Analytical Procedures for Determining the Impacts of Reliability Mitigation Strategies (2012)

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14 C h a p t e r 1 The fundamental objective of this project was to develop predictive relationships between highway improvements and travel time reliability. In other words, how can the effect of an improvement on reliability be predicted? Alter- natively, how can reliability be characterized as a func- tion of highway, traffic, and operating conditions? A variety of challenging issues were confronted in addressing this objective. Significance of travel time reliability on transportation System performance Reliability is important to travelers and transportation prac- titioners for a variety of reasons: • From an economic perspective, reliability is highly impor- tant because travelers must either build in extra time to their trips to avoid arriving late or suffer the consequences of being late. This extra time has value beyond the average travel time used in traditional economic analyses. Recent work has documented that reliability has value to travelers and influences their behavior (1, 2); • Because of the extra time required in planning trips and the uncertainty about how much time will be required for a trip, reliability influences decisions about where, when, and how travel is made; and • Transportation planners and operators need to include the extra economic cost of unreliable travel to users in project planning, programming, and selection processes. This is particularly true of strategies that deal directly with road- way events (e.g., incidents). In the past, most assessments of these types of strategies have missed this important aspect of travel. New Concept of travel time reliability Although use of travel time–based performance measures in planning and operations applications has taken on greater significance in the past few years, travel time reliability—how consistent (or variable) travel conditions are from day to day— is a relatively new concept to which much of the transporta- tion profession has had only limited exposure. Congestion has been growing nationwide, and planners increasingly have become involved in short-term activities such as performance monitoring, as well as operations and management strategies. These activities have been elevated in importance by trans- portation agencies in order to be responsive to the demands of the public and state legislatures. Anecdotal reports and technical studies indicate that average congestion levels have grown, and continue to grow, in our cities. In a 2005 report, Travel Time Index (TTI) researchers found that congestion levels in 85 of the largest metropolitan areas have grown in almost every year from 1982 to 2003 for all population groups (3). Recently, anecdotal reports and empirical information have suggested that congestion levels have eased; TTI researchers noted in the 2007 Urban Mobility Report that Congestion, by every measure, has increased substantially over the 25 years covered in this report. The most recent two years of the report, however, have seen slower growth or even a decline in congestion. Delay per traveler—the number of hours of extra travel time that commuters spend during rush hours—was 1.3 hours lower in 2007 than 2005. This change would be more hopeful if it was associated with something other than rising fuel prices (which occurred for a short time in 2005 and 2006 before the sustained increase in 2007 and 2008) and a slowing economy. This same kind of slow growth/ decline over a few years occurred in the early 1990s when spending and growth in the high-tech and defense sectors of Introduction

