Incorporating Reliability Performance Measures into the Transportation Planning and Programming Processes (2013)

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28 C h a p t e r 3 Incorporating reliability performance measures into the transportation planning and programming process requires an understanding of the state of the practice to ensure that the guidance will be useful to the transportation agencies and practitioners who will be responsible for the integration. A state of the practice survey was conducted in October and November 2010 to gather information about the identifica- tion of travel time reliability as an issue, the collection of travel time data, the calculation of reliability performance measures, and the challenges and issues agencies face in this area. This chapter describes the approach to the survey and findings. This information will be used both to help shape the material being developed for the guide and to identify poten- tial candidates for the validation case studies to be conducted in Phase 2 of this research. approach The research team developed a short on-line survey to iden- tify the depth of knowledge and level of sophistication of travel time reliability; performance measures; travel time data collection and availability; reliability valuation; use of reli- ability in planning and programming; institutional relation- ships; and staff capacity. The survey instrument is provided in Appendix A. The survey was distributed to DOTs and MPOs through all available channels. For state DOTs, the survey was distributed through the American Association of State Highway and Transportation Officials (AASHTO) Standing Committee on Planning (SCOP), Standing Committee on Performance Management (SCOPM), and Subcommittee on System Oper- ations and Management (SSOM). For MPOs, the survey was distributed through research team contacts with individual MPOs and MPO organizations in several states. The survey responses were reviewed and cleaned to ensure that there were no duplicate responses. Some DOTs and MPOs did provide multiple responses, typically from different divisions, and these responses were usually retained. In cases in which one respondent from an agency appeared to have more information, this information was used. For example, one respondent from an agency might have answered “I don’t know” to a question that another respondent from the same agency answered with more specific information. The data were identified by agency so that various com- parisons could be made about the data, including area popu- lation, geographic location, and others. For the purposes of the findings presented, large agencies include states with more than five million people or regions with more than one million people. Small agencies are states with fewer than five million and regions with fewer than one million. Findings Response Rate There is significant interest in travel time reliability among transportation agencies. There were 92 responses were received, with responses from 29 state DOTs and 39 MPOs. In several cases, multiple responses were received from the same agency. Note that the findings only include names of agencies that gave explicit approval to use their information; all other agencies are included in aggregate. There are 50 states and 384 MPOs in the United States. Figure 3.1 presents the response rate by size of agency. Larger states and MPOs were more likely to respond to the survey, although states of all sizes responded. MPO responses were much more heavily concentrated among the agencies repre- senting relatively large populations. Because the challenge of reliability is likely to impact larger urban areas more signifi- cantly than medium and small areas, it is useful to have a high response rate (50%) of these larger agencies. Figure 3.2 presents the geographic distribution of responses across five regions of the United States. For state DOTs, a reasonable response rate was achieved from each region (at least 40% of states in each region responded to the State of the Practice

29 survey) and 75% of midwestern and southwestern states responded. For MPOs, a roughly equal number of responses were received from each region, but percentages are lower for the Southeast (5%) and Midwest (8%) and higher for the Southwest (22%). This may be in part because of the larger number of single county MPOs in states like Florida; only 7% of MPOs in the Southeast region are over one million in population. Key Findings Definition of Travel Time Reliability Of the organizations surveyed, 25% have developed an estab- lished definition of travel time reliability. Large agencies are far more likely to have developed a formal definition (35%) than small agencies (7%). MPOs and DOTs have established definitions at approximately the same rate. Figure 3.2. Number of survey respondents by agency type and geography. 0 20 40 60 80 100 120 140 Northeast Southeast Midwest Southwest West Northeast Southeast Midwest Southwest West State MPO Number of Agencies Total agencies Survey Responses Figure 3.1. Number of survey respondents by agency type and size. 0 50 100 150 200 250 Large (>10 M) Medium (5-10 M) Small Large (> 1 M) Medium (200,000-1 M) Small (< 200,000) State Number of Agencies Total agencies Survey Responses (< 5 M) MPO

