Araştırma Makalesi
BibTex RIS Kaynak Göster

Uyarlanabilir, Dağıtılmış ve Akıllı Trafik Işık Sistemi

Yıl 2020, Sayı: 20, 866 - 871, 31.12.2020
https://doi.org/10.31590/ejosat.831348

Öz

Bu araştırmada, düşük maliyetli bir uyarlanabilir trafik ışığı sistemi oluşturulması hedeflenmiştir. Bu amaçla öncelikle mevcut trafik ağlarını modellemek için kullanılabilecek olasılıksal, ayrık zamanlı bir trafik simülatörü geliştirilmiştir. Geliştirilen simülatör üzerinde sabit zaman ayarlı bir trafik ışığı sistemi ile karşılaştırıldığında daha yüksek hizmet kalitesine erişen, özgün bir uyarlanabilir trafik ışığı sistemi geliştirilmiş ve test edilmiştir. Geliştirilen sistemin gerçek zamanlı olarak trafik akışını yönetebildiği ve modellenen yolların aşırı doygunluğundan kaynaklanan bilgi kaybından etkilenmediği gösterilmiştir.

Kaynakça

  • Dimitrakopoulos, G., and Demestichas, P. Intelligent transportation systems. IEEE Vehicular Technology Magazine, 5(1), (2010) 77-84.
  • Studer, L., Ketabdari, M., and Marchionni, G. Analysis of adaptive traffic control systems design of a decision support system for better choices. Journal of Civil and Environmental Engineering, 5(6), (2015) 1-10.
  • Chintalacheruvu, N., and Muthukumar, V. Video based vehicle detection and its application in intelligent transportation systems. Journal of transportation technologies, 2(4), (2012) 305-314.
  • Gajda, J., Sroka, R., Stencel, M., Wajda, A., and Zeglen, T. A vehicle classification based on inductive loop detectors. Proceedings of the 18th IEEE Instrumentation and Measurement Technology Conference, (2001) pp. 460-464.
  • Garcia, F., Cerri, P., Broggi, A., de la Escalera, A., and Armingol, J. M. Data fusion for overtaking vehicle detection based on radar and optical flow. In IEEE Intelligent Vehicles Symposium (2012) pp. 494-499.
  • Hunt, P. B., Robertson, D. I., Bretherton, R. D., and