In order to solve the traffic problem of mixed platoon of connected and autonomous vehicles and connected vehicles at intersection under the intelligent network environment, a traffic model was built based on Vehicle to Everything(V2X) real-time communication technology, mixed integer programming, branch and bound method. Meanwhile, a simulation system of mixed platoon at intersection under intelligent network environment was established using Simulation of Urban Mobility(SUMO) software for model verification. Taking one typical intersection as an example, the parameters such as average vehicle delay, average stop times and average energy consumption of the model and adaptive traffic signal control system were compared and analyzed. The results showed that under different penetration rates of connected and autonomous vehicles, the model could optimize the vehicle trajectory and signal timing according to the traffic flow conditions, and reduce the stop times by 90%~94%, vehicle delay by 20%~30%, and energy consumption by 10%~15% respectively; with the increasing of the penetration rate of autonomous vehicles, the influence of the acceptance probability of speed suggestions of networked vehicles was weakened, and the optimization effect of the model was increased.
刘天天，莫 磊，陈思祺，刘洪廷，张 钊，丁 川
. Construction of Traffic Model for Mixed Platoon at Intersection under Intelligent Network Environment[J]. Transport Research, 2020
, 6(6)
: 46
-54
.
DOI: 10.16503/j.cnki.2095-9931.2020.06.006
[1] Vazifeh M M, Santi P, Resta G, et al. Addressing the Minimum Fleet Problem in On-demand Urban Mobility[J]. Nature: International Weekly Journal of Science, 2018, 557(7706): 534-538.
[2] Shen Y, Zhang H M, Zhao J H. Integrating Shared Autonomous Vehicle in Public Transportation System: A Supply-side Simulation of the First-mile Service in Singapore[J]. Transportation Research Part A: Policy and Practice, 2018, 113: 125-136.
[3] Hawkins J, Habib K N. Integrated Models of Land Use and Transportation for the Autonomous Vehicle Revolution[J]. Transport Reviews, 2019, 39(1): 66-83.
[4] Hyland M, Mahmassani H S. Dynamic Autonomous Vehicle Fleet Operations: Optimization-based Strategies to Assign AVs to Immediate Traveler Demand Requests[J]. Transportation Research Part C: Emerging Technologies, 2018, 92: 278-297.
[5] Szilassy P, Németh B, Gáspár P. Design and Robustness Analysis of Autonomous Vehicles in Intersections[J]. IFAC PapersOnLine, 2019, 52(8): 321-326.
[6] Barthauer M, Friedrich B. Presorting and Presignaling: A New Intersection Operation Mode for Autonomous and Human-Operated Vehicles[J]. Transportation Research Procedia, 2019, 37: 179-186.
[7] Yang K D, Zheng N, Menendez M. Multi-scale Perimeter Control Approach in a Connected-vehicle Environment[J]. Transportation Research Procedia, 2017, 23: 101-120.
[8] Zhao W M, Ngoduy D, Shepherd S P, et al. A Platoon Based Cooperative Eco-driving Model for Mixed Automated and Human-driven Vehicles at a Signalised Intersection[J]. Transportation Research Part C: Emerging Technologies, 2018, 95: 802-821.
[9] Talebpour A, Mahmassani H S. Influence of Connected and Autonomous Vehicles on Traffic Flow Stability and Throughput[J]. Transportation Research Part C: Emerging Technologies, 2016, 71: 143-163.
[10] Feng Y H, Yu C H, Liu H X, et al. Spatiotemporal Intersection Control in a Connected and Automated Vehicle Environment[J]. Transportation Research Part C: Emerging Technologies, 2018, 89: 364-383.
[11] Yu C H, Feng Y H, Liu H X, et al. Integrated Optimization of Traffic Signals and Vehicle Trajectories at Isolated Urban Intersections[J]. Transportation Research Part B: Methodological, 2018, 112: 89-112.
[12] Yu C H, Sun W L, Liu H X, et al. Managing Connected and Automated Vehicles at Isolated Intersections: From Reservation-to Optimization-based Methods[J]. Transportation Research Part B: Methodological, 2019, 122: 416-435.
[13] Xu B, Ban X G, Bian Y G, et al. Cooperative Method of Traffic Signal Optimization and Speed Control of Connected Vehicles at Isolated Intersections[J]. IEEE Transactions on Intelligent Transportation Systems, 2018, 20(4): 1390-1403.
[14] Krau? S, Wagner P, Gawron C, et al. Metastable States in a Microscopic Model of Traffic Flow[J]. Physical Review E, 1997, 55(5): 5597-5602.
[15] Stebbins S, Hickman M, Kim J, et al. Characterising Green Light Optimal Speed Advisory Trajectories for Platoon-based Optimisation[J]. Transportation Research Part C: Emerging Technologies, 2017, 82: 43-62.
