Traffic Flow Assignment Method Considering Travelers' Different Rational Degree Under Congestions

To investigate the influence of traveler' perceptual preference on traffic assignment results, this paper proposes a microscopic route selection model and a traffic assignment algorithm constrained by road capacity under congested conditions. Travelers' regret and indifference threshold are introduced into the decision-making process. The route selection probability model under different rational degree is developedin consideration of the psychological perception difference of normal travel time and queuing time. At the aggregate level, the inflow and outflow correction method is proposed based on the capacity limitation of the current road and its upstream and downstream sections, as well as the space queue and overflow of vehicles. The incremental traffic loading assignment method is adopted to study vehicles' dissipation characteristics, and the evolution process from individual route decisions to macroscopic road network states is reproduced. Based on the Nguyen-Dupuis simulation network, the traffic congestion and inflow-outflow are compared using different algorithms. The results show that travelers' personal preference perception significantly affect the cost function of congested road sections, but has minimum impact on vehicles' inflow and outflow in non-congested sections. The bounded rationality traffic assignment method considering individual preferences can reduce the average saturation of the road network. The proposed traffic assignment method can be applied to the traffic guidance of the congested road network, which is beneficial to the rational utilization of road resources. © 2023 Science Press. All rights reserved.