Abstract
In this thesis, we first propose an efficient and accurate protocol to detect congested road segments in a downtown area using VANETs. We refer to this protocol as the Efficient COngestion DEtection (ECODE) protocol. ECODE evaluates three different traffic characteristics of each road segment including traffic speed, traffic density, and the time required to travel the segment. In addition, we propose an intelligent, dynamic, distributed, and real-time path recommendations protocol. We refer to this protocol as Intelligent path reCOmenDation (ICOD) protocol. ICOD selects the path towards each destination in a hop-by-hop manner, which makes the turn decision at each road intersection more accurate and real-time. Different variants of ICOD are introduced that consider travel time, travel distance, fuel consumption, gas emissions, and context-awareness of each road segment parameters. Moreover, two traffic balancing mechanisms are proposed in this thesis to distribute traffic over the road network evenly, namely Bal-Traf and Abs-Bal. These mechanisms eliminate the highly congested road segment scenarios that are caused by the path recommendation protocol. Bal-Traf detects and eliminates the highly congested output road segment at each road intersection. However, Abs-Bal aims to keep the traffic density balanced among all output road segments at each road intersection. Finally, we propose an Intelligent Traffic Light Controlling (ITLC) algorithm to schedule the phases of each traffic light at isolated road intersections. This algorithm aims to decrease the queuing delay time of competing traffic flows and to increase the throughput of each signalized road intersection.
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