A novel pedestrian road crossing simulator for dynamic traffic light scheduling systems

TL;DR

This paper introduces a detailed pedestrian crossing simulator that improves traffic light scheduling by accurately modeling pedestrian behavior, aiming to enhance pedestrian experience while maintaining traffic flow efficiency.

Contribution

The paper presents a novel pedestrian simulation environment for signalized crossings, enabling optimized traffic light control considering pedestrian comfort and large group behaviors.

Findings

Achieves 98.37% accuracy in crossing time estimation.

Enables traffic light schedules that reduce pedestrian waiting times.

Maintains vehicular throughput during optimized scheduling.

Abstract

The major advances in intelligent transportation systems are pushing societal services toward autonomy where road management is to be more agile in order to cope with changes and continue to yield optimal performance. However, the pedestrian experience is not sufficiently considered. Particularly, signalized intersections are expected to be popular if not dominant in urban settings where pedestrian density is high. This paper presents the design of a novel environment for simulating human motion on signalized crosswalks at a fine-grained level. Such a simulation not only captures typical behavior, but also handles cases where large pedestrian groups cross from both directions. The proposed simulator is instrumental for optimized road configuration management where the pedestrians' quality of experience, for example, waiting time, is factored in. The validation results using field data show that an accuracy of 98.37 percent can be obtained for the estimated crossing time. Other results using synthetic data show that our simulator enables optimized traffic light scheduling that diminishes pedestrians' waiting time without sacrificing vehicular throughput.