Centralised Urban Traffic Routing Using Mixed-Integer Programming

Abstract

The increase in the urban population over the past decades led to an increase in the number of vehicles in urban road networks, especially in larger metropolitan areas. The problem is exacerbated during rush hours and when an unexpected or rare event occurs (e.g. accidents, concerts). Existing traffic routing methods, including those embedded in modern navigation systems, consider Dynamic User Optimal (DUO) traffic routing that generates routes in a decentralised fashion. Centralized traffic routing, which we consider in this paper, benefits from the global perspective of the situation that can utilise the road network more effectively. We propose a technique leveraging Mixed-Integer Programming (MIP) for distributing vehicles in the road network while minimizing traffic intensity on road segments. Our evaluation shows the potential of the proposed technique for centralized traffic routing.