Research Highlights

Network Effects of Disruptive Traffic Events

Juan Medina
Xiaoyue Cathy Liu
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 n... Read More

Vehicle Sensor Data (VSD) Based Traffic Control in Connected Automated Vehicle (CAV) Environment

Xianfeng (Terry) Yang
It can be expected that automated vehicles and human-driven vehicles will coexist in the transportation network for quite some time. In order to support various traffic control tasks it is critical to develop a reliable model to understand the real-time traffic patterns in this mixed environment. A new report from the National Institute for Transportation and Communities (NITC) contributes three new tools to help planners model freeway traffic with both connected automated vehicles (CAVs) and... Read More