TITLE:</B> CONTROL AND OPTIMIZATION METHODS FOR PROBLEMS IN INTELLIGENT TRANSPORTATION SYSTEMS
ABSTRACT: This prospectus aims to address three research topics in intelligent transportation systems which include multi-intersection traffic light control based on stochastic flow models with delays and blocking, optimization of ride sharing systems using eventdriven
receding horizon control and some ongoing work for the optimal control of lane change maneuvers in highways for
Connected and Automated Vehicles.
First, for the traffic light control work, we extend Stochastic Flow Models (SFMs), used for a large class of discrete event and
hybrid systems, by including the delays which typically arise in flow movements, as well as blocking effects due to space
constraints. We apply this framework to the multi-intersection traffic light control problem by including transit delays for vehicles moving from one intersection to the next and possible blocking between two intersections. Using Infinitesimal Perturbation Analysis (IPA) for this SFM with delays and possible blocking, we derive new on-line gradient estimates of several congestion cost metrics with respect to the controllable green and red cycle lengths. The IPA estimators are used to iteratively adjust light cycle lengths to improve performance and, in conjunction with a standard gradient-based algorithm, to obtain optimal values which adapt to changing traffic conditions.
The second problem relates to a Ride Sharing System (RSS) in which passengers can be delivered to the associated destinations from their origins by shared vehicles. Using a method based on Receding Horizon Control (RHC) which is event-driven, we reduce (ideally, optimize) the waiting and traveling times of passengers in this RSS.
Finally, we address the problem of automatically and optimally controlling lane change maneuvers in highways in which the target vehicle cooperates with other autonomous vehicles to complete a lane change maneuver. We aim at optimizing the maneuver time and presenting an optimal control framework to minimize the associated energy consumption for all controllable vehicles over this process.
COMMITTEE: ADVISOR/CHAIR Christos Cassandras, SE/ECE; Ioannis Paschalidis, SE/ECE; Sean Anderssonz,SE/ME; Pirooz Vakili,SE/ME |
