Abstract: Transportation systems are uncertain due to disruptions such as incidents and inclement weather. Real-time information, an integral element of smart cities, allows travelers to adapt to traffic conditions and potentially mitigate the adverse effects of uncertainty. Travelers create and suffer from congestion. The collective of all travelers' choices defines the traffic load and its distribution. Understanding the choices made by travelers in an uncertain and dynamic environment who have access to real-time traffic information is paramount to better system design, management, and policy making. I have conducted a series of empirical studies using data from both laboratory experiments and in-vehicle tracking and monitoring devices in real-life urban networks. In this talk, I will focus on the modeling and optimization of adaptive route choice based on GPS (Global Positioning System) data from Stockholm, Sweden. It is found that two types of travelers both exist: one adapts to real-time information, and the other does not. Travelers are more likely to adapt during longer trips. Results from laboratory experiment suggest that travelers learn to adapt at a slower pace in a more complex network. An ongoing project on route optimization for taxi drivers’ customer searching using GPS data from Shanghai, China will also be discussed.
Bio: Song Gao is an associate professor of Civil and Environmental Engineering at the University of Massachusetts Amherst. Dr. Gao’s research focuses on transportation network optimization, econometric and psychological models of traveler behavior, equilibrium analysis of transportation systems with traveler information, with applications in smart and shared mobility, transportation planning under both normal and emergency conditions, and sustainable transportation systems. Prior to joining the faculty of the University of Massachusetts Amherst in 2007, Dr. Gao worked as a transportation engineer at Caliper Corporation, Newton, MA for three years, and developed advanced traffic assignment modules for TransCAD, a GIS-based transportation planning software. Dr. Gao received her Ph.D. and M.S. in Transportation from Massachusetts Institute of Technology in 2005 and 2002 respectively. She received her B.S. in Civil Engineering from Tsinghua University of China in 1999.