A probabilistic approach to driver assistance for delay reduction at congested highway lane drops
| dc.contributor.author | Mehr, Goodarz | en |
| dc.contributor.author | Eskandarian, Azim | en |
| dc.date.accessioned | 2022-03-22T19:49:31Z | en |
| dc.date.available | 2022-03-22T19:49:31Z | en |
| dc.date.issued | 2021-12-01 | en |
| dc.date.updated | 2022-03-22T19:35:16Z | en |
| dc.description.abstract | 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. | en |
| dc.description.notes | Manuscript accepted for publication in the International Journal of Transportation Science and Technology. This manuscript version is made available under the CC-BY-NC-ND 4.0 license (http://creativecommons.org/licenses/by-nc-nd/4.0/) | en |
| dc.description.version | Accepted version | en |
| dc.format.extent | Pages 353-365 | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.doi | https://doi.org/10.1016/j.ijtst.2020.10.002 | en |
| dc.identifier.eissn | 2046-0449 | en |
| dc.identifier.issn | 2046-0430 | en |
| dc.identifier.issue | 4 | en |
| dc.identifier.orcid | Eskandarian, Azim [0000-0002-4117-7692] | en |
| dc.identifier.uri | http://hdl.handle.net/10919/109412 | en |
| dc.identifier.volume | 10 | en |
| dc.language.iso | en | en |
| dc.publisher | Elsevier | en |
| dc.relation.uri | http://arxiv.org/abs/2007.14232v2 | en |
| dc.relation.uri | http://dx.doi.org/10.1016/j.ijtst.2020.10.002 | en |
| dc.rights | Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International | en |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | en |
| dc.subject | eess.SY | en |
| dc.subject | cs.SY | en |
| dc.title | A probabilistic approach to driver assistance for delay reduction at congested highway lane drops | en |
| dc.title.serial | International Journal of Transportation Science and Technology | en |
| dc.type | Article - Refereed | en |
| dc.type.dcmitype | Text | en |
| dc.type.other | Journal Article | en |
| pubs.organisational-group | /Virginia Tech | en |
| pubs.organisational-group | /Virginia Tech/Engineering | en |
| pubs.organisational-group | /Virginia Tech/Engineering/Mechanical Engineering | en |
| pubs.organisational-group | /Virginia Tech/All T&R Faculty | en |
| pubs.organisational-group | /Virginia Tech/Engineering/COE T&R Faculty | en |
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