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to include in the Southern California CSMPs and expressed an interest in extending and focusing SHRP 2 efforts on short- to medium-term operations-centric projects. These projects tend not to be controversial to environmental stakeholders; improving reliability will generally lead to improvements in GHG emissions. This is in line with a goal of this SHRP 2 pilot testing to find ways to demonstrate how operational strategies improve travel time reliability, which is highly valued by both the person and goods movement transportation markets: ⢠Travelers get frustrated when their trip travel times vary significantly. They either have to routinely plan for longer travel times or frequently arrive at their destinations later than planned. ⢠Truck drivers often do not have choices. They have to arrive at a certain time, so they must plan for a margin of unexpected delays, which reduces their productivity and increases costs. Caltrans representatives recognized the value of incorporating reliability in decision making and thought reliability could be useful as one measure among many for choosing operations projects. Reliability also may help to promote managed lane projects, which are a major focus of planning efforts in Southern California. SHRP 2 Tool Modifications Calibrating the SHRP 2 tools to baseline conditions is a critical first step before any reliability analysis can occur. The reliability tools show promise for analyzing travel time reliability on highway facilities, but they need modifications to their user interfaces and calculation analytics before they are ready for implementation by transportation agencies. The Southern California pilot site provided the SHRP 2 Reliability program with a list of quick fixes that are critical for moving the tools toward implementation. The detailed findings in this report support those quick fixes. Below are a few common threads of modifications needed across the tools: ⢠There needs to be guidance for how to calibrate each tool to baseline conditions. This guidance should cover how to identify study areas and analysis periods as well as which levers allow the tool to be calibrated. ⢠These calibration levers must be easily accessible to the user. The Southern California study team identified several variables, such as capacity, capacity adjustment factors, and demand by hour of day that can be used to calibrate models. In some tools, these calibration levers are hidden from the user or not presented directly on the input pages. They need to be made more easily accessible. 12
