Traffic flow optimization of different lane modesbased on autonomous vehicles(PDF)
长安大学学报（自然科学版）[ISSN:1006-6977/CN:61-1281/TN]
- Issue:
- 2021年1期
- Page:
- 103-115
- Research Field:
- 交通工程
- Publishing date:
Info
- Title:
- Traffic flow optimization of different lane modesbased on autonomous vehicles
- Author(s):
- ZHOU Zhaoming1; 2; 3; HUANG Zhongxiang3; YUAN jianbo3; LI pan2
- (1. Engineering Research Center of Catastrophic Prophylaxis and Treatment of Road & Traffic Safety ofMinistry of Education, Changsha University of Science & Technology, Changsha 410114, Hunan, China；2. School of Civil Engineering, Hunan City University, Yiyang 413000, Hunan, China; 3. School of Traffic andTransportation Engineering， Changsha University of Science & Technology， Changsha 410004, Hunan, China)
- Keywords:
- traffic engineering; mixed traffic flow optimization; method of successive averages; autonomous vehicle; market penetration; special lane
- PACS:
- -
- DOI:
- -
- Abstract:
- In order to research the operation mode of mixed traffic flow composed of different types of vehicles, it was assumed that autonomous vehicles, advanced traveler information systems (ATIS) device vehicles and ordinary driving vehicles respectively follow the system optimum mode, user equilibrium mode and stochastic user equilibrium mode to select the path. The traffic assignment models of ordinary lane and special lane were established respectively, and method of successive averages (MSA) algorithm was cooperated with the model. The calculation of road capacity, the influence of information quality level, travel demand and market penetration on travel time was analyzed through an example. On the basis of determining the parameters of the model, the mixed equilibrium flow state was researched according to the setting of the special lane, and the feasibility and convergence of the model algorithm were verified. The results show that with the increase of driving speed, the traffic capacity first increases and then decreases, choosing an appropriate driving speed will improve the road capacity, and the capacity of the autonomous lane will be significantly higher than that of the ordinary lane. Properly improving the level of information quality can reduce the randomness of route selection and effectively reduce the average travel time. With the increase of travel demand, the average travel time gradually increases, among which the average travel time of the system optimal mode (autonomous lane) is the smallest. According to the change of market penetration rate, choosing the appropriate lane configuration mode can not only improve the use efficiency of road resources, but also reduce the travel cost of travelers. The mixed traffic flow under different lane configuration modes gradually reaches a stable state with the increase of iteration times. When the market penetration rate of autonomous vehicles is high, the setting of autonomous driving lanes will shorten the driving time and improve the operating efficiency. 9 tabs, 11 figs, 26 refs.
Last Update: 2021-01-25