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A hybrid machine learning model for predicting Real-Time secondary crash likelihood
Accident Analysis & Prevention, 2022Secondary crashes usually occur within the spatio-temporal impact ranges of primary crashes, which could cause traffic disturbance and increase traffic safety problems. However, existing studies only focused on predicting the likelihood of crashes leading to secondary crashes without considering the likelihood of the occurrence of secondary crashes. In
Pei, Li, Mohamed, Abdel-Aty
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Data integration and clustering for real time crash prediction
Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration (IEEE IRI 2014), 2014Cities are facing increasingly challenges with the projected population growth and the resulting increased urban travel demand. Road safety is a major issue in urban planning. Much of the empirical research on road safety and determining the probability of accidents has focused on the accident events. While human error and mechanical failure are common
Elahe Paikari +3 more
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Real-time rear-end crash potential prediction on freeways
Journal of Central South University, 2017This study develops new real-time freeway rear-end crash potential predictors using support vector machine (SVM) technique. The relationship between rear-end crash occurrences and traffic conditions were explored using historical loop detector data from Interstate-894 in Milwaukee, Wisconsin, USA.
Xu Qu, Wei Wang, Wen-fu Wang, Pan Liu
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Real-time crash prediction on expressways using deep generative models
Transportation Research Part C: Emerging Technologies, 2020Abstract Real-time crash prediction is essential for proactive traffic safety management. However, developing an accurate prediction model is challenging as the traffic data of crash and non-crash cases are extremely imbalanced. Most of the previous studies undersampled non-crash cases to balance the data, which may not capture the heterogeneity of ...
Qing Cai +4 more
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Real-time crash prediction based on high definition monitoring systems
2017 2nd IEEE International Conference on Intelligent Transportation Engineering (ICITE), 2017This paper presents an innovative approach to investigate the inner mechanism between traffic status and crash potential based on High Definition Monitoring Systems (HDMS) data. HDMS records delicate vehicle trajectory data and characteristic details. Matched case-control method and Support Vector Machines (SVMs) were employed to identify risk status ...
Jinming You +3 more
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Real-time prediction and avoidance of secondary crashes under unexpected traffic congestion
Accident Analysis & Prevention, 2018According to the Federal Highway Administration, nonrecurring congestion contributes to nearly half of the overall congestion. Temporal disruptions impact the effective use of the complete roadway, due to speed reduction and rubbernecking resulting from primary incidents that in turn provoke secondary incidents.
Hyoshin, Park +3 more
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A novel approach for real time crash prediction at signalized intersections
Transportation Research Part C: Emerging Technologies, 2020Abstract This study proposes a novel approach to predict real time crash risk at signalized intersections at the signal cycle level. The approach uses traffic conflicts extracted from informative vehicle trajectories as an intermediate for crash prediction and develops generalized extreme value (GEV) models based on conflict extremes.
Lai Zheng, Tarek Sayed
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A Genetic Programming Model for Real-Time Crash Prediction on Freeways
IEEE Transactions on Intelligent Transportation Systems, 2013This paper aimed at evaluating the application of the genetic programming (GP) model for real-time crash prediction on freeways. Traffic, weather, and crash data used in this paper were obtained from the I-880N freeway in California, United States.
Chengcheng Xu, Wei Wang, Pan Liu
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Predicting reduced visibility related crashes on freeways using real-time traffic flow data
Journal of Safety Research, 2013The main objective of this paper is to investigate whether real-time traffic flow data, collected from loop detectors and radar sensors on freeways, can be used to predict crashes occurring at reduced visibility conditions. In addition, it examines the difference between significant factors associated with reduced visibility related crashes to those ...
Hassan, Hany M., Abdel-Aty, Mohamed A.
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Developing transferable real-time crash prediction models for highly imbalanced data
2022The advent of Intelligent Transport Systems (ITS) has facilitated a shift towards proactive safety measures in which a crash occurrence is anticipated and prevented before it happens under the proactive safety approach. Given the capability to identify pre-crash conditions, real-time crash prediction has become widely examined with the availability of ...
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