Inferring and Analysis Drivers Violation Behavior Through Trajectory - Intelligence Science I (ICIS 2017) Access content directly
Conference Papers Year : 2017

Inferring and Analysis Drivers Violation Behavior Through Trajectory

Zouqing Cai
  • Function : Author
  • PersonId : 1033394
Yongying Zhu
  • Function : Author
  • PersonId : 1033395
Mingyu Lu
  • Function : Author
  • PersonId : 1033396
Lei Wu
  • Function : Author
  • PersonId : 1033397


In this paper, we present an algorithm for inferring violation movements and categorizing levels of driving behavior. With this algorithm we extract the speeding and retrograde behavior from the real trajectories datasets of Xinjiang, analyze the changing regulation of six streets in the working day and day off on the overall and explore the driving characteristics which is very dangerous (level 4). The results of this study can not only be used for early warning of drivers violations, but also provide the data support and decision basis for the traffic management department to master the situation of traffic violations and formulate the traffic management counter measures.
Fichier principal
Vignette du fichier
978-3-319-68121-4_32_Chapter.pdf (785.02 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-01820920 , version 1 (22-06-2018)





Zouqing Cai, Wei Pei, Yongying Zhu, Mingyu Lu, Lei Wu. Inferring and Analysis Drivers Violation Behavior Through Trajectory. 2nd International Conference on Intelligence Science (ICIS), Oct 2017, Shanghai, China. pp.295-304, ⟨10.1007/978-3-319-68121-4_32⟩. ⟨hal-01820920⟩
44 View
82 Download



Gmail Facebook X LinkedIn More