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Short-Term Prediction for the Occurrence Probability of Traffic Incidents in Freeways

Hao Wang, Wei Wang

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Abstract

This paper presents a simple method for freeway traffic incidents short term prediction based on the traffic flow theory. A model is proposed to estimate the probability of traffic incidents occurrence, which is achieved by analyzing traffic flow data from two neighboring detectors. The proposed model indicates that the probability of traffic incident occurrence is positively related to two terms: a) the ratio of the upstream traffic density to the steady traffic density, and b) the speed difference between the upstream traffic and the downstream traffic. The empirical data from Dutch motorways is used to calibrate the model. This method appears promising for the application in the on-line traffic incidents predictions in the future.

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What this paper is about

This paper presents a simple method for freeway traffic incidents short term prediction based on the traffic flow theory. A model is proposed to estimate the probability of traffic incidents occurrence, which is achieved by analyzing traffic flow data from two neighboring detectors. The proposed model indicates that the probability of traffic incident occurrence is positively related to two terms: a) the ratio of the upstream traffic density to the steady traffic density, and b) the speed difference between the upstream traffic and the downstream traffic. The empirical data from Dutch motorways is used to calibrate the model. This method appears promising for the application in the on-line traffic incidents predictions in the future.

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Available abstract

This paper presents a simple method for freeway traffic incidents short term prediction based on the traffic flow theory. A model is proposed to estimate the probability of traffic incidents occurrence, which is achieved by analyzing traffic flow data from two neighboring detectors. The proposed model indicates that the probability of traffic incident occurrence is positively related to two terms: a) the ratio of the upstream traffic density to the steady traffic density, and b) the speed difference between the upstream traffic and the downstream traffic. The empirical data from Dutch motorways is used to calibrate the model. This method appears promising for the application in the on-line traffic incidents predictions in the future.

Key concepts: Traffic flow (computer networking), Upstream (networking), Traffic congestion reconstruction with Kerner's three-phase theory, Traffic conflict, Computer science, Term (time), Traffic generation model, Transport engineering

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