Behavior Prediction of Traffic Actors for Intelligent Vehicle Using Artificial Intelligence Techniques: A Review

被引:21
作者
Kolekar, Suresh [1 ]
Gite, Shilpa [1 ,2 ]
Pradhan, Biswajeet [3 ,4 ,5 ]
Kotecha, Ketan [1 ,2 ]
机构
[1] Symbiosis Int Univ, Symbiosis Inst Technol, Comp Sci & Informat Technol Dept, Pune 412115, Maharashtra, India
[2] Symbiosis Int Univ, Symbiosis Ctr Appl SCAAI, Pune 412115, Maharashtra, India
[3] Univ Technol Sydney, Fac Engn & IT, Ctr Adv Modelling & Geospatial Informat Syst CAMG, Ultimo, NSW 2007, Australia
[4] King Abdulaziz Univ, Ctr Excellence Climate Change Res, Jeddah 21589, Saudi Arabia
[5] Univ Kebangsaan Malaysia, Inst Climate Change, Earth Observat Ctr, Bangi 43600, Selangor, Malaysia
关键词
Intelligent vehicles; Systematics; Predictive models; Artificial intelligence; Roads; Navigation; Bibliographies; Intelligent driving; deep learning; intelligent vehicles; vehicle behavior prediction; pedestrian behavior prediction; PEDESTRIAN PREDICTION; TRAJECTORY PREDICTION; HYBRID APPROACH; NETWORKS; POSE; LSTM;
D O I
10.1109/ACCESS.2021.3116303
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Intelligent vehicle technology has made tremendous progress due to Artificial Intelligence (AI) techniques. Accurate behavior prediction of surrounding traffic actors is essential for the safe and secure navigation of the intelligent vehicle. Minor misbehavior of these vehicles on the busy roads may lead to an accident. Due to this, there is a need for vehicle behavior research work in today's era. This research article reviews traffic actors' behavior prediction techniques for intelligent vehicles to perceive, infer, and anticipate other vehicles' intentions and future actions. It identifies the key strategies and methods for AI, emerging trends, datasets, and ongoing research issues in these fields. As per the authors' knowledge, this is the first systematic literature review dedicated to the vehicle behavior study examining existing academic literature published by peer review venues between 2011 and 2021. A systematic review was undertaken to examine these papers, and five primary research questions have been addressed. The findings show that using sophisticated input representation that includes traffic rules and road geometry, artificial intelligence-based solutions applied to behavior prediction of traffic actors for intelligent vehicles have shown promising success, particularly in complex driving scenarios. Finally, the paper summarizes the most widely used approaches in behavior prediction of traffic actors for intelligent vehicles, which the authors believe serves as a foundation for future research in behavior prediction of surrounding traffic actors for secure and accurate intelligent vehicle navigation.
引用
收藏
页码:135034 / 135058
页数:25
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