Pilot Testing of SHRP 2 Reliability Data and Analytical Products: Southern California (2014)

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• Test recently programmed or planned projects and potential operational strategies; and • Present results to SCAG policy and technical committees and to Caltrans District 12 management. These steps allowed the study team to test multiple reliability products from five separate SHRP 2 projects (Table ES.1). Table ES.1. SHRP 2 Reliability Products Tested in the Southern California Pilot Site Type of Product L02 L05 L07 L08 C11 Methods for Describing Reliability and Contributing Factors  Suggested Alternative Strategies and Design Features   Tools for Forecasting Reliability and Estimating Impacts    Benefit Estimates for Benefit-Cost Analysis   Guidelines for Goal Setting  Test Facilities With the consultation of SCAG and Caltrans, the study team selected two test facilities. The first is the I-5 in Orange County, a 45-mile, heavily congested interstate highway with four to six general-purpose lanes in each direction. There are also multiple barrier-separated high- occupancy vehicle and auxiliary lanes throughout the I-5 corridor. This complex geometry led to some difficulties in calibrating the SHRP 2 products, especially the FREEVAL-RL model from the L08 product. The second facility is also heavily congested. The 16-mile, urban segment of I-210 in Los Angeles County has the worst reliability of any Southern California freeway evaluated through the CSMP process. It has four to five general-purpose lanes as well as barrier-separated high- occupancy vehicle and auxiliary lanes in each direction. Analysis of Existing Conditions The study team analyzed existing reliability conditions along the two freeways by following the approach described in the L02 guide. This allowed the team to test the value of collecting, storing, and using nonrecurring event data from various sources to help explain causal relationships. The L02 guide provided specific techniques for determining these causal factors and for assessing the relative contributions of these factors on the two pilot facilities. 5

One such technique is the use of cumulative distribution functions (CDFs) to visualize the impact of specific reliability factors on travel rates at different congestion levels. Figure ES.3 shows an example of a CDF curve for I-5. Different lines indicate “normal” conditions for uncongested and low-, moderate-, and high-congested regimes. Dotted lines show the same travel rates, but during special events. As can be seen in the figure, special events can dramatically increase travel rates on the facility such that, even under moderate congestion, the travel rates for special events can exceed those on the most heavily congested weekdays. Figure ES.3. Cumulative distribution functions for I-5 special events. Another useful technique presented in the guide summarizes the relative contributions of different nonrecurring events to reliability on the facility (Table ES.2). Decision makers particularly liked this table for its ability to summarize critical factors and suggested that they would be interested in seeing this tested on other facilities. 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50% 55% 60% 65% 70% 75% 80% 85% 90% 95% 100% 45 55 65 75 85 95 105 115 125 135 145 155 165 175 185 195 205 215 225 235 245 255 265 275 285 295 Cu m ul at iv e Di st rib ut io n of T rip s Travel Rate (seconds per mile) Normal-Uncong Normal-Low Cong Normal-Mod Cong Normal-High Cong Special Event-Uncong Special Event-Low Cong Special Event-Mod Cong Special Event-High Cong 6