Empirical Observation of the Impact of Traffic Oscillations on Freeway Safety: Final Report, OTREC-RR-10-13, September 2010

012080492010Final report.PDFTech ReportOTREC-RR-10-1308-108Accident dataFreewaysLogistic regression analysisStandard deviationTraffic congestionTraffic speedTraffic patternsTraffic congestionExpress highwaysTraffic safetyResearch HubHighwaysSafety and Human FactorsI80: Accident StudiesOregonUnited StatesOregon Transportation Research and Education ConsortiumMonsere, ChristopherAhn, SoyoungZheng, ZuduoPortland State University. Dept. of Civil & Environmental EngineeringArizona State University. Dept. of Civil, Environmental and Sustainable EngineeringOregon Transportation Research and Education ConsortiumUnited States. Dept. of Transportation. Research and Innovative Technology AdministrationNTL-OPERATIONS AND TRAFFIC CONTROLS-OPERATIONS AND TRAFFIC CONTROLSNTL-OPERATIONS AND TRAFFIC CONTROLS-CongestionUS Transportation CollectionTraffic oscillations are typical features of congested traffic flow that are characterized by recurring decelerations followed by accelerations (stop-and-go driving). The negative environmental impacts of these oscillations are widely accepted, but their impact on traffic safety has been debated. This report describes the impact of freeway traffic oscillations on traffic safety. This study employs a matched case-control design using high resolution traffic and crash data from a freeway segment. Traffic conditions prior to each crash were taken as cases, while traffic conditions during the same periods on days without crashes were taken as controls. These were also matched by presence of congestion, geometry and weather. A total of 82 cases and about 80,000 candidate controls were extracted from more than three years of data from 2004 to 2007. Conditional logistic regression models were developed based on the case-control samples. To verify consistency in the results, 20 different sets of controls were randomly extracted from the candidate pool. The results reveal that the standard deviation of speed (thus, oscillations) is a significant variable, with an average odds ratio of about 1.08. This implies that the odds of a (rear-end) crash occurring increases by about 8 percent with an additional unit increase in the standard deviation of speed. The average traffic states prior to crashes were less significant than the speed variations in congestion