A probabilistic approach to driver assistance for delay reduction at congested highway lane drops

This paper proposes an onboard advance warning system based on a probabilistic prediction model that advises vehicles on when to change lanes for an upcoming lane drop. Using several traffic- and driver-related parameters such as the distribution of inter-vehicle headway distances, the prediction mo...

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Autores principales:	Goodarz Mehr, Azim Eskandarian
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Lane change Probability estimation Traffic simulation Parameter analysis Lane drop Transportation engineering TA1001-1280
Acceso en línea:	https://doaj.org/article/d673372feb5746ebb69ed06f09a74d70
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id	oai:doaj.org-article:d673372feb5746ebb69ed06f09a74d70
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spelling	oai:doaj.org-article:d673372feb5746ebb69ed06f09a74d702021-11-30T04:15:27ZA probabilistic approach to driver assistance for delay reduction at congested highway lane drops2046-043010.1016/j.ijtst.2020.10.002https://doaj.org/article/d673372feb5746ebb69ed06f09a74d702021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2046043020300630https://doaj.org/toc/2046-0430This paper proposes an onboard advance warning system based on a probabilistic prediction model that advises vehicles on when to change lanes for an upcoming lane drop. Using several traffic- and driver-related parameters such as the distribution of inter-vehicle headway distances, the prediction model calculates the likelihood of utilizing one or multiple lane changes to successfully reach a target position on the road. When approaching a lane drop, the onboard system projects current vehicle conditions into the future and uses the model to continuously estimate the success probability of changing lanes before reaching the lane-end, and advises the driver or autonomous vehicle to start a lane changing maneuver when that probability drops below a certain threshold. In a simulation case study, the proposed system was used on a segment of the I-81 interstate highway with two lane drops – transitioning from four lanes to two lanes – to advise vehicles on avoiding the lane drops. The results indicate that the proposed system can reduce average delay by up to 50% and maximum delay by up to 33%, depending on traffic flow and the ratio of vehicles equipped with the advance warning system.Goodarz MehrAzim EskandarianElsevierarticleLane changeProbability estimationTraffic simulationParameter analysisLane dropTransportation engineeringTA1001-1280ENInternational Journal of Transportation Science and Technology, Vol 10, Iss 4, Pp 353-365 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Lane change Probability estimation Traffic simulation Parameter analysis Lane drop Transportation engineering TA1001-1280
spellingShingle	Lane change Probability estimation Traffic simulation Parameter analysis Lane drop Transportation engineering TA1001-1280 Goodarz Mehr Azim Eskandarian A probabilistic approach to driver assistance for delay reduction at congested highway lane drops
description	This paper proposes an onboard advance warning system based on a probabilistic prediction model that advises vehicles on when to change lanes for an upcoming lane drop. Using several traffic- and driver-related parameters such as the distribution of inter-vehicle headway distances, the prediction model calculates the likelihood of utilizing one or multiple lane changes to successfully reach a target position on the road. When approaching a lane drop, the onboard system projects current vehicle conditions into the future and uses the model to continuously estimate the success probability of changing lanes before reaching the lane-end, and advises the driver or autonomous vehicle to start a lane changing maneuver when that probability drops below a certain threshold. In a simulation case study, the proposed system was used on a segment of the I-81 interstate highway with two lane drops – transitioning from four lanes to two lanes – to advise vehicles on avoiding the lane drops. The results indicate that the proposed system can reduce average delay by up to 50% and maximum delay by up to 33%, depending on traffic flow and the ratio of vehicles equipped with the advance warning system.
format	article
author	Goodarz Mehr Azim Eskandarian
author_facet	Goodarz Mehr Azim Eskandarian
author_sort	Goodarz Mehr
title	A probabilistic approach to driver assistance for delay reduction at congested highway lane drops
title_short	A probabilistic approach to driver assistance for delay reduction at congested highway lane drops
title_full	A probabilistic approach to driver assistance for delay reduction at congested highway lane drops
title_fullStr	A probabilistic approach to driver assistance for delay reduction at congested highway lane drops
title_full_unstemmed	A probabilistic approach to driver assistance for delay reduction at congested highway lane drops
title_sort	probabilistic approach to driver assistance for delay reduction at congested highway lane drops
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/d673372feb5746ebb69ed06f09a74d70
work_keys_str_mv	AT goodarzmehr aprobabilisticapproachtodriverassistancefordelayreductionatcongestedhighwaylanedrops AT azimeskandarian aprobabilisticapproachtodriverassistancefordelayreductionatcongestedhighwaylanedrops AT goodarzmehr probabilisticapproachtodriverassistancefordelayreductionatcongestedhighwaylanedrops AT azimeskandarian probabilisticapproachtodriverassistancefordelayreductionatcongestedhighwaylanedrops
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A probabilistic approach to driver assistance for delay reduction at congested highway lane drops

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