Book Description

This dissertation aims to study effective and efficient ways for both travelers and transportation authorities to consider the actions of the other side when they make their corresponding travel or management decisions, such that certain common goals, such as mitigating congestion, reducing cost in travel expenses and improving the overall reliability of the transportation system can be achieved. A novel dynamic traffic routing (DTR) with an adaptive signal control framework is developed to utilize the fast developing wireless communication technologies that makes V2X (Vehicle To Everything) possible. The hyper-path based dynamic traffic routing method takes stochasticity of link travel time into consideration, which ensures robust and reliable routing decisions. In addition, online travel time updating is incorporated into the DTR model. The online updating presented in this dissertation uses both historical information (a priori knowledge) and new information, thanks to the V2X system, to form a posteriori knowledge about the link travel time. Various distributed traffic signal control methods are proposed and tested with the DTR model to cope with the different levels of the traffic demand. The joint dynamic traffic routing and adaptive signal control model developed in this dissertation performs well in most cases. However, the underlying logic of DTR does not guarantee to prevent deadlock from happening. To address this issue, following the study of dynamic traffic routing and adaptive signal control, I formulate a deadlock avoidance model under dynamic user equilibrium with queue spillback. In the proposed model, travelers' route choice is governed by a simple "DLA (DeadLock Avoidance) Routing" rule which is proved to generate deadlock free routing result. Potential deadlocks during the optimization of the model are detected with an algorithm modified based on Floyd Warshall Algorithm. The algorithm then assigns a deadlock potential value to each potential deadlock. The model minimizes this potential, and meanwhile tries to maintain the total travel time in the network at a reasonably low level. Many transportation applications can potentially take advantage of the research results in this dissertation. We explored one interesting and important application scenario-the parking search problem in the final chapter of this dissertation.