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Proactive freeway crash prevention using real-time traffic control

2003; NRC Research Press; Volume: 30; Issue: 6 Linguagem: Inglês

10.1139/l03-040

1208-6029

Chris Lee, Bruce Hellinga, Frank Saccomanno,

Traffic control and management

This paper makes use of a probabilistic model that predicts the likelihood of crashes (crash potential) on freeways on the basis of traffic flow conditions, in real-time crash prevention. The model was developed using incident logs and loop detector data collected over a 13-month period on the Gardiner Expressway in Toronto. Previous work suggested that an increase in levels of traffic turbulence generally yields high crash potential. Traffic turbulence was defined in terms of a series of crash precursors that represent traffic conditions that were present prior to crash occurrence. To apply the model in crash prevention, the link needs to be established between crash potential and real-time safety intervention. The objective of this paper is to explore this link for different thresholds of crash potential. The paper discusses the guidelines for evaluating the safety benefit of one crash prevention strategy (variable speed limits) and suggests the risk-based evaluation framework for real-time traffic control.Key words: crash, accident, freeway, safety, traffic flow, real-time control.