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Identifying crash type propensity using real-time traffic data on freeways

Abstract : We examine the effects of various traffic parameters on type of road crash. Multivariate Probit models are specified on 4-years of data from the A4-A86 highway section in the Ile-de-France region, France. Empirical findings indicate that crash type can almost exclusively be defined by the prevailing traffic conditions shortly before its occurrence. Rear-end crashes involving two vehicles were found to be more probable for relatively low values of both speed and density, rear-end crashes involving more than two vehicles appear to be more probable under congested congestions, while single-vehicle crashes appear to be largely geometry-dependent.
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https://hal.archives-ouvertes.fr/hal-01221053
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Submitted on : Tuesday, October 27, 2015 - 12:59:16 PM
Last modification on : Saturday, January 15, 2022 - 3:47:40 AM

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Z Christoforou, S Cohen, M Karlaftis. Identifying crash type propensity using real-time traffic data on freeways. Journal of Safety Research, Elsevier, 2011, 42 (42), pp 43-50. ⟨10.1016/j.jsr.2011.01.001⟩. ⟨hal-01221053⟩

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