Traffic Signal Light (TSL) can be optimized using vehicle flow statistics obtained by the developed Autonomous Road Surveillance System (ARSS). This research proposes an efficient traffic control system by detecting and counting the vehicle numbers at various times and locations. At present, one of the biggest problems in the main cities in many countries are the traffic jam during office hour and office break hour. Sometimes it can be seen that the traffic signal green light is still ON even though there is no vehicle on road. Similarly, it is also observed that long queues of vehicles are waiting even though the road is empty due to inefficient traffic control system. This is due to TSL selection without proper investigation on vehicle flow. This can be handled by adjusting TSL timing proposed by the developed ARSS. A number of experimental results of vehicle flows are discussed in this research in order to test the feasibility of the developed system. Finally, several advantages and features of ARSS are discussed in successfully implementing the developed system in order to reduce traffic jam in big cities and towns as well as other necessary places.
|Number of pages||8|
|Journal||Procedia Computer Science|
|Publication status||Published - Jan 1 2013|
|Event||4th International Conference on Ambient Systems, Networks and Technologies, ANT 2013 and the 3rd International Conference on Sustainable Energy Information Technology, SEIT 2013 - Halifax, NS, Canada|
Duration: Jun 25 2013 → Jun 28 2013
All Science Journal Classification (ASJC) codes
- Computer Science(all)