Traffic flow brake light model simulation based on driver behavior learning

TL;DR

This paper introduces an improved traffic flow brake light model that better simulates driver behavior and stabilizes congestion wave propagation, addressing limitations of previous models.

Contribution

The paper proposes a new brake light traffic model incorporating driver behavior parameters to improve realism and stability of congestion wave simulation.

Findings

Enhanced model stabilizes congestion wave speed

Adjustable parameters simulate driver behavior

More realistic traffic flow simulation

Abstract

The theory of urban traffic flow has been developed and new types of meta-automata have emerged and simulate realistic traffic conditions relatively well. Among these models, the brake light model can simulate the three-phase traffic flow theory very well. However, the existing brake light model also has certain shortcomings, in that the model will change the speed of congestion propagation upward when the model is covariant, which is not realistic, and the model also lacks simulation parameters for driver behavior. In this paper, we propose a new model based on the brake light model, which can achieve a certain degree of simulation of driver behavior by adjusting the parameters, and also achieve a stabilization of the propagation speed of the congestion wave when the parameters are changed.