United States Department of Transportation
i
Quantifying Incident-Induced Travel Delays on Freeways Using Traffic Sensor Data [2008-02]
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2008-02-01
[PDF-868.21 KB]
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Edition:Final research report
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Abstract:Traffic congestion is a major operational problem for freeways in Washington State. Recent studies have estimated that more than 50% of freeway congestion is caused by traffic incidents. To help the Washington State Department of Transportation (WSDOT) identify effective countermeasures against such congestion-inducing incidents, a thorough understanding of travel delays caused by incidents is essential. This research project developed a new algorithm for quantifying travel delays induced by different incident categories using traffic data extracted from archived loop detector data and incident log data recorded by the WSDOT Incident Response (IR) team. The algorithm applies a modified deterministic queuing theory to estimate incident-induced delay using one-minute aggregated loop detector data. Incident-induced delay refers to the difference between the total delay and the recurring travel delay at the time and location associated with the impact of incident. The specialty of the delay calculation in this study is the use of a dynamic traffic-volume-based background profile, which is considered a more accurate representative of prevailing traffic conditions. According to the test results, the proposed algorithm can provide good incident-induced delay estimates and capture the evolution of freeway traffic flow during incident duration. Since the actual traffic data measured by loop detectors are used in this study to compute vehicle arrival and departure rates for delay calculations, the estimated incident-induced delay should be much closer to the reality than simulation based estimates. Additionally, the proposed algorithm was implemented in the Advanced Roadway Incident Analyzer (ARIA) system. ARIA is a database-driven computer system that automates all the computational processes. More accurate incident delay information will help WSDOT improve its understanding of congestion-inducing incidents and select more effective countermeasures against incident-related traffic congestion on freeways. /Abstract from report summary page/
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