Research on active collision avoidance algorithm for intelligent vehicle based on improved artificial potential field model

Research on active collision avoidance algorithm for intelligent vehicle based on improved artificial potential field model

In this article, an active collision avoidance based on improved artificial potential field is proposed to satisfy collision avoidance for intelligent vehicle. A longitudinal safety distance model based on analysis of braking process and a lane-changing safety spacing model based on minimum time of...

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Main Authors: Chaochun Yuan, Shuofeng Weng, Jie Shen, Long Chen, Youguo He, Tong Wang
Format: Article
Language:English
Published: SAGE Publishing 2020-05-01
Series:International Journal of Advanced Robotic Systems
Online Access:https://doi.org/10.1177/1729881420911232
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spelling doaj-0d58b395c1744909ba7b8888524c36882020-11-25T04:03:35ZengSAGE PublishingInternational Journal of Advanced Robotic Systems1729-88142020-05-011710.1177/1729881420911232Research on active collision avoidance algorithm for intelligent vehicle based on improved artificial potential field modelChaochun Yuan0Shuofeng Weng1Jie Shen2Long Chen3Youguo He4Tong Wang5 Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, China Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, China Department of Computer and Information Science, University of Michigan-Dearborn, MI, USA Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, China Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, China Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, ChinaIn this article, an active collision avoidance based on improved artificial potential field is proposed to satisfy collision avoidance for intelligent vehicle. A longitudinal safety distance model based on analysis of braking process and a lane-changing safety spacing model based on minimum time of lane changing under the constraint of sideslip angle are presented. In addition, an improved artificial potential field method is introduced, which represents the influence of environmental information with artificial force. Simulation results demonstrate the superior performance of the proposed algorithm over collision avoidance for intelligent vehicle.https://doi.org/10.1177/1729881420911232
collection DOAJ
language English
format Article
sources DOAJ
author Chaochun Yuan
Shuofeng Weng
Jie Shen
Long Chen
Youguo He
Tong Wang
spellingShingle Chaochun Yuan
Shuofeng Weng
Jie Shen
Long Chen
Youguo He
Tong Wang
Research on active collision avoidance algorithm for intelligent vehicle based on improved artificial potential field model
International Journal of Advanced Robotic Systems
author_facet Chaochun Yuan
Shuofeng Weng
Jie Shen
Long Chen
Youguo He
Tong Wang
author_sort Chaochun Yuan
title Research on active collision avoidance algorithm for intelligent vehicle based on improved artificial potential field model
title_short Research on active collision avoidance algorithm for intelligent vehicle based on improved artificial potential field model
title_full Research on active collision avoidance algorithm for intelligent vehicle based on improved artificial potential field model
title_fullStr Research on active collision avoidance algorithm for intelligent vehicle based on improved artificial potential field model
title_full_unstemmed Research on active collision avoidance algorithm for intelligent vehicle based on improved artificial potential field model
title_sort research on active collision avoidance algorithm for intelligent vehicle based on improved artificial potential field model
publisher SAGE Publishing
series International Journal of Advanced Robotic Systems
issn 1729-8814
publishDate 2020-05-01
description In this article, an active collision avoidance based on improved artificial potential field is proposed to satisfy collision avoidance for intelligent vehicle. A longitudinal safety distance model based on analysis of braking process and a lane-changing safety spacing model based on minimum time of lane changing under the constraint of sideslip angle are presented. In addition, an improved artificial potential field method is introduced, which represents the influence of environmental information with artificial force. Simulation results demonstrate the superior performance of the proposed algorithm over collision avoidance for intelligent vehicle.
url https://doi.org/10.1177/1729881420911232
work_keys_str_mv AT chaochunyuan researchonactivecollisionavoidancealgorithmforintelligentvehiclebasedonimprovedartificialpotentialfieldmodel
AT shuofengweng researchonactivecollisionavoidancealgorithmforintelligentvehiclebasedonimprovedartificialpotentialfieldmodel
AT jieshen researchonactivecollisionavoidancealgorithmforintelligentvehiclebasedonimprovedartificialpotentialfieldmodel
AT longchen researchonactivecollisionavoidancealgorithmforintelligentvehiclebasedonimprovedartificialpotentialfieldmodel
AT youguohe researchonactivecollisionavoidancealgorithmforintelligentvehiclebasedonimprovedartificialpotentialfieldmodel
AT tongwang researchonactivecollisionavoidancealgorithmforintelligentvehiclebasedonimprovedartificialpotentialfieldmodel
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