30 Tracking Reliability Performance Measures Many of the agencies that responded to the survey indicated that they are using performance measures, but only about 25% reported performance measures for tracking travel time reliability. Figure 3.3 presents the number of DOTs and MPOs that are tracking travel time reliability and other performance measures. Nearly all of the MPOs track mobility measures and over half track preservation and safety measures. About two-thirds of states track each of these measures. Among agencies that do not track travel time reliability, 40% plan to begin within the next 3 years, while the remain- ing respondents were not sure or do not plan to do so within the next three years. Large agencies are far more likely to track reliability measures (33%) than small agencies (10%). Among agencies that report tracking travel time reliability, roughly equal numbers track the 95th or 90th percentile travel times (eight respondents), the planning-time index (seven respondents), and the buffer index (six respondents). Notably, many of these respondents (5) indicated that they track two or three of these measures, and one respon- dent noted tracking additional points of the travel time distribution (i.e., 50th and 80th percentiles in addition to 90th and 95th). Data Collection Most agencies collect travel time data and do so mostly on urban freeways. Nearly all large agencies collect some form of travel time data (over 90%), while just under two-thirds of small agencies collect any travel time data. Loop detectors are the most common way to collect travel time data, with DOTs much more likely to indicate that they use detectors than MPOs. Because DOTs typically own these detectors, MPO responses to this question may indicate DOT data to which they have access. MPOs are most likely to use floating car runs to validate their models. Fewer agencies use intelligent trans- portation system (ITS) detectors (such as loops, radar, or video imaging) and purchased private travel time data (e.g., INRIX, Traffic.com, or Trafficast). Figure 3.4 summarizes the data col- lection methods used by respondents to the survey. Among agencies that collect travel time data, most collect data on most or all of their urban freeway segments, and all agencies collect travel time data on some of their urban free- way segments (Figure 3.5). DOTs commonly collect data on rural freeway segments, but very few agencies collect data for urban arterials. Only a few MPOs collect data for rural arterials, collector, or local streets. Among agencies that collect travel time data, more than half of the agencies use operations data from traffic management centers to support planning efforts. While about two-thirds of DOTs make use of the TMC opera- tions data, fewer than half of the MPOs do. Monetization of Reliability Relatively few agencies (fewer than 25%) responded that they monetize reliable travel time differently than average travel time. Respondents who said they monetized reliable travel time were asked for a value. The responses to this question generally indicated that agencies are only monetizing reliable travel time. Only one respondent provided an actual value (1.3 times the average value of travel time), and the respondent indicated that the agency only used it for occasional purposes, not on an ongoing basis. Figure 3.3. Performance measures reported by DOTs and MPOs. 0 5 10 15 20 25 30 35 40 Travel time reliability Other mobility or congestion measures Preservation and maintenance Safety and security Other Number of Agencies DOTs MPOs

31 Use of Reliability in Planning For recently completed or upcoming planning studies, survey respondents were asked if reliability was incorporated in the planning process. For a range of planning efforts, respondents were asked if they “include reliability as a goal or address as an issue,” “identify reliability deficiencies or needs,” and/or “use reliability results to help evaluate or prioritize projects.” Findings by level of integration include the following: • Goal/issue. Agencies commonly appear to identify reliability as a goal, with 54% of agencies identifying a reliability-related goal for at least one planning effort. More do so for long- range plans and CMPs (22 and 19 agencies, respectively) and somewhat fewer for State Transportation Improvement Programs (STIPs) and Transportation Improvement Pro- grams (TIPs), corridor plans, operation planning, and project plans (10 to 12 agencies). • Needs and deficiencies. Just under half of agencies respond- ing to the survey examine reliability needs and deficiencies in one or more planning product. These are identified most commonly within CMPs (19 agencies), which is not sur- prising, considering the intended role for CMPs in address- ing these issues. Agencies claim to address reliability needs somewhat less frequently in long-range planning and oper- ations plans (12 agencies) and project plans (15 agencies). Only 9 address reliability needs in a STIP/TIP and 12 in a corridor or area plan. 50 10 15 20 25 30 Loop detectors ITS detectors Probe data/ floating car Purchased data Number of Agencies MPO DOT Figure 3.4. Data collection methods by agency type. 0 5 10 15 20 Urban freeway segments Rural freeway segments Urban arterials Rural arterials Urban or rural collector or local streets Entire trips from origin to destination Number of Agencies Most or all Some Few or none Figure 3.5. Travel time data collection by facility type.

