Dynamic Car-Following Model With Jerk Suppression for Highway Autonomous Driving

This study proposes a dynamic safe car-following strategy that is based on dynamic adjustment of headway time with jerk suppression. Reinforcement learning models trained with this strategy result in enhanced safety and driving comfort, validated using real driving data from the Next Generation Simu...

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Main Authors: Ke Liu, Jing Ma, Edmund M.-K. Lai
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10856099/
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author Ke Liu
Jing Ma
Edmund M.-K. Lai
author_facet Ke Liu
Jing Ma
Edmund M.-K. Lai
author_sort Ke Liu
collection DOAJ
description This study proposes a dynamic safe car-following strategy that is based on dynamic adjustment of headway time with jerk suppression. Reinforcement learning models trained with this strategy result in enhanced safety and driving comfort, validated using real driving data from the Next Generation Simulation (NGSIM) I-80 and HighD datasets. Simulation results demonstrate significant reduction in the risk of collisions. More importantly, low collision rates are maintained with driving speed profiles that are different from the training data, exhibiting cross-dataset generalizability. It also significantly improves driving comfort, with a 10% jerk reduction compared to existing models.
format Article
id doaj-art-10a63c69495c482fb6a59f2997ca11c1
institution Kabale University
issn 2169-3536
language English
publishDate 2025-01-01
publisher IEEE
record_format Article
series IEEE Access
spelling doaj-art-10a63c69495c482fb6a59f2997ca11c12025-02-07T00:01:36ZengIEEEIEEE Access2169-35362025-01-0113231112311910.1109/ACCESS.2025.353559610856099Dynamic Car-Following Model With Jerk Suppression for Highway Autonomous DrivingKe Liu0https://orcid.org/0009-0008-8445-8428Jing Ma1https://orcid.org/0000-0002-5128-2445Edmund M.-K. Lai2https://orcid.org/0000-0001-9159-3718School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Auckland, New ZealandSchool of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Auckland, New ZealandSchool of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Auckland, New ZealandThis study proposes a dynamic safe car-following strategy that is based on dynamic adjustment of headway time with jerk suppression. Reinforcement learning models trained with this strategy result in enhanced safety and driving comfort, validated using real driving data from the Next Generation Simulation (NGSIM) I-80 and HighD datasets. Simulation results demonstrate significant reduction in the risk of collisions. More importantly, low collision rates are maintained with driving speed profiles that are different from the training data, exhibiting cross-dataset generalizability. It also significantly improves driving comfort, with a 10% jerk reduction compared to existing models.https://ieeexplore.ieee.org/document/10856099/Autonomous drivingcar-followingjerk reductionadaptive headway threshold
spellingShingle Ke Liu
Jing Ma
Edmund M.-K. Lai
Dynamic Car-Following Model With Jerk Suppression for Highway Autonomous Driving
IEEE Access
Autonomous driving
car-following
jerk reduction
adaptive headway threshold
title Dynamic Car-Following Model With Jerk Suppression for Highway Autonomous Driving
title_full Dynamic Car-Following Model With Jerk Suppression for Highway Autonomous Driving
title_fullStr Dynamic Car-Following Model With Jerk Suppression for Highway Autonomous Driving
title_full_unstemmed Dynamic Car-Following Model With Jerk Suppression for Highway Autonomous Driving
title_short Dynamic Car-Following Model With Jerk Suppression for Highway Autonomous Driving
title_sort dynamic car following model with jerk suppression for highway autonomous driving
topic Autonomous driving
car-following
jerk reduction
adaptive headway threshold
url https://ieeexplore.ieee.org/document/10856099/
work_keys_str_mv AT keliu dynamiccarfollowingmodelwithjerksuppressionforhighwayautonomousdriving
AT jingma dynamiccarfollowingmodelwithjerksuppressionforhighwayautonomousdriving
AT edmundmklai dynamiccarfollowingmodelwithjerksuppressionforhighwayautonomousdriving