Current traffic management strategies are based on expected conditions caused by recurring congestion (e.g. by time of day, day of week), and can be very effective when provisions are also given for reasonable variations from such expectations. However, traffic variations due to non recurrent events (e.g. crashes) can be much larger and difficult to predict, making also challenging efforts to measure and forecast their disruptive effects. This project explores a proactive approach to manage non… Read More

Our research focused on understanding the travel behavior of individuals in complex urban environments. Specifically, we investigated how land use patterns and infrastructure influence how individuals across a broad range of travel abilities navigate through urban landscapes. Our overall project goal was to develop a transportation planning tool that allows users to simulate pedestrian travel behavior. The tool was built on a computation model that was developed through rigorous measures and… Read More