for traffic management. It is a tool that decision makers can use to understand how much of their delay is due to unreliability, and how to mitigate that delay. For example, should a freeway operator deploy more service patrol vehicles (to clear incidents more quickly) or focus efforts on coordinating special-event traffic (to reduce delay from stadium access)? A reliability monitoring system, as outlined in Figure ES.2. Information flow in a TTRMS. Low High Computation Engine

5GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY this guide, can tell an operator which of these activities is worth the investment and what the payoff will look like. Building this system will add a new, powerful, practical traffic management tool to the arsenal of system operators. HOW SHOULD A TRAVEL TIME RELIABILITY MONITORING SYSTEM BE STRUCTURED? The process described above is designed to be integrated within an existing traffic management system with a structure like that generalized in Figure ES.3. Inside the large box in Figure ES.3 are the three major modules of a TTRMS: a data manager, a computation engine, and a report generator. The data manager assembles incoming information from traffic sensors and other systems, such as weather data feeds and incident reporting systems, and places them in a database that is ready for analysis as “cleaned data.” The computation engine works with the cleaned data to prepare indications of the system’s reliability: when it is reliable, when it is not, to what ex- tent, under what conditions, and so forth. In the figure this is illustrated by “regime TT-PDFs,” or travel time probability density functions organized by regimes. Regimes consist of the congestion level and the type of nonrecurring event (including none), such as high congestion and an incident or low congestion and work zone activity. The report generator responds to inquiries from users (system managers or travelers) and uses the computation engine to analyze the data and provide information that can then be presented to the inquirer or decision maker. Each of these modules is discussed and described in the Guide. In addition, case studies and use cases illustrate how these modules work together to produce answers to questions that managers would likely pose. The appendices provide further details about how each of the modules should work, together and separately. Figure ES.3. Reliability monitoring system overview, with boxes for modules and circles for inputs and outputs.

6GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY AN ILLUSTRATION Figure ES.4 shows the travel times for a specific trip on a freeway (I-5 in San Diego, California) throughout a typical weekday, excluding any nonrecurrent events such as incidents, weather, unusual demand, or special events. Time of day is shown along the x-axis, and the travel time in minutes is shown on the y-axis. It is clear from Figure ES.4 that the travel times on this roadway segment are not always the same; the system is unreliable, even without the influence of incidents and weather. Not only does the travel time vary but also the spread in the times varies, slightly during the a.m. peak but dramatically during the p.m. peak. At about mid- night, the minimum and maximum are only 5 minutes different (50 versus 55 minutes), but they differ by 50 minutes during the weekday p.m. peak without the additional influence of nonrecurring events (50 versus 100 minutes). This is the effect of recurring congestion. Figure ES.5 shows the same travel times, now with nonrecurrent events included. It is clear that nonrecurring events have an impact, with the spread between minimum and maximum times widening. Adverse weather is a good example of the effect a non- recurrent event can have, especially during the peak period. Traffic incidents also have an effect on travel time reliability, as do special events and unusually high demand. The TTRMS helps indicate when, why, and by how much travel time will vary. Figure ES.6 shows an example from a different data source (I-8 westbound in San Diego) of what to expect as an output from a TTRMS. The figure shows plots with the distribution of travel rates (seconds per mile) across a 3-month period under two iden- tified operating conditions (uncongested and high recurrent congestion) and whether an incident is present. The distributions for this example are shown cumulatively (as a CDF); the location of each line shows how many travel rates are that value or shorter. For example, when traffic incidents occur during heavy (recurrent) congestion, one- half (50%) of the travel rates are up to 65 s/mi. That is, 50% of the travel rates are either this long or shorter (smaller). The 90th percentile travel rate is 100 s/mi. Or put another way, nine of every 10 vehicles is traveling at that rate or faster. The value comes from comparing one distribution with another. For example, analysts can compare the distribution for high recurrent congestion with traffic inci- dents with high recurrent congestion without incidents. Without incidents, 50% of the vehicles are traveling at approximately 55 s/mi instead of 65 s/mi—considerably faster. At the 90th percentile, the traveling difference is even more dramatic, being approxi- mately 60 s/mi versus 100 s/mi. The cumulative density functions presented as an output of the TTRMS are the technical means by which many useful outcomes can be reached. Some examples include the following: • Understanding the system. The TTRMS shows that the impact of incidents on travel rates is dramatic, particularly during periods when the facility is already congested due to normal traffic conditions (e.g., peak hour travel). This knowledge allows an agency to prioritize funding toward measuring and responding to the types of nonrecurrent events that most significantly affect that agency’s system.

7GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY Figure ES.4. Illustration of variation in travel times by time of day across a year with nonrecurrent events excluded. Figure ES.5. Variation in travel times by time of day across a year with nonrecurrent events included. 0 20 40 60 80 100 120 0:00 6:00 12:00 18:00 0:00 Tr av el T im e (m in ) Time of Day (hr:min) 0 20 40 60 80 100 120 140 160 180 0:00 6:00 12:00 18:00 0:00 Tr av el T im e (m in ) Time of Day (hr:min) No Events Incidents Demand Special Events Weather

8GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY • Communicating to the public. The TTRMS can be used to communicate travel times or ranges of travel times to the traveling public and to passenger and freight movers, both pretrip and en route. This allows the public to be informed and a partner in managing the demand on the system. • Measuring the effects of actions. The TTRMS can be used to measure the effect of actions taken to improve reliability. The mitigating actions would be intended to cause the travel times (or travel rates) during incidents to get closer to those when there are no incidents. Moreover, after the mitigating actions are taken, the TTRMS would be able to show how reliability improved. The Guide contains many examples of potential applications of the use of a TTRMS through a series of use cases. The use cases are organized around the various stakeholders who use or manage aspects of the surface transportation system, includ- ing the following: • Policy and planning support. Agency administrators and planners who have re- sponsibility for and make capital investment decisions about the highway network; • Overall highway system. Operators of the roadway system (supply), including its freeways, arterials, collectors, and local streets; and drivers of private autos, trucks, and transit vehicles (demand); • Transit subsystem. Operators of transit systems that operate on the highway net- work, primarily buses and light rail (supply) and riders (demand); and Figure ES.6. How travel rates are affected by congestion and nonrecurring incidents. 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 40 60 80 100 120 140 Cu m ul at iv e Pr ob ab ili ty Travel Rate (sec/mi) Normal Conditions, Uncongested Normal Conditions, High Congestion Incident Conditions, Uncongested Incident Conditions, High Congestion

9GUIDE TO ESTABLISHING MONITORING PROGRAMS FOR TRAVEL TIME RELIABILITY • Freight subsystem. Freight service suppliers (supply) and shippers and receivers that make use of those services (demand). IMPLEMENTATION Much of the work of developing a TTRMS can be carried out by a team that includes people with expertise in database management, statistics, traffic detection technology, and traffic engineering. Executive-level guidance to the implementation team should answer the following questions: • What is the desired geographical scope of the system? • Are periodic reports (weekly, monthly, quarterly, or annual) sufficient or does the system need to be providing continuous real-time reporting capabilities? • Is the reliability information primarily for the agency’s internal use or is the intent to provide information to the public in a way that will influence travel decisions? • How much detail is required? Is it sufficient to have a generalized comparison of reliability on different routes or is it desirable to know about the reliability of in- dividual trips on a specific highway segment? CONCLUSION A TTRMS will help an agency understand the reliability performance of their systems and monitor how reliability improves over time. It will help an agency answer a variety of key questions, including the following: • What is the extent of congestion within the system (in space and time)? • What is the effect of nonrecurring events (i.e., the seven sources of unreliability) on the operation of the system? • How are freeways and arterials performing relative to performance targets set by the agency? • Are capacity investments and other improvements necessary given the current dis- tribution of travel times? • Are operational improvement actions and capacity investments improving the travel times and their reliability?

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TRB’s second Strategic Highway Research Program (SHRP 2) Report S2-L02-RR-2: Guide to Establishing Monitoring Programs for Travel Time Reliability describes how to develop and use a Travel Time Reliability Monitoring System (TTRMS).

The guide also explains why such a system is useful, how it helps agencies do a better job of managing network performance, and what a traffic management center (TMC) team needs to do to put a TTRMS in place.

SHRP 2 Reliability Project L02 has also released Establishing Monitoring Programs for Travel Time Reliability, that describes what reliability is and how it can be measured and analyzed, and Handbook for Communicating Travel Time Reliability Through Graphics and Tables, offers ideas on how to communicate reliability information in graphical and tabular form.

A related paper in TRB’s Transportation Research Record, “Synthesizing Route Travel Time Distributions from Segment Travel Time Distributions,” examines a way to synthesize route travel time probability density functions (PDFs) on the basis of segment-level PDFs in Sacramento, California.

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