Research Progress and Prospects of Vehicle Driving Behavior Prediction

Autonomous driving technology is vital for intelligent transportation systems. Vehicle driving behavior prediction is the foundation and core of autonomous driving. A detailed review of the existing research on vehicle driving behavior prediction can improve the understanding of the current progress...

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Main Authors: Xinghua Hu, Mintanyu Zheng
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:World Electric Vehicle Journal
Subjects:
Online Access:https://www.mdpi.com/2032-6653/12/2/88
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spelling doaj-aa0c4fc84cef43fcaf32907e93849f2e2021-07-01T00:32:37ZengMDPI AGWorld Electric Vehicle Journal2032-66532021-06-0112888810.3390/wevj12020088Research Progress and Prospects of Vehicle Driving Behavior PredictionXinghua Hu0Mintanyu Zheng1School of Traffic & Transportation, Chongqing Jiaotong University, Chongqing 400074, ChinaSchool of Traffic & Transportation, Chongqing Jiaotong University, Chongqing 400074, ChinaAutonomous driving technology is vital for intelligent transportation systems. Vehicle driving behavior prediction is the foundation and core of autonomous driving. A detailed review of the existing research on vehicle driving behavior prediction can improve the understanding of the current progress of research on autonomous driving and provide references for follow-up researchers. This paper primarily reviews and analyzes the control models of autonomous driving, prejudgment methods, on-road and intersection traffic decision-making, and shortcomings of the research about the prediction of individual intelligent vehicle driving behavior, the prediction on movements of vehicles connected via the Internet, and prediction of driving behavior in a mixed traffic environment. The deficiencies in the research on vehicle driving behavior prediction are as follows: (1) there are numerous limitations in the intelligent application scenarios of individual intelligent vehicles; (2) although the Internet of Vehicles is a significant developmental trend, the training and test datasets are not rich enough; and (3) as the research of mixed traffic flow is still in the initial stages, the comfort brought by autonomous driving in hybrid driving environments is not being considered. In addition to the above analyses and comments, the future research prospects of vehicle driving behavior prediction are discussed as well.https://www.mdpi.com/2032-6653/12/2/88traffic engineeringintelligent transportationautonomous vehicledriving behaviorindividual intelligent vehicleInternet of Vehicles
collection DOAJ
language English
format Article
sources DOAJ
author Xinghua Hu
Mintanyu Zheng
spellingShingle Xinghua Hu
Mintanyu Zheng
Research Progress and Prospects of Vehicle Driving Behavior Prediction
World Electric Vehicle Journal
traffic engineering
intelligent transportation
autonomous vehicle
driving behavior
individual intelligent vehicle
Internet of Vehicles
author_facet Xinghua Hu
Mintanyu Zheng
author_sort Xinghua Hu
title Research Progress and Prospects of Vehicle Driving Behavior Prediction
title_short Research Progress and Prospects of Vehicle Driving Behavior Prediction
title_full Research Progress and Prospects of Vehicle Driving Behavior Prediction
title_fullStr Research Progress and Prospects of Vehicle Driving Behavior Prediction
title_full_unstemmed Research Progress and Prospects of Vehicle Driving Behavior Prediction
title_sort research progress and prospects of vehicle driving behavior prediction
publisher MDPI AG
series World Electric Vehicle Journal
issn 2032-6653
publishDate 2021-06-01
description Autonomous driving technology is vital for intelligent transportation systems. Vehicle driving behavior prediction is the foundation and core of autonomous driving. A detailed review of the existing research on vehicle driving behavior prediction can improve the understanding of the current progress of research on autonomous driving and provide references for follow-up researchers. This paper primarily reviews and analyzes the control models of autonomous driving, prejudgment methods, on-road and intersection traffic decision-making, and shortcomings of the research about the prediction of individual intelligent vehicle driving behavior, the prediction on movements of vehicles connected via the Internet, and prediction of driving behavior in a mixed traffic environment. The deficiencies in the research on vehicle driving behavior prediction are as follows: (1) there are numerous limitations in the intelligent application scenarios of individual intelligent vehicles; (2) although the Internet of Vehicles is a significant developmental trend, the training and test datasets are not rich enough; and (3) as the research of mixed traffic flow is still in the initial stages, the comfort brought by autonomous driving in hybrid driving environments is not being considered. In addition to the above analyses and comments, the future research prospects of vehicle driving behavior prediction are discussed as well.
topic traffic engineering
intelligent transportation
autonomous vehicle
driving behavior
individual intelligent vehicle
Internet of Vehicles
url https://www.mdpi.com/2032-6653/12/2/88
work_keys_str_mv AT xinghuahu researchprogressandprospectsofvehicledrivingbehaviorprediction
AT mintanyuzheng researchprogressandprospectsofvehicledrivingbehaviorprediction
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