15 the economy declined dramatically. The decline means con- gestion is near the levels recorded in 2003, not exactly a year remembered for trouble-free commuting. (4) However, talking about typical or average conditions in a transportation system that experiences wide fluctuations in performance tells only part of the story. Travel time reliability has taken on increasing importance. Variation in travel times now is understood as a separate component of the public’s and business sector’s frustration with congestion problems. Reliability is a major part of system performance and of trav- elers’ perceptions of performance. Although reliability has not been widely used to describe performance, agencies are increasingly recognizing its value in assessing their own per- formance and in communicating performance to the public. Defining travel time reliability In terms of highway travel, the Reliability Research Program of the Future Strategic Highway Research Program (F-SHRP) defined highway travel time variability as synonymous with reliability: . . . from a practical standpoint, travel-time reliability can be defined in terms of how travel times vary over time (e.g., hour- to-hour, day-to-day). This concept of variability can be extended to any other travel-time-based metrics such as average speeds and delay. For the purpose of this study, travel-time variability and reliability are used interchangeably. (5) A slightly different view of reliability is based on the notion of a probability or the occurrence of failure often used to character- ize industrial processes. With this view, it is necessary to define failure in terms of travel times; in other words, a threshold must be established, and the number of times the threshold is not achieved or exceeded can be counted. These types of measures are similar to on-time performance, since performance is mea- sured relative to a preestablished threshold. The only differ- ence is that failure is defined in terms of how many times the travel time threshold is exceeded, but on-time performance measures how many times the threshold is not exceeded. The authors of NCHRP Project 3-68 note that the defini- tions for variability and failure have an underlying theme: they both imply that a history or distribution of travel times exists (6). The history over which travel times are measured must be sufficiently long to capture the variations that result from the random and planned events on the roadway system. Once this distribution is established, any number of measures can be constructed to describe its size and shape. The pres- ence of a distribution of travel times leads to a more general definition of travel time reliability as the level of consistency in travel conditions over time. Travel time reliability is measured by describing the distribution of travel times that occur over a substantial period of time. In recent years, some non-U.S. reliability research has focused on another aspect of reliability—the probability of failure, in which failure is defined in terms of traffic flow breakdown. A corollary concept, vulnerability, is a measure of how vulnerable a network is to breakdown conditions. This measure can be applied at the link or network level (7). Understanding travel time reliability To understand travel time reliability, it is essential to under- stand the factors that cause travel times to be unreliable. Pre- vious work indicates that reliability is determined by the variability in conditions that travelers encounter from day to day. Reliability metrics show that variability exists in the sys- tem, but they do not tell what causes it. The original F-SHRP Reliability Research Plan identified seven sources of conges- tion as the factors that cause travel times to be unreliable and contribute to total congestion: incidents, inclement weather, work zones, special events, traffic control device timing, demand fluctuations, and inadequate base capacity. These categories were developed to avoid the recurring–nonrecurring nomen- clature that has been in wide use but is not detailed enough for the purpose of SHRP 2 research. Operational Strategies and Capacity expansion Both operational strategies and capacity expansion projects were postulated to affect reliability, and both were studied in the research. Many operational strategies are aimed specifi- cally at the factors that cause unreliable travel (e.g., incident management, work zone management). Note, however, that one of the seven sources of congestion affecting reliability is inadequate base capacity. The effect of physical capacity on congestion is well established and has been the focus of ana- lytic procedures for the past several decades (e.g., the Highway Capacity Manual). Physical capacity also affects reliability because it interacts with all the other sources of congestion. For example, consider an incident that blocks one lane of traf- fic. Its effect is much greater if there are only two lanes avail- able than if three or more were available. So, adding physical capacity definitely will have an effect on reliability. travel time Measurements Travel time measurements are critical to any definition of reli- ability and reliability metrics. Travel time is the starting point for sound congestion measurement because it reflects the

16 actual experience of system users. When measured directly, it also is independent of theoretical capacity concerns, such as what happens in oversaturated conditions. Once travel time is obtained, a whole family of additional measures can be created using other basic information about the system (e.g., volume, free-flow speed). Delay is one example of a metric that natu- rally derives from travel time measurements. references 1. Joint Transport Research Centre. Improving Reliability on Surface Transport Networks: Summary Document. International Transport Forum, Organisation for Economic Co-operation, Paris, 2009. www.internationaltransportforum.org/jtrc/infrastructure/networks/ ReliabilitySum.pdf. 2. Fosgerau, M., and A. Karlström. The Value of Reliability. Transporta- tion Research Part B, Vol. 44, No. 1, 2010, pp. 38–49. 3. Schrank, D., and T. Lomax. The 2005 Urban Mobility Report. Texas Transportation Institute, Texas A&M University, College Station, 2005. http://d3koy9tzykv199.cloudfront.net/static/ums/mobility_ report_2005_wappx.pdf. Accessed May 8, 2012. 4. Schrank, D., and T. Lomax. The 2007 Urban Mobility Report. Texas Transportation Institute, Texas A&M University, College Station, 2007. http://d3koy9tzykv199.cloudfront.net/static/ums/mobility_ report_2007_wappx.pdf. Accessed May 8, 2012. 5. Cambridge Systematics, Inc., Texas Transportation Institute, Univer- sity of Washington, and Dowling Associates. Providing a Highway System with Reliable Travel Times: Study 3—Reliability. Final report, NCHRP Project 20-58(3). Transportation Research Board of the National Academies, Washington, D.C., 2003. http://trb.org/ publications/f-shrp/f-shrp_webdoc_3.pdf. 6. Cambridge Systematics, Inc., Texas Transportation Institute, Univer- sity of Washington, and Dowling Associates. Guide to Effective Free- way Performance Measurement: Final Report and Guidebook. NCHRP Web-Only Document No. 97. Transportation Research Board of the National Academies, Washington, D.C., 2006. http://onlinepubs.trb .org/onlinepubs/nchrp/nchrp_w97.pdf. 7. Watling, D., A. Sumalee, R. Connors, and C. Balijepalli. Advancing Methods for Evaluating Network Reliability. Institute for Transport Studies, University of Leeds, United Kingdom, 2004.