The tremendous adoption and usage of electric bikes have caused a series of challenges to road safety in China. The existing researches mainly use accumulated trajectory clusters or pairwise conflict indicators to model the potential risks among electric bikes, neglecting different spatial interactions from surrounding electric bikes or the corresponding temporal causality. A novel video-based sequential heat map method is proposed to represent the temporal influence area of a running electric bike as a teardrop-shaped thermal potential field, instead of accumulating group conflicts from irrelevant trajectories or decomposing them into several pairwise indicators. A time decay factor along with a thermal diffusion process is introduced in order to retain both spatial and temporal motion information. Moreover, a spatial–temporal potential risk index scheme based on the sequential heat map model is proposed to detect the type of potential risk as well as the occurring time and place. The experiment results have shown its strength and efficiency of the proposed risk detecting method in seeking for the potential risk areas and electric bikes’ conflicts.
Video-based method for detecting potential risks among multiple electric bikes
IET Intelligent Transport Systems ; 13 , 9 ; 1440-1446
2019-06-11
7 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
pattern clustering , temporal motion information , filtering theory , usage , pairwise conflict indicators , video-based method , different spatial interactions , pairwise indicators , spatial–temporal potential risk index scheme , multiple electric bikes , video-based sequential heat map method , tremendous adoption , spatial motion information , risk detecting method , corresponding temporal causality , video signal processing , running electric bike , image motion analysis , road safety , statistical analysis , sequential heat map model , spatiotemporal phenomena , thermal diffusion , temporal influence area , teardrop-shaped thermal potential field , image sequences , risk management , potential risk areas
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