Understanding mobility patterns and decision-making using an integrated, multi-modal sensing platform in a quantified community

Overview City governments all over the world face challenges understanding mobility patterns within dense urban environments at high spatial and temporal resolution. While such measures are important to provide insights into the functional patterns of a city, novel quantitative methods, derived from ubiquitous mobile connectivity, are needed to provide decision-makers better insights to improve urban…

Integrative Vehicle-Traffic Control in Connected/Automated Cities

Research Objective The researchers plan to investigate the critical issues involved in traffic control at intersections with CAVs in connected/automated cities. In particular, the team aims to achieve the following objectives: Develop methods to deal with mixed traffic flow, i.e. human-driven vehicles mixed with CAVs Develop CAV-based signal coordination methods with multiple signalized intersections Test/validate…