Road Charging, Complex Transport Policies, and Agent-Based Models
ABMs allow deep analysis of transport systems, leading to better, more equitable, and more reliable outcomes
Arup’s Global Cities, Planning and Design (CPD) Leader, Richard de Cani, wrote an article on Arup.com about the London Congestion Charge (that recently celebrated its 20th birthday) based on his experiences working for TfL.
Agent-Based Models vastly outperform traditional models when it comes to understanding the impacts of road charging, allowing deep analysis from the aggregate level all the way down to the level of each individual person traversing the transport network. Indeed, one of our long-term projects involves using an ABM to understand how road charging impacts different groups of people
Although we in the City Modelling lab love to delve into the technical details of ABMs, we also understand the importance of starting from policy and then figuring out how models support developing sustainable and equitable policy options — rather than thinking about modelling for its own sake.
To set out this approach, I’ve written an Arup Perspective entitled “Modelling the future: how people can drive better city development” to set out why we think ABMs can enable much better policymaking.
