Urban traffic from the perspective of dual graph

TL;DR

This paper models urban traffic using a dual graph approach, representing roads as nodes and intersections as links, to analyze system capacity and congestion based on network topology.

Contribution

It introduces a dual graph model for urban traffic that incorporates vehicle navigation, road capacity, and intersection turning, providing a new perspective on traffic flow analysis.

Findings

System capacity depends on network topology.

Grid networks have higher capacity than scale-free networks.

Phase transition from free flow to congestion identified.

Abstract

In this paper, urban traffic is modeled using dual graph representation of urban transportation network where roads are mapped to nodes and intersections are mapped to links. The proposed model considers both the navigation of vehicles on the network and the motion of vehicles along roads. The road's capacity and the vehicle-turning ability at intersections are naturally incorporated in the model. The overall capacity of the system can be quantified by a phase transition from free flow to congestion. Simulation results show that the system's capacity depends greatly on the topology of transportation networks. In general, a well-planned grid can hold more vehicles and its overall capacity is much larger than that of a growing scale-free network.