Dynamic traffic light flow control system using on-road sensor technology / Mohamed Irfan

Mohamed , Irfan (2017) Dynamic traffic light flow control system using on-road sensor technology / Mohamed Irfan. Masters thesis, Universiti Malaya.

[img] PDF (The Candidate's Agreement)
Restricted to Repository staff only

Download (210Kb)
    [img] PDF (Thesis M.A.)
    Download (1037Kb)

      Abstract

      The increasing number of vehicular traffic around the world has resulted in congestion, especially in large urban areas. This has become a major concern among transportation specialists & related decision makers. Traffic congestion at cross-roads is a huge problem since precious time and resources are wasted when vehicles have to wait in the queue for a long period of time. The most common traffic light systems that are currently installed have a fixed time interval for changing the signals. These systems remain this way until further resetting is done to change the signal time. The timing of these standard traffic light systems are based on their default setup which basically considers normal traffic flow. The existing methods and proposed methods for intelligent traffic management and control are not adequately efficient in terms of performance and decision making. In this research, a system is proposed that utilizes and manages traffic light controllers; more specifically an algorithm is presented which dynamically changes the traffic control system based on the vehicular flow data generated by on-road sensor technology. The sensors are used as a tool to measure the volume of vehicles, while a dynamic traffic controller is developed to control the operation of the traffic light system which is supported by these sensors. The controller uses Traffic Light Signal Manipulation Algorithm (TLSMA) to dynamically change in the traffic signals by using the data generated by the sensors. Simulation has been carried out using SUMO to solve traffic congestion by measuring the average speed and the vehicular flow on a single intersection.

      Item Type: Thesis (Masters)
      Additional Information: Dissertation (M.A.) – Faculty of Computer Science & Information Technology, Universiti Malaya, 2017.
      Uncontrolled Keywords: Sensor; Traffic Light Signal Manipulation Algorithm (TLSMA); Traffic congestion; Traffic light system; Wireless based methods
      Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
      T Technology > T Technology (General)
      Divisions: Faculty of Computer Science & Information Technology
      Depositing User: Mr Mohd Safri Tahir
      Date Deposited: 11 Apr 2023 06:33
      Last Modified: 11 Apr 2023 06:33
      URI: http://studentsrepo.um.edu.my/id/eprint/14257

      Actions (For repository staff only : Login required)

      View Item