Self routing traffic light for traffic light controller using priority method based on volume of vehicles - Tan, Swee Tiang (2015)
Traffic congestion is defined as the volume of vehicles at the traffic junction which is higher than the available road capacity. However, with traffic light system installed, traffic congestion still happens especially during peak hours. This thesis proposes a new joint algorithm for traffic light system to manage and control the traffic flow at the traffic junction in conjunction with a proposed new sensing method. The aim is to improve the efficiency of conventional traffic light system in terms of reduction of the waiting and travelling times of road users. Normally, there are two methods used to control the conventional traffic light system which are sequencing and sensor demand methods. In the sequencing method, the traffic light system is designed to operate based on a preprogrammed sequence without consideration of real time behavior. In the sensor demand method, it is based on real time sensor detection where loop sensors are placed under certain road junctions. In order to increase and enhance the efficiency and accuracy of real time traffic flow, this thesis proposes a novel implementation of sensing method called Self-Routing Traffic Light (SRTL) which incorporates a self-algorithm program as a practical solution to reduce traffic congestion. SRTL is capable of counting the total number of vehicles entering a certain junction and exiting from the same junction on a real time basis. Based on the use of dual sensors at each road junction, the vehicles are detected by triggering the programmable logic controller to manage and control the traffic light indicators according to real traffic demand. This research uses data at a cross traffic junction in Perak between Jalan Taiping and Kuala Sepatang with the primary data provided by Jabatan Kerja Raya, JKR Larut Matang & Selama, Taiping. With the primary data provided, Simulation of Urban Mobility (SUMO) is used to create traffic simulation for different types of situation. The performance of STRL is compared with conventional sequencing and sensor demand methods. Based on the results of the simulation using SUMO, SRTL show better performance in terms of reducing waiting and travelling time of road users at the traffic junction during peak hours by 35.28% (waiting time) and 24.59% (travelling time) compared to the sensor demand method and an improvement compared to the sequencing method of 46.01% (waiting time) and 29.18% (travelling time). For off peak hours, SRTL also show better performance, 55.57% (waiting time) and 30.25% (travelling time) compared to the sensor demand method and an improvement compared to the sequencing method of 59.43% (waiting time) and 32.89% (travelling time). In conclusion, SRTL provides and ensures the smoothness of traffic flow especially during peak hours by reducing significantly the waiting and travelling times of vehicles at the traffic junction.