A Decision Support System for Evaluating the Impacts of Routing Applications on Urban Mobility

The rise of congestion across the United States and the increasing adoption of mobile routing services have enabled drivers with the ability to find the fastest routes available in urban road networks. Arterial roads and side streets originally designed for local traffic are impacted by the influx of selfishly routed drivers, garnering much recent media attention and civic debate. Classic flow-based game theoretic models provide the framework for simulating the behavior of routed and non-routed drivers on a road network. We developed an interactive policy decision support system called the Routing Impact Detection, Evaluation, and Response Decision Support System (RIDER DSS) as a tool for policymakers and practitioners to hone in on areas most impacted by routing apps and assess potential policy actions to mitigate the effects of cut-through traffic on a local and regional scale. In a case study of Baxter Street in the Los Angeles Basin we demonstrate how the RIDER DSS can relate the percentage of app users in a network to the distribution of traffic flow on side streets.