A Regional Road Network Capacity Estimation Model for Mountainous Cities Based on Auxiliary Map

Author:

Xing Ruru1,Wang Fei1,Cai Xiaoyu2,Chen Ning1,Yang Tao3,Peng Bo2

Affiliation:

1. College of Traffic & Transportation, Chongqing Jiaotong University, Chongqing 400074, China

2. College of Smart City, Chongqing Jiaotong University, Chongqing 400074, China

3. Chongqing Linggu Transportation Technology Co., Ltd., Chongqing 400064, China

Abstract

The focus of sustainable urban transportation development lies in realizing the untapped capacity potential of the existing road network and enhancing its operational efficiency without expanding its physical footprint. To quantify the supply capacity of road networks in mountainous cities, this paper converts the problem of solving the capacity of road networks into the problem of solving the minimum cut set in road networks from the perspective of road network capacity, using the idea of the auxiliary diagram method in graph theory. By improving the limitation that the auxiliary map method is only applicable to the single starting point and terminal point network, a regional road network capacity estimation model of a mountain city based on the auxiliary map is constructed. Combined with the actual regional road network, the model results presented in this paper show that the road network capacity calculated by the auxiliary graph method is 30,137 pcu/h. Using the improved traffic distribution simulation method, the network capacity is 38,776 pcu/h. Compared with the traffic distribution simulation method, the regional road network capacity model based on an auxiliary map proposed in this paper is more realistic.

Funder

Young Scientists Fund of the National Natural Science Foundation of China

the Science and Technology Research Program of the Chongqing Municipal Education Commission

Publisher

MDPI AG

Subject

Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development,Building and Construction

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