Lane-changing decision model of connected and automated vehicles driving off ramp

被引：0
|
作者：
Hao W. [1 ]
Zhang Z.-L. [1 ]
Wu Q.-Y. [1 ]
Yi K.-F. [1 ]
机构：
[1] Hunan Key Laboratory of Smart Roadway and Cooperative Vehicle-Infrastructure Systems, Changsha University of Science and Technology, Hunan, Changsha
来源：
Jiaotong Yunshu Gongcheng Xuebao/Journal of Traffic and Transportation Engineering | 2023年 / 23卷 / 05期
关键词：
CAV; CAV penetration rate; cost function; lane-changing decision model; mixed traffic flow; numerical simulation;
D O I：
10.19818/j.cnki.1671-1637.2023.05.017
中图分类号：
学科分类号：
摘要：
A safety risk-based lane-changing decision model of connected and automated vehicles (CAVs) driving off the ramp in mixed traffic flow was proposed to macroscopically characterize the behaviors of CAVs driving off the ramp in the CAV lane. The model abstracted the lane-changing gap selection process into Bernoulli experiments of successful or unsuccessful lane-changing, and a lane-changing success rate formula was set up based on the traffic flow theory. A driving off ramp lane-changing decision cost function considering lane-changing safety and efficiency was proposed, in which the weight parameters of safety and efficiency were determined based on different driving modes, so as to determined the optimal lane-changing intention generation point for CAVs and provided instructions for CAV lane-changing. Numerical analysis results show that the success rate of CAV driving off the ramp is determined by the preparation distance of lane-changing, traffic demand, and CAV penetration rate. The cost function has an obvious inflection point with the change of CAV penetration rate. When the traffic volume is 2 400 veh·h-1, the optimal lane-changing intention generation point for CAVs is 1 km away from the entrance of the off-ramp. When the traffic volume increases to 4 000 veh·h-1, the optimal lane-changing intention generation point is 2.5 km away from the entrance of the off-ramp. When the traffic volume is greater than 6 400 veh·h-1, the CAV needs to increase aggressiveness to drive off the highway efficiently. The cost function first decreases and then increases as the CAV penetration rate increases. If the penetration rate is lower than the inflection point penetration rate, the cost function can be reduced by increasing the preparation distance of lane-changing. If the penetration rate is higher than the inflection point penetration rate, reducing the preparation distance of lane-changing is necessary to reduce the cost function. Simulated results show that the traffic safety of driving off the ramp significantly influenced by the traffic demand and CAV penetration rate. The time-to-collision reduces to 76.23%, with the penetration rate increasing from 30% to 60%. 2 tabs, 8 figs, 31 refs. © 2023 Chang'an University. All rights reserved.
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页码：242 / 252
页数：10
相关论文
共 31 条
  • [1] QIU Xiao-ping, MA Li-na, ZHOU Xiao-xia, Et al., The mixed traffic flow of manual-automated driving based on safety distance, Journal of Transportation Systems Engineering and Information Technology, 16, 4, pp. 101-108, (2016)
  • [2] MOHAMED A A, WU Y N, MOATZ S., Safety and operational impact of connected vehicles' lane configuration on freeway facilities with managed lanes, Accident Analysis and Prevention, 144, (2020)
  • [3] CHANG Xin, LI Hai-jian, RONG Jian, Et al., Analysis on traffic stability and capacity for mixed traffic flow with platoons of intelligent connected vehicles, Physica A: Statistical Mechanics and Its Applications, 557, (2020)
  • [4] WU Bing, WANG Wen-xuan, LI Lin-bo, Et al., Longitudinal control model for connected autonomous vehicles influenced by multiple preceding vehicles, Journal of Traffic and Transportation Engineering, 20, 2, pp. 184-194, (2020)
  • [5] CHANG Xin, LI Hai-jian, RONG Jian, Et al., Analysis of capacity for mixed traffic flow with connected vehicle platoon on freeway, Journal of South China University of Technology (Natural Science Edition), 48, 4, pp. 142-148, (2020)
  • [6] VANDER L Z, SADABADI K F., Operational performance of a congested corridor with lanes dedicated to autonomous vehicle traffic, International Journal of Transportation Science and Technology, 6, 1, pp. 42-52, (2017)
  • [7] XIAO L, WANG M, VAN AREM B., Traffic flow impacts of converting an HOV lane into a dedicated CACC lane on a freeway corridor, IEEE Intelligent Transportation Systems Magazine, 12, 1, pp. 60-73, (2020)
  • [8] LI T, GUO F, KRISHNAN R, Et al., Right-of-way reallocation for mixed flow of autonomous vehicles and human driven vehicles, Transportation Research Part C: Emerging Technologies, 115, (2020)
  • [9] ZHONG Z J, LEE J., Dedicated lane for connected and automated vehicle: how much does a homogeneous traffic flow contribute?
  • [10] WEI Xiu-jian, HU Rong-xin, SU Hang, Et al., Mixed traffic flow game model and simulation of automatic and manual driving vehicle in two-lane condition, Systems Engineering, 36, 11, pp. 97-104, (2018)
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