Flow dynamics of mixed traffic comprising connected autonomous vehicles and conventional vehicles
Flow dynamics of mixed traffic, comprising connected autonomous vehicles (CAVs) and human-driven vehicles (HDVs) were elucidated by focusing on the CAV penetration rate and communication performance. The mixed traffic flow was modeled using a deterministic cellular automaton (CA). Each CAV utilized...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-12-01
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| Series: | Cogent Engineering |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/23311916.2025.2536123 |
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| author | Yasushi Yokoya Akito Yamasaki Hitoshi Soma |
| author_facet | Yasushi Yokoya Akito Yamasaki Hitoshi Soma |
| author_sort | Yasushi Yokoya |
| collection | DOAJ |
| description | Flow dynamics of mixed traffic, comprising connected autonomous vehicles (CAVs) and human-driven vehicles (HDVs) were elucidated by focusing on the CAV penetration rate and communication performance. The mixed traffic flow was modeled using a deterministic cellular automaton (CA). Each CAV utilized its communication functionality to acquire real-time information on the driving conditions, such as velocity, position, from the multiple CAVs traveling within the communication range. The mutual CAV behavior was synchronized by information transmitted in real time. In contrast, each HDV traveled by only referring to the single vehicle traveling immediately ahead. Simulation results indicated that when the critical density is exceeded, the time evolutions of the average velocity and flow do not reach a steady state, causing unstable traffic flow. As the CAV penetration rate increases, the flow increases, but the traffic flow instability intensifies above the critical density. Moreover, an increasing CAV penetration rate enhances the flow by expanding the communication range; however, a threshold penetration rate exists. The enhancement of the traffic flow was not appreciable below the threshold even if the CAV communication range expanded. These results provide useful knowledge for future attempts to increase flows for mixed traffic flows, while avoiding instability. |
| format | Article |
| id | doaj-art-d7a23a7b814548e5abeeed87765ef0c0 |
| institution | Kabale University |
| issn | 2331-1916 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Cogent Engineering |
| spelling | doaj-art-d7a23a7b814548e5abeeed87765ef0c02025-08-20T03:55:49ZengTaylor & Francis GroupCogent Engineering2331-19162025-12-0112110.1080/23311916.2025.2536123Flow dynamics of mixed traffic comprising connected autonomous vehicles and conventional vehiclesYasushi Yokoya0Akito Yamasaki1Hitoshi Soma2Department of Vehicle and Mechanical Engineering, Faculty of Science and Technology, Meijo University, Nagoya, JapanDepartment of Vehicle and Mechanical Engineering, Faculty of Science and Technology, Meijo University, Nagoya, JapanDepartment of Vehicle and Mechanical Engineering, Faculty of Science and Technology, Meijo University, Nagoya, JapanFlow dynamics of mixed traffic, comprising connected autonomous vehicles (CAVs) and human-driven vehicles (HDVs) were elucidated by focusing on the CAV penetration rate and communication performance. The mixed traffic flow was modeled using a deterministic cellular automaton (CA). Each CAV utilized its communication functionality to acquire real-time information on the driving conditions, such as velocity, position, from the multiple CAVs traveling within the communication range. The mutual CAV behavior was synchronized by information transmitted in real time. In contrast, each HDV traveled by only referring to the single vehicle traveling immediately ahead. Simulation results indicated that when the critical density is exceeded, the time evolutions of the average velocity and flow do not reach a steady state, causing unstable traffic flow. As the CAV penetration rate increases, the flow increases, but the traffic flow instability intensifies above the critical density. Moreover, an increasing CAV penetration rate enhances the flow by expanding the communication range; however, a threshold penetration rate exists. The enhancement of the traffic flow was not appreciable below the threshold even if the CAV communication range expanded. These results provide useful knowledge for future attempts to increase flows for mixed traffic flows, while avoiding instability.https://www.tandfonline.com/doi/10.1080/23311916.2025.2536123Connected autonomous vehiclemixed traffic flowcommunication rangecellular automatonflow dynamicspenetration rate |
| spellingShingle | Yasushi Yokoya Akito Yamasaki Hitoshi Soma Flow dynamics of mixed traffic comprising connected autonomous vehicles and conventional vehicles Cogent Engineering Connected autonomous vehicle mixed traffic flow communication range cellular automaton flow dynamics penetration rate |
| title | Flow dynamics of mixed traffic comprising connected autonomous vehicles and conventional vehicles |
| title_full | Flow dynamics of mixed traffic comprising connected autonomous vehicles and conventional vehicles |
| title_fullStr | Flow dynamics of mixed traffic comprising connected autonomous vehicles and conventional vehicles |
| title_full_unstemmed | Flow dynamics of mixed traffic comprising connected autonomous vehicles and conventional vehicles |
| title_short | Flow dynamics of mixed traffic comprising connected autonomous vehicles and conventional vehicles |
| title_sort | flow dynamics of mixed traffic comprising connected autonomous vehicles and conventional vehicles |
| topic | Connected autonomous vehicle mixed traffic flow communication range cellular automaton flow dynamics penetration rate |
| url | https://www.tandfonline.com/doi/10.1080/23311916.2025.2536123 |
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