Chinese Journal of Intelligent Science and Technology ›› 2022, Vol. 4 ›› Issue (1): 1-13.doi: 10.11959/j.issn.2096-6652.202220

• Review Intelligence •     Next Articles

Traffic situational awareness research and development enhanced by social media data: the state of the art and prospects

Yuanwen CHEN1,2, Xiao WANG2,3, Lingxi LI3,4, Fei-Yue WANG2,3   

  1. 1 Department of Automation, School of Aerospace Engineering, Xiamen University, Xiamen 361100, China
    2 The State Key Laboratory for Management and Control of Complex Systems, Chinese Academy of Sciences, Beijing 100190, China
    3 Parallel Intelligence Innovation Center, Qingdao Academy of Intelligent Industries, Qingdao 266114, China
    4 Department of Electrical and Computer Engineering, Indiana University-Purdue University, Indianapolis IN 46204, USA
  • Revised:2022-03-01 Online:2022-03-15 Published:2022-03-01
  • Supported by:
    The National Natural Science Foundation of China(62173329)

Abstract:

Traffic situational awareness is an important research direction of intelligent transportation systems.Most of the existing research focused on how to use physical sensors to perceive the current traffic situation and predict the future traffic state.However, the performance of physical sensors is prone to instability or failure due to adverse weather, electromagnetic interference, energy limitation and other problems, resulting in sparse or missing collected data, which makes the perception of traffic situation lagging and inaccurate.Social media data provides a new and enhanced way of perceiving comprehensive traffic situation information in a timely manner.Facing with the current traffic situation where sudden abnormal traffic events occur frequently, social sensing and physical sensing data can complement with each other to further improve the efficiency of urban traffic management.The related work of traffic event detection and traffic state prediction enhancing based on social media data were analyzed, and how those research works provide decision support for the traffic management departments to plan and guide traffic reasonably and alleviate traffic congestion were explored.Finally, some future research directions of traffic situational awareness enhanced by social media data were proposed.

Key words: traffic situational awareness, intelligent transportation system, social perception, traffic event detection, traffic state prediction

CLC Number: 

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