traffic_proj

Summary of Urban Traffic Signal Scheduling Project

Summary

In this project we will investigate how to improve traffic situations in a densely populated region by using intelligent traffic control with Vehicle-to-infrastructure (V2X) information technologies.

  • In the first stage of research, we aim to develop a distributed traffic-responsive scheduling architecture for urban traffic signal control, which consists of a set of local processing centres running in parallel that communicate with each other for neighboring traffic information to refine their own local traffic signals. It takes real-time traffic measurements via road sensors and/or V2X communication infrastructure, estimates vehicle driving patterns (such as speeds, turning ratios and link densities), and generates the corresponding green time schedule for each junction aiming for minimizing the network-wise total waiting time. To deal with traffic uncertainties, a model-predictive strategy will be adopted.

  • In the second stage, synthesized traffic-responsive traffic light schedules and the corresponding predicted link speeds are sent back to individual vehicles via V2X, which affect vehicles future route plans. Such updated route plans will be fed back to the traffic light control centers via V2X to enhance existing traffic light schedules.

  • Our ultimate goal is to form a closed loop between traffic light schedulers and traffic signal end users (i.e., vehicles), whose joint efforts will eventually lead to an intelligent and highly adaptive road traffic management system.

Project Objectives

  • Real-time traffic signal scheduling

    • Distributed architecture

    • Receding horizon strategy

  • Real-time model identification

    • Information collection via V2X

    • Machine learning for model validation

  • Holistic traffic signal scheduling

    • Traffic scheduler to drivers - route planning

    • Drivers to traffic scheduler - road usage

Research Topics

  • Heterogenerous Traffic System Modelling

  • Computational Intelligence for Solving Large Scale Traffic System

  • Pedestrain Movement Modelling

  • Real-time Route Planner

  • Simulation Platform Developmen