An Analysis Of The Impact Of An Incident Management System On Secondary Incidents On Freeways – An Application To The I-5 In California
Accidents are the largest source of external costs related to transportation in the United States with annual costs estimated to exceed $200 billion per year. Incidents also create traffic backups and delays that can result in secondary incidents (i.e., collisions that occur as a result of other incidents). Although incident management has received a lot of attention from academics and practitioners alike, secondary incidents have so far been somewhat neglected.
The main purpose of this dissertation is to investigate empirically whether the implementation of changeable message signs (CMS), which are one Intelligent Transportation System tool, can reduce secondary collisions. After reviewing previously published methods for estimating secondary accidents, I implement a Binary Speed Contour Map approach to detect secondary incidents using PeMS data. I also estimate the extra time lost to congestion because of incidents. My study area is a portion of Interstate 5 that stretches 74 miles from the Mexico-US border to Orange County, CA. This freeway has an average annualized daily traffic volume of 230,000 vehicles and fifty-five miles of it are equipped with CMS. My unique dataset includes incident data for 2008 combined with detailed weather data, elements of freeway geometry, and information about CMS usage.
I identify a total of 10,172 incidents in my study area in 2008. Using the BSCM approach, I find that 4.6 percent ofcollisions were secondary incidents. Moreover, my statistical model shows that incidents occurring during evening peak hours on Fridays are more likely to result in secondary crashes as do more severe incidents, areas with a complex
geometry, wet pavement, and changeable message signs (CMS). The maximum effectiveness of a CMS is approximately 10.5 miles for a range of 21 miles. Finally, annual incident-related congestion is approximately 1.9 hours per freeway vehicle, which represents five percent of the 37 hours of annual traffic delay experienced by the average San Diego motorist.