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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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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1721348308779139072 |