Effects of Prediction Feedback in Multi-Route Intelligent Traffic Systems

TL;DR

This paper investigates the impact of a prediction feedback strategy (PFS) on traffic flow in multi-route systems, demonstrating its efficiency in managing traffic distribution through cellular automaton simulations.

Contribution

The study introduces and evaluates a prediction feedback strategy (PFS) for multi-route traffic systems, incorporating adaptability into cellular automaton models and comparing its effectiveness with other strategies.

Findings

PFS outperforms other feedback strategies in controlling traffic distribution.

Simulation results show high efficiency of PFS in traffic management.

Discussion on conditions where PFS may become invalid.

Abstract

We first study the influence of an efficient feedback strategy named prediction feedback strategy (PFS) based on a multi-route scenario in which dynamic information can be generated and displayed on the board to guide road users to make a choice. In this scenario, our model incorporates the effects of adaptability into the cellular automaton models of traffic flow. Simulation results adopting this optimal information feedback strategy have demonstrated high efficiency in controlling spatial distribution of traffic patterns compared with the other three information feedback strategies, i.e., vehicle number and flux. At the end of this paper, we also discuss in what situation PFS will become invalid in multi-route systems.