No abstract

No abstract

No abstract

In large and highly populated downtown areas, traffic congestion is becoming a challenging problem. This work proposes an Efficient road COngestion DEtection protocol (ECODE). This protocol intends to detect road segments that are suffering high traffic congestion using cooperative vehicular communication. It uses multi-hop communication and geocast principles to gather and analyze vehicles' basic data per road segment. Each vehicle can evaluate and report its road segment's congestion level per direction efficiently. This protocol is discussed and reported on its performance compared to previous techniques in this field, using an extensive set of scenarios and experiments implemented on NS-2.

Traffic signals are essential to guarantee safe driving at road intersections. However, they disturb and reduce the traffic fluency due to the queue delay at each traffic flow. In this work, we introduce an Intelligent Traffic Light Controlling (ITLC) algorithm. This algorithm considers the real-time traffic characteristics of each traffic flow that intends to cross the road intersection of interest, whilst scheduling the time phases of each traffic light. The introduced algorithm aims at increasing the traffic fluency by decreasing the waiting time of traveling vehicles at the signalized road intersections. Moreover, it aims to increase the number of vehicles crossing the road intersection per second. We report on the performance of ITLC and we compare ITLC to previous algorithms in this field for different simulated scenarios. From the experimental results, we infer that ITLC reduces the queuing delay and increases the traffic fluency by 25% compared to previous traffic light signal schedules. Furthermore, ITLC increases the throughput of each signalized road intersection by 30%.