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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Language: | English |
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IEEE
2025-01-01
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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 |