An Asymmetric-Anticipation Car-following Model in the Era of Autonomous-Connected and Human-Driving Vehicles
Herein, we explored the impact of anticipation and asymmetric driving behavior on vehicle’s position, velocity, acceleration, energy consumption, and exhaust emissions of CO, HC, and NOx in mixed traffic flow. We present an asymmetric-anticipation car-following model (AAFVD) considering the motion i...
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2020/8865814 |
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| author | Ammar Jafaripournimchahi Wusheng Hu Lu Sun |
| author_facet | Ammar Jafaripournimchahi Wusheng Hu Lu Sun |
| author_sort | Ammar Jafaripournimchahi |
| collection | DOAJ |
| description | Herein, we explored the impact of anticipation and asymmetric driving behavior on vehicle’s position, velocity, acceleration, energy consumption, and exhaust emissions of CO, HC, and NOx in mixed traffic flow. We present an asymmetric-anticipation car-following model (AAFVD) considering the motion information from two direct preceding vehicles (i.e., human-driving (HD) and autonomous and connected (AC) vehicles platoon) via wireless data transmission. The linear stability approach was used to evaluate the properties of the AAFVD model. Our simulations revealed that the drivers’ anticipation factor using the motion information from two direct preceding vehicles in connected vehicles environment can effectively improve traffic flow stability. The vehicle’s departure and arrival process while passing through a signal lane with a traffic light considering the anticipation and asymmetric driving behavior, and the motion information from two direct preceding vehicles was explored. Our numerical results demonstrated that the AAFVD model can decrease the velocity fluctuations, energy consumption, and exhaust emissions of vehicles in mixed traffic flow system. |
| format | Article |
| id | doaj-art-6b7d5c2602ef4ababd885eb6a385e83b |
| institution | Kabale University |
| issn | 0197-6729 2042-3195 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-6b7d5c2602ef4ababd885eb6a385e83b2025-02-03T01:04:03ZengWileyJournal of Advanced Transportation0197-67292042-31952020-01-01202010.1155/2020/88658148865814An Asymmetric-Anticipation Car-following Model in the Era of Autonomous-Connected and Human-Driving VehiclesAmmar Jafaripournimchahi0Wusheng Hu1Lu Sun2School of Transportation Engineering, Southeast University, Nanjing 210096, ChinaSchool of Transportation Engineering, Southeast University, Nanjing 210096, ChinaDepartment of Civil and Environmental Engineering, University of Maryland, College Park, MD, USAHerein, we explored the impact of anticipation and asymmetric driving behavior on vehicle’s position, velocity, acceleration, energy consumption, and exhaust emissions of CO, HC, and NOx in mixed traffic flow. We present an asymmetric-anticipation car-following model (AAFVD) considering the motion information from two direct preceding vehicles (i.e., human-driving (HD) and autonomous and connected (AC) vehicles platoon) via wireless data transmission. The linear stability approach was used to evaluate the properties of the AAFVD model. Our simulations revealed that the drivers’ anticipation factor using the motion information from two direct preceding vehicles in connected vehicles environment can effectively improve traffic flow stability. The vehicle’s departure and arrival process while passing through a signal lane with a traffic light considering the anticipation and asymmetric driving behavior, and the motion information from two direct preceding vehicles was explored. Our numerical results demonstrated that the AAFVD model can decrease the velocity fluctuations, energy consumption, and exhaust emissions of vehicles in mixed traffic flow system.http://dx.doi.org/10.1155/2020/8865814 |
| spellingShingle | Ammar Jafaripournimchahi Wusheng Hu Lu Sun An Asymmetric-Anticipation Car-following Model in the Era of Autonomous-Connected and Human-Driving Vehicles Journal of Advanced Transportation |
| title | An Asymmetric-Anticipation Car-following Model in the Era of Autonomous-Connected and Human-Driving Vehicles |
| title_full | An Asymmetric-Anticipation Car-following Model in the Era of Autonomous-Connected and Human-Driving Vehicles |
| title_fullStr | An Asymmetric-Anticipation Car-following Model in the Era of Autonomous-Connected and Human-Driving Vehicles |
| title_full_unstemmed | An Asymmetric-Anticipation Car-following Model in the Era of Autonomous-Connected and Human-Driving Vehicles |
| title_short | An Asymmetric-Anticipation Car-following Model in the Era of Autonomous-Connected and Human-Driving Vehicles |
| title_sort | asymmetric anticipation car following model in the era of autonomous connected and human driving vehicles |
| url | http://dx.doi.org/10.1155/2020/8865814 |
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