Time-Delay following Model for Connected and Automated Vehicles with Collision Conflicts and Forced Deceleration
The connected and automated car-following model can provide a model reference for the queue control algorithm of connected and automated driving and has become a hot research topic in the field of connected vehicles and intelligent transportation. A queue of fast-moving vehicles on urban roads can c...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi-Wiley
2024-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2024/6632473 |
| _version_ | 1827077649617387520 |
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| author | Wenbo Wang Fei Hui Kaiwang Zhang Xiangmo Zhao Asad J. Khattak |
| author_facet | Wenbo Wang Fei Hui Kaiwang Zhang Xiangmo Zhao Asad J. Khattak |
| author_sort | Wenbo Wang |
| collection | DOAJ |
| description | The connected and automated car-following model can provide a model reference for the queue control algorithm of connected and automated driving and has become a hot research topic in the field of connected vehicles and intelligent transportation. A queue of fast-moving vehicles on urban roads can cause traffic congestion when forced to slow down and, in serious cases, can cause rear-impact accidents. Therefore, this paper introduces information on the time delay of information reception and processing, a collision risk quantification factor reflecting the speed characteristics of the front vehicle, and the speed limit and proposes an improved intelligent driver collision quantification model that considers drastic changes in the speed of the front vehicle. Additionally, the model parameters are calibrated using real vehicle data from urban roads combined with an improved salp swarm algorithm. Finally, the evolution rule of disturbance in the traffic flow under different states is analyzed using a time-space diagram, and the DIDM-CSCL model is compared with the classical IDM. The results show that the improved IDM can better describe the following behavior at the microscopic level, which provides a basis for research related to connected and automated driving. |
| first_indexed | 2024-04-24T07:40:21Z |
| format | Article |
| id | doaj.art-9a97311cf5ac4d858a4862da08272390 |
| institution | Directory Open Access Journal |
| issn | 2042-3195 |
| language | English |
| last_indexed | 2025-03-20T02:17:08Z |
| publishDate | 2024-01-01 |
| publisher | Hindawi-Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj.art-9a97311cf5ac4d858a4862da082723902024-10-03T07:50:09ZengHindawi-WileyJournal of Advanced Transportation2042-31952024-01-01202410.1155/2024/6632473Time-Delay following Model for Connected and Automated Vehicles with Collision Conflicts and Forced DecelerationWenbo Wang0Fei Hui1Kaiwang Zhang2Xiangmo Zhao3Asad J. Khattak4School of Information EngineeringSchool of Information EngineeringSchool of Information EngineeringSchool of Information EngineeringSchool of Information EngineeringThe connected and automated car-following model can provide a model reference for the queue control algorithm of connected and automated driving and has become a hot research topic in the field of connected vehicles and intelligent transportation. A queue of fast-moving vehicles on urban roads can cause traffic congestion when forced to slow down and, in serious cases, can cause rear-impact accidents. Therefore, this paper introduces information on the time delay of information reception and processing, a collision risk quantification factor reflecting the speed characteristics of the front vehicle, and the speed limit and proposes an improved intelligent driver collision quantification model that considers drastic changes in the speed of the front vehicle. Additionally, the model parameters are calibrated using real vehicle data from urban roads combined with an improved salp swarm algorithm. Finally, the evolution rule of disturbance in the traffic flow under different states is analyzed using a time-space diagram, and the DIDM-CSCL model is compared with the classical IDM. The results show that the improved IDM can better describe the following behavior at the microscopic level, which provides a basis for research related to connected and automated driving.http://dx.doi.org/10.1155/2024/6632473 |
| spellingShingle | Wenbo Wang Fei Hui Kaiwang Zhang Xiangmo Zhao Asad J. Khattak Time-Delay following Model for Connected and Automated Vehicles with Collision Conflicts and Forced Deceleration Journal of Advanced Transportation |
| title | Time-Delay following Model for Connected and Automated Vehicles with Collision Conflicts and Forced Deceleration |
| title_full | Time-Delay following Model for Connected and Automated Vehicles with Collision Conflicts and Forced Deceleration |
| title_fullStr | Time-Delay following Model for Connected and Automated Vehicles with Collision Conflicts and Forced Deceleration |
| title_full_unstemmed | Time-Delay following Model for Connected and Automated Vehicles with Collision Conflicts and Forced Deceleration |
| title_short | Time-Delay following Model for Connected and Automated Vehicles with Collision Conflicts and Forced Deceleration |
| title_sort | time delay following model for connected and automated vehicles with collision conflicts and forced deceleration |
| url | http://dx.doi.org/10.1155/2024/6632473 |
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