Congestion Risk Propagation Model Based on Multi-Layer Time-Varying Network
Jincai Huang, Mu Sun, Qu Cheng · International Journal of Simulation Modelling · 2021
To quantify the responses of drivers to traffic information and the congestion evacuation effect on the basis of traffic guidance information, a multilayer network congestion risk propagation model of urban roads was built to analyse the influence of the advanced traveller information system (ATIS) penetration rate, group behaviours of drivers, and traveller flow distribution features on the traffic congestion risk propagation of urban roads.Meanwhile, the dynamic evolutionary characteristics of group behaviours of drivers in a road network under the guidance of traffic information were analysed with the microscopic Markov chain approach (MMCA).A simulation analysis of the artery network in the fourth ring of Beijing was also carried out.Results demonstrated that the influence of traffic information and drivers' information reinforcement psychology on congestion risk propagation depend on the aggregation effect caused by traffic information.Increasing the ATIS market penetration rate and drivers' acceptance of information is beneficial to relieve traffic congestion as long as the drivers' aggregation effect is within a critical range.