Autonomous road surveillance system: A proposed model for vehicle detection and traffic signal control

Md Hazrat Ali, Syuhei Kurokawa, A. A. Shafie

研究成果: ジャーナルへの寄稿Conference article

6 引用 (Scopus)

抄録

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.

元の言語英語
ページ(範囲)963-970
ページ数8
ジャーナルProcedia Computer Science
19
DOI
出版物ステータス出版済み - 1 1 2013
イベント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, カナダ
継続期間: 6 25 20136 28 2013

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Traffic signals
Traffic control
Control systems
Statistics

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

これを引用

Autonomous road surveillance system : A proposed model for vehicle detection and traffic signal control. / Ali, Md Hazrat; Kurokawa, Syuhei; Shafie, A. A.

:: Procedia Computer Science, 巻 19, 01.01.2013, p. 963-970.

研究成果: ジャーナルへの寄稿Conference article

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