32 • Project prioritization. Agencies report using reliability to support project prioritization least frequently (38% across all planning products). This was least common in long-range plans and corridor/area plans (8 and 7 agencies, respectively) and most common in operations planning and project plans (12 and 11 agencies, respectively). Figure 3.6 indicates agency uses of reliability in the planning process. Agencies identified several challenges to incorporating reli- ability into planning and programming, including lack of data, newness of the subject material, or lack of staff (Figure 3.7). More than 60% of agencies saw lack of data availability as a challenge; more than 50% of agencies said that the newness of the subject is a challenge; and nearly 45% of responding agencies indicated they do not have enough staff (note that this is a bigger issue among small agencies). About one-third of agencies said that there is “no clear way to link reliability with planning and programming process.” Lack of skills in current staff and coordination with other organizations were less frequently mentioned as challenges by survey respondents. Respondents also listed a number of additional challenges, including the following: • Lack of internal coordination; • Data quality and managing large volumes of available data; • Inability to predict future travel time reliability; • Highway focus of reliability; and • Cost to address reliability, including any impact on other initiatives. Include as goal Identify deficiencies Use to prioritize projects 0 5 10 15 20 25 Long-Range Transportation Plan Transportation Improvement Program (TIP/STIP) Congestion Management Process (CMP) update Corridor or area plan(s) Operations Planning Project plans for major capacity improvements Number of Agencies Figure 3.6. Agency uses of reliability in the planning process. 0% 10% 20% 30% 40% 50% 60% 70% Data availability New subject area More staff Method to integrate reliability Skills of staff Coordination - transportation Coordination - other Other Figure 3.7. Challenges to incorporating reliability in planning and programming.

33 Coordination Coordination with other agencies on transportation system operations or reliability issues is most common through ongoing committee and stakeholder outreach with transpor- tation planning and operations staff at DOTs and MPOs. Respondents noted that transit agencies are commonly involved, nearly equally through stakeholder outreach, on - going committees, or planning study committees. Public safety and emergency response agencies are most commonly involved in addressing reliability or operations issues through stake- holder outreach and, in many cases, they participate in an ongoing committee. Toll authorities, towing companies, and shippers or freight carriers are less commonly involved, and when they are, it is through stakeholder outreach. It is not common among responding agencies to have staff colocated at a traffic management center. Figure 3.8 identifies the pri- mary methods of coordination identified by respondents for various stakeholder groups. Upcoming Planning Efforts Finally, respondents were asked about upcoming planning efforts to help identify where potential opportunities exist to perform validation case studies. Most agencies will be working on planning products in the coming year. Of the 68 respond- ing agencies, 39 will be producing a Long-Range Transporta- tion Plan (LRTP) in the next year, and 45 will be working on their Transportation Improvement Program (TIP). Forty agencies plan to conduct corridor or area plans; 31 agencies will update their congestion management process (CMP); 26 agencies will conduct major capacity improvements plans; and 27 will conduct operations planning. Information on upcoming planning efforts has been integrated into the case study selection effort described in Chapter 4. Summary The state of the practice survey provides a useful examination of where agencies stand in terms of their efforts to address and to measure travel time reliability, the data they need to measure, and the efforts they are making to integrate reliabil- ity as an issue within the transportation planning and pro- gramming process. By examining all of the responses together, a general continuum of sophistication in reliability measure- ment and application can be ascertained. The components of this continuum include the following: • Leaders and innovators. Five DOTs and seven MPOs have established a definition of reliability and are currently tracking travel time reliability performance measures. Most of these are agencies with large populations in their juris- dictions, including DOTs from Florida, New York, and Wisconsin, and MPOs from Seattle, Washington, and Philadelphia, Pennsylvania. Note that throughout the sum- mary, examples of agencies that have indicated an interest in participating in the study effort are given. Many responses to the survey were given anonymously. Some of these agen- cies are in relatively lower population jurisdictions, such as the MPO in Gary, Indiana. 0 5 10 15 20 25 30 35 40 45 50 Transportation operations Transportation planning Transit Toll authorities Public safety/ emergency response Towing companies Shippers/ carriers Number of Agencies Co-locate staff Ongoing committee Study committee Stakeholder outreach Figure 3.8. Coordination around reliability by stakeholder group.

34 • Unrealized opportunities. Six large DOTs and 13 large MPOs are likely to have reliability problems (by virtue of population size). They track other performance measures and collect travel time data but do not track travel time reli- ability performance measures. This group includes DOTs in Colorado, Maryland, and Texas, and MPOs in Atlanta, Georgia; Detroit, Michigan; Dallas-Fort Worth, Texas; Pittsburgh, Pennsylvania; and Tucson, Arizona, among others. • Planning ahead. Seven small DOTs and six small MPOs that are less likely to have ongoing reliability problems do track other performance measures and do collect travel time data but do not track travel time reliability perfor- mance measures. This group includes DOTs in Idaho and Iowa, as well as the Lake Tahoe, California MPO. • In need of a reliability primer. A small number of larger agencies claim to not collect travel time data (though it is possible that respondents are simply not aware of what other parts of the agency are doing). Eleven smaller agen- cies also said they do not collect travel time data. The information from the survey was an important input into the development of the guide. The survey helped iden- tify which challenges the research team should focus on and what information holds interest for the primary audience. The survey makes clear that the audience for the guide has varying levels of sophistication and ability to take on the measurement and use of reliability within their planning processes. The methods in the guide will speak to these vari- ous audiences. Conclusions and Lessons Learned The case study resulted in the following conclusions and lessons learned for MPOs in updating their CMP: • In a survey of 20 MPOs representing most of the major met- ropolitan areas in the United States, only five are accounting for travel time reliability in some significant way in their transportation plans. Several of the larger metropolitan area MPOs (including Metro in Los Angeles County, Central Transportation Planning Staff [CTPS] in Boston, Chicago Metropolitan Agency for Planning [CMAP] in Chicago, Puget Sound Regional Council [PSRC] in Seattle) mention reliability only in the context of transit planning or freight movement. • Those agencies that do not use reliability measures all agreed that it would be “nice” or “wish they could do it,” but resource limitations prevented them from doing so. These resource limitations include lack of sufficiently high- quality data and inadequate technical expertise. • Calculating reliability performance measures requires robust amounts and sources of traffic data. Alternative data sources such as integrated corridor management (ICM) simulation modeling, regional 5-1-1 systems, and private sector data sources should be considered when developing data collection plans for reliability. • Corridor-level reliability measures are recommended based on MWCOG experience. • Effective report graphics are essential for presentation of the indices. • No significant resistance to adopting and incorporating reliability measures into the CMP was encountered at the MPO Policy Board, stakeholder, or public involvement level at the five agencies. However, MPOs should consider developing explanations of travel time reliability indices that can be easily understood by multiple audiences. • None of the five agencies using reliability exhibited signifi- cant differences in adoption and usage of the measures, regardless of the number of jurisdictions or institutional history or structure. This could bode well for MPOs with multiple jurisdictions or other factors that can complicate regional planning efforts. • A performance measurement working group should be created with membership consisting of agency staff, tech- nical and policy board members, local stakeholders, and the public. This will serve MPOs in CMP development and other initiatives. • As a result of this case study, NCTCOG is already making efforts to acquire and incorporate additional sources of traffic data for use in their planning processes. This includes US-75 ICM data and continuous travel time data received as part of its regional 5-1-1 project. In conducting their CMP update, NCTCOG plans to report on reliability at the corridor level. NCTCOG staff members will focus on reporting reliability on highways for the current update and then work toward adding major arterials in the next update. The approach will allow them to set realistic goals for the first update, using the additional data and incorpo- rating reliability measures. Once experience is gained using these resources and analysis approach, they will strengthen their planning techniques even further.