Cyrille Genre-Grandpierre

Towards New Metrics for Urban Road Networks: Some Preliminary Evidence from Agent-Based Simulations

Road networks are complex entities, which are arranged hierarchically both in their structure (topology) and by speed. This property has a strong influence on their performance, both at an individual and collective level. Indeed, they intrinsically favour car use, especially for distant trips. In that sense, they may contribute actively to urban sprawl, a non desirable property of urban growth. In this chapter, we propose and explore a strategy aimed at regulating and even reversing such a “speed metric”. Using agents, we simulate road traffic on various road network structures and show how limited but well targeted actions can have a strong global impact on the system.

New Types of Metrics for Urban Road Networks Explored with S3: An Agent-Based Simulation Platform

The metric of the current road networks tends intrinsically to favour the efficacy of the routes which have the longer range, what leads to promote urban sprawl and automobile dependence. Indeed this metric ensures to individuals the possibility to travel even further, without necessarily increasing their transportation time in the same proportions. According to this assessment, we introduce a new kind of metric, the “slow metric”, which amounts to invert the current ratios of efficacy between the different types of automobile travels, i.e. to favour the efficacy of the short range travels. This metric is reached thanks to traffic lights, under constraints regarding their location and duration. The calibration of the slow metric (number, duration and location of the traffic lights for different networks structures), its impact on traffic (fluidity versus congestion) and conversely the impact of traffic interactions on the slow metric, are simulated and evaluated with S3 which is an agent-based simulation platform.