Abstract
The paper proposes an automatic traffic accident detection algorithm for the urban expressway. The algorithm is established on longitudinal time series theory based on catastrophe theory and statistics theory. The results: (1) the lengthways time series of traffic parameters data manifests a good stability than the transverse time series and it can detect accident when the losing data are more; (2) no matter what traffic flow stats are, the model can detect accident accurately. The model developed in the study can be directly used by traffic engineers and managers to detect traffic accident.
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Acknowledgements
This work was supported by National Natural Science Foundation of China (No. 71501061, 51408190 and 51608171), Natural Science Foundation of Jiangsu province (No. BK20150821), and Science and Technology Plan of Hubei Provincial Transport Department (No.2016-13-1-3).
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Li, Hw., Li, Sl., Zhu, Hw., Zhao, X., Zhang, X. (2019). Automated Detection Algorithm for Traffic Incident in Urban Expressway Based on Lengthways Time Series. In: Wang, W., Bengler, K., Jiang, X. (eds) Green Intelligent Transportation Systems. GITSS 2017. Lecture Notes in Electrical Engineering, vol 503. Springer, Singapore. https://doi.org/10.1007/978-981-13-0302-9_61
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DOI: https://doi.org/10.1007/978-981-13-0302-9_61
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