Abstract

The determination of the traffic carrying capacity of road network is of great significance to the scale control of urban vehicles and the control of transportation systems. Existing related works have proposed calculation models and solutions for different application environments. However, these studies have problems such as diversification of capacity definitions, incorrect analysis of factors, and excessive model constraints. In response to these problems, this paper aims to determine the connotation of traffic carrying capacity and put forward a novel calculation model for carrying capacity. Firstly, in-depth analysis found that the key factor affecting the number of vehicles is the service level of road network. Then, the connotation of traffic carrying capacity is clarified, that is, the maximum number of vehicles travelling simultaneously in the road network under a certain service level. Second, based on the definition of carrying capacity and the characterization relationship between average travel speed and service level, the calculation of carrying capacity is transformed into the establishment of relationship between average travel speed and maximum number of vehicles. The construction of this relationship includes five steps, which are proposal of equivalent lane, division of traffic basic units, construction of basic unit travel time model, calculation of basic unit carrying capacity, and calculation of road network carrying capacity. In particular, the proposal of equivalent lane achieves the conversion from intermittent flow to continuous flow, and the abstraction of traffic flow further unifies the operation process into a unified mode of free travel and stacked release. Finally, the VISSIM simulation software is employed to verify and evaluate the proposed models. The results show that the average relative error between the simulated data and the calculated data obtained from the model is -0. 46%. Findings from this study will provide an innovative idea for the evaluation of urban road network performance. It can also provide a basis for urban managers to improve service level of road network and optimize the design of transportation system.

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