Review of Vehicle Behavior Prediction for Intelligent Driving Systems in Highway Scenarios

In recent years, particularly since 2015, autonomous driving systems have developed rapidly. With the increase of autonomous driving levels, more precise detection and environment cognition are necessary. In this paper, a systematic review on vehicle behavior prediction in highway scenarios is carried out, including the role of vehicle behavior prediction in autonomous driving system, the application scenarios and the mechanisms of widely used vehicle behavior prediction methods such as the Bayesian network (BN) based method and the long short-term memory (LSTM) network-based method. The future directions of vehicle behavior prediction are discussed.

• Record URL:
  • https://doi.org/10.1177/03611981241260698
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/03611981
• Supplemental Notes:
  • Zihan Wang https://orcid.org/0009-0008-8619-0234© The Author(s) 2024.
• Authors:
  • Wang, Zihan
  • 0009-0008-8619-0234
  • Li, Guozheng
  • Peng, Lihui
• Publication Date: 2024

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Serial:
  • Transportation Research Record: Journal of the Transportation Research Board
  • Publisher: Sage Publications, Incorporated
  • ISSN: 0361-1981
  • EISSN: 2169-4052
  • Serial URL: http://journals.sagepub.com/home/trr

Subject/Index Terms

• TRT Terms: Advanced vehicle control systems; Autonomous vehicles; Detection and identification; Forecasting; Mathematical prediction; Vehicle dynamics
• Subject Areas: Data and Information Technology; Highways; Planning and Forecasting; Vehicles and Equipment;

Filing Info

• Accession Number: 01926328
• Record Type: Publication
• Files: TRIS, TRB
• Created Date: Aug 1 2024 2:39PM