Real-time crash prediction of elevated expressway based on gene expression programming algorithm
In order to effectively predict crash on elevated expressway,taking Yan'an elevated expressway in Shanghai as the research object,based on its traffic flow and crash data,an improved Gene Expression Programming algorithm with additional elite gene bank and extinction mechanism was applied to dig out'Crash Prediction Empirical Formula'.The prediction accuracy and interpretability of the empirical formula were verified by comparing with the results of machine learning and statistical analysis.The crash of another expressway was predicted by empirical formula without retraining and calibration,and the portability of the empirical formula was verified.The research results indicated that the prediction performance of the empirical formula on the Yan'an elevated expressway dataset is significantly improved compared with the traditional Logistics regression,and the receiver operating characteristic curve area and F1-score indexes are consistent with the artificial neural network model,identifying 74%of the crashes correctly.The good performance of the empirical formula on Hangzhou Shangtang elevated expressway dataset shows that the empirical formula has basic portability.In conclusion,the gene expression programming algorithm considers both high accuracy and interpretability for the crash risk prediction problem,and shows portability,which is helpful to establish a low-cost and efficient crash prediction system.
engineering of traffic and transportation systemcrash predictiongene expression programmingelevated expressway
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