Analysis of Traffic Oversaturation Based on Multi-Objective Data

Abstract

With the increase in people’s travel demands, the air pollution generated by the means of transportation they take is also becoming more and more serious. Among them, in the process of people’s travel, the exhaust pollution caused by traffic congestion is particularly serious. Accurately identifying various regimes of oversaturation and taking effective control strategies play a key role in alleviating traffic congestion. There are three regimes of evolution during an oversaturated scenario: loading, oversaturated operation, and recovery. In the traffic signal control under the oversaturated scenario, the corresponding control targets and methods should be adopted based on the regime of oversaturation. In this paper, the multi-objective attributes and their trajectory data of each movement at the intersection are analyzed. Based on the oversaturation severity index, the traffic volume, and the queuing on the movement, the identification and cause analysis of each regime of the oversaturation are carried out. The examples and simulation results proved that the method proposed in this paper could effectively analyze the cause and degree of oversaturation and identify its regime. This has important implications for alleviating traffic congestion and reducing vehicle carbon emissions.