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

Ruru Xing, Fei Wang, Xiaoyu Cai (), Ning Chen, Tao Yang and Bo Peng
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Ruru Xing: College of Traffic & Transportation, Chongqing Jiaotong University, Chongqing 400074, China
Fei Wang: College of Traffic & Transportation, Chongqing Jiaotong University, Chongqing 400074, China
Xiaoyu Cai: College of Smart City, Chongqing Jiaotong University, Chongqing 400074, China
Ning Chen: College of Traffic & Transportation, Chongqing Jiaotong University, Chongqing 400074, China
Tao Yang: Chongqing Linggu Transportation Technology Co., Ltd., Chongqing 400064, China
Bo Peng: College of Smart City, Chongqing Jiaotong University, Chongqing 400074, China

Sustainability, 2023, vol. 15, issue 14, 1-27

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.

Keywords: cut-set method; mountain cities; regional road networks; road network capacity (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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