Improved Road-Network-Flow Control Strategy Based on Macroscopic Fundamental Diagrams and Queuing Length in Connected-Vehicle Network

Author:

Lin Xiaohui1ORCID,Xu Jianmin2,Lin Peiqun2ORCID,Cao Chengtao1,Liu Jiahui2

Affiliation:

1. Institute of Rail Traffic, Guangdong Communication Polytechnic, Guangzhou, China

2. School of Civil Engineering and Transportation, South China University of Technology, Guangzhou, China

Abstract

Connected-vehicles network provides opportunities and conditions for improving traffic signal control, and macroscopic fundamental diagrams (MFD) can control the road network at the macrolevel effectively. This paper integrated proposed real-time access to the number of mobile vehicles and the maximum road queuing length in the Connected-vehicles network. Moreover, when implementing a simple control strategy to limit the boundary flow of a road network based on MFD, we determined whether the maximum queuing length of each boundary section exceeds the road-safety queuing length in real-time calculations and timely adjusted the road-network influx rate to avoid the overflow phenomenon in the boundary section. We established a road-network microtraffic simulation model in VISSIM software taking a district as the experimental area, determined MFD of the region based on the number of mobile vehicles, and weighted traffic volume of the road network. When the road network was tending to saturate, we implemented a simple control strategy and our algorithm limits the boundary flow. Finally, we compared the traffic signal control indicators with three strategies: (1) no control strategy, (2) boundary control, and (3) boundary control with limiting queue strategy. The results show that our proposed algorithm is better than the other two.

Funder

Guangdong Province Science and Technology Development Special Funds

Publisher

Hindawi Limited

Subject

General Engineering,General Mathematics

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Research of heterogeneous traffic control with intelligent connected vehicles and human drive vehicles;Seventh International Conference on Electromechanical Control Technology and Transportation (ICECTT 2022);2022-11-23

2. Traffic Signal Optimization under Connected-Vehicle Environment: An Overview;Journal of Advanced Transportation;2021-08-10

3. Research of Wireless Congestion Control Algorithm Based on EKF;Symmetry;2020-04-17

4. Real-Time Dynamic Traffic Control Based on Traffic-State Estimation;Transportation Research Record: Journal of the Transportation Research Board;2019-04-04

5. A Real-Time Queue Length Estimation Method Based on Probe Vehicles in CV Environment;IEEE Access;2019

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