Optimization and scheduling for a large scale urban transportation system in a fast-changing world

TL;DR

This paper presents innovative optimization and control strategies to enhance urban transportation systems, focusing on traffic light scheduling, dispatching operations, and integration of autonomous vehicles to improve efficiency and residents' quality of life.

Contribution

It introduces new optimization and control methods tailored for large-scale urban transport, including a traffic light scheduling strategy, a dispatching-operation system, and integration schemes for autonomous vehicles.

Findings

Traffic light scheduling reduces delays for pedestrians and vehicles.

Enhanced control flexibility improves dispatching and boarding operations.

Proposed integration schemes can potentially modernize public transport systems.

Abstract

This paper proposes a set of technological solutions to transform existing transport systems into more intelligent, interactive systems by utilizing optimization and control methods that can be implemented in the near future. This will result in improved public services and quality of life for residents. Three application scenes that are closely related to people's daily life are discussed. We first propose a traffic light scheduling strategy using a model predictive control (MPC) method, with the aim of fairly minimizing delays for both pedestrians and vehicles. Then, a combined dispatching-operation system is proposed to increase control flexibility, with a corresponding implementation solution for boarding control. Finally, a possible scheme to combine both public transport and autonomous vehicle systems is proposed to improve existing public transport systems.