A task-level emergency experience reuse method for freeway accidents onsite disposal with policy distilled reinforcement learning

Yan, Longhao; Wang, Ping; Qi, Fan; Xu, Zhuohang; Zhang, Ronghui; Han, Yu

doi:10.1016/j.aap.2023.107179

Accident Analysis & Prevention

2023

DOI: 10.1016/j.aap.2023.107179

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A task-level emergency experience reuse method for freeway accidents onsite disposal with policy distilled reinforcement learning

Longhao Yan

Ping Wang

Fan Qi

et al.

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2024

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Cited by 1 publication

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Crash data mining in mountainous freeway: a case study with K-prototype algorithm

Wang

2024

Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024)

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To enhance the risk management strategies for crashes in mountainous freeways, this study conducted a data mining using the mountainous freeway in Fuzhou as an example. The K-prototype algorithm was used to cluster crash types into three categories with a SSE of 6450.049. The three categories reflects different crash characteristics, which can be used to implement different strategies. C1 represents crashes with high death rates, primarily occurring in confluence zones and tunnels during holidays with high traffic flow. C2 represents crashes with high injury rates, occurring on bridges, long downhill slopes, and diversion zones during evening peak hours. C3 represents crashes with low severity but long rescue response times. Different risk management strategies such as visual guidance devices and recommended speed reminders, were proposed for the three types of crashes mentioned above. The result also showed that more attention should be paid to the peak hours and holiday time in critical areas to minimize the influence of mountainous freeway crashes.

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Crash data mining in mountainous freeway: a case study with K-prototype algorithm

Wang

2024

Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024)

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A task-level emergency experience reuse method for freeway accidents onsite disposal with policy distilled reinforcement learning

Cited by 1 publication

References 34 publications

Crash data mining in mountainous freeway: a case study with K-prototype algorithm

Crash data mining in mountainous freeway: a case study with K-prototype algorithm

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