Self Synchronization of Moving Vehicles

Abstract

In this dissertation, we investigate and develop a novel scheduling scheme for conflict-free movement of vehicles at road intersections. We claim that our scheduling scheme not only guarantees conflict-free movement at any intersection, it also provides nonstop movement for the maximum possible number of vehicles at multiple intersections on its route. If it is not possible to provide a nonstop movement to a vehicle, the proposed scheme works to minimize the waiting time for each of the vehicles at an intersection. At present, traffic signals manage (synchronize) the conflict-free movement of vehicles on road intersections (common resource). These signals enforce the traffic rules to manage conflict-free movement of vehicles. Each side of traffic is allotted a stipulated time slot for crossing the intersection. The existing traffic signal scheme works well; however, it has a number of issues. These include the effect of changing traffic volume on traffic flow and indecisiveness of human drivers, etc., which can be eliminated by using state of the art technology. Motivated by the need of improving conflict-free traffic flow at road intersections, a large number of commercial and academic institutions have been taking a serious interest in solving some of these issues. One of the main approaches is to create a virtual environment so that information of traffic on an intersection can be transmitted to adjacent intersections in order to provide stoppage free movement of vehicles. In this dissertation, we investigate the traffic regulation problem from the point of view of “scheduling vehicle movement at road intersections”. We develop innovative scheduling schemes that require minimum human intervention in conflict-free traffic movement at intersections. This leads to the mechanism of self-synchronization of vehicles at these intersections in which conflicting vehicles mutually synchronize their movement using real-time contextual information. In self synchronization approach, vehicles that use the shared resources (intersections) communicate with each other and make a decision who will utilize the resource first based on a fair scheduling algorithm. To investigate and develop our fair scheduling algorithm, contextual information related to each of the vehicles must be exchanged among the vehicles in real-time. Existing communication protocols that are based on collision avoidance (of data packets) or collision detection and resolution may not work satisfactorily. The self-synchronization scheme generates a very dynamic, rapidly changing network of vehicles that requires a unique protocol for reliable real time data communication. So we have developed a new protocol for exchanging contextual information among vehicles.