Chen Ken
7 Papers
2 Citations
Chen Ken is an academic researcher. The author has contributed to research in topics: Graph (abstract data type) & Warning system. The author has an hindex of 2, co-authored 7 publications.
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Papers
Dynamic Spatio-Temporal Graph-Based CNNs for Traffic Flow Prediction
Chen Ken,Chen Fei,Baisheng Lai,Zhongming Jin,Yong Liu,Li Kai,Long Wei,Pengfei Wang,Tang Yandong,Jianqiang Huang,Xian-Sheng Hua +10 more
TL;DR: DST-GCNN is a two stream network that learns expressive features to represent spatio-temporal structures and predicts future traffic flows from surveillance video data and achieves competitive performances compared with the other state-of-the-art methods.
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Dynamic Spatio-temporal Graph-based CNNs for Traffic Prediction
Chen Ken,Chen Fei,Baisheng Lai,Zhongming Jin,Yong Liu,Li Kai,Long Wei,Pengfei Wang,Tang Yandong,Jianqiang Huang,Xian-Sheng Hua +10 more
TL;DR: This paper presents dynamic spatio-temporal graph-based CNNs (DST-GCNNs) by learning expressive features to represent spatio,temporal structures and predict future traffic flows from surveillance video data using a two stream network.
An Early Warning Method for Highway Traffic Accidents Based on Bayesian Networks
Chen Ken,Chen Fei,Li Kai,Liu Juexiong,Fengli Zhang,Lin Mei,Jiayi Zhai +6 more
- 12 Jul 2019
TL;DR: The experimental results show that the proposed early warning method for highway traffic accident based on Bayesian network has higher accuracy in early warning of accidents and the temporal distribution of prediction results is consistent with the peak season.
4
Patent
Vehicle-road cooperative joint service linkage platform
Yong Tang,Chen Ken,Yong Liu,Xiong Qigao,Jianxing Li,Chen Guangjun,Hu Shengxia,Wu Zaixin +7 more
- 05 Jan 2021
TL;DR: In this paper, a one-road multi-party joint service linkage quick response working mechanism is established, and internal workers, public security traffic police officers, highway law enforcement officers, vehicle enterprise parties, road test equipmentsuppliers and vehicle owners can timely perform real-time communication through a communication module, so that a plurality of units can be coordinated to work; and meanwhile, a scheduling module andan emergency processing module are used for managing and cooperatively processing emergencies in real time.
An Algorithm-optimized Car-following Model Based on Chengdu Ring Expressway Traffic Flow Characteristics
TL;DR: An algorithm-optimized car-following model is presented to describe the overall effect on the Chengdu ring expressway in China from May to October, 2019, based on dynamic data observed from the intelligent transportation system.