Corpus ID: 235485593

Edge Computing for Real-Time Near-Crash Detection for Smart Transportation Applications

@inproceedings{Ke2020EdgeCF,
  title={Edge Computing for Real-Time Near-Crash Detection for Smart Transportation Applications},
  author={Ruimin Ke and Zhiyong Cui and Yanlong Chen and Meixin Zhu and Hao Yang and Yinhai Wang},
  year={2020}
}
Traffic near-crash events serve as critical data sources for various smart transportation applications, such as being surrogate safety measures for traffic safety research and corner case data for automated vehicle testing. However, there are several key challenges for near-crash detection. First, extracting nearcrashes from original data sources requires significant computing, communication, and storage resources. Also, existing methods lack efficiency and transferability, which bottlenecks… Expand

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