CEE Seminar (ZOOM): An Artificial Neural Network-based Model for Real-time Dispatching of Electric Autonomous Taxis

Abstract: This talk discusses a real-time dispatching model for electric autonomous vehicle (EAV) taxis that combines mathematical programming and machine learning. The EAV taxi dispatching problem is formulated and solved as an integer linear program that maximizes the total reward for serving customers. The optimal dispatch solutions are generated by simulating electric autonomous taxis that are dispatched by the optimization model. The artificial neural network(ANN)-based model was trained using the optimization model’s dispatch solutions to learn the optimal dispatch strategies. Although the dispatch decisions made by the ANN-based model are not optimal, the system’s performance is very close to the optimization dispatch model in terms of customer service and taxis’ operational efficiency. In addition, the ANN-based dispatch model runs much faster. When comparing to current taxis, it was found that the EAV taxis dispatched by our ANN-based model can improve operational efficiency by reducing empty travel distance. EAV taxis can also reduce fleet size by 15% while maintaining a comparable level of service with the current taxi fleet.

Bio: Jing Dong is an associate professor of transportation engineering in the Department of Civil, Construction and Environmental Engineering at Iowa State University (ISU). She also is a transportation engineer for the Center for Transportation Research and Education at ISU’s Institute for Transportation. Before joining ISU, she worked at Oak Ridge National Laboratory as a research staff member from 2010 to 2012. Dong’s primary research interests include transportation planning, traffic operations and network modeling. Her research is focused on improving the mobility, safety and environmental sustainability of multimodal transportation systems. Dong is a member of the Transportation Research Board Committee on Traffic Flow Theory and Characteristics and Transportation Network Modeling. She is also a senior member of IEEE.