The intelligent Urban Transportation Systems (iUTS) Lab focuses on the Monitoring, Mining, Modeling, and Managing (4M) of the Urban Transportation Systems (UTS).
- Monitoring: In the era of new sensing/monitoring/communication technologies, emerging vehicle technologies (Connected/Autonomous Vehicles), and Big Data Analytics, what data
to collect and how to use them for UTS pose both exciting opportunities and significant challenges. This is particular so when data related critical issues are considered, such as privacy/security and data biases.
- Mining: Learn from the data on how new technologies may better reveal or even transform the fundamental behaviors and interactions of UTS components including vehicles, drivers, passenger, and other key players such as policy makers and the industry sector (e.g., your employers may have more say about your work schedule and thus the departure time of your commuting trip).
- Modeling: Answer key modeling questions such as:
- How to estimate/predict UTS performances (travel times, emissions, etc.), pay particular attention to the possible behavior changes of system components;
- How to estimate/predict human travel patterns in a city or a region, while recognizing that the data might be biased or limited by privacy protection;
- How to integrate/ model the behaviors/interactions of system components on a multimodal transportation network?
- Management: Based on UTS modeling and predictions, develop system-wide strategies (traffic control, guidance, pricing/tolling, incentives, among others) to effectively/efficiently manage urban multimodal dynamic network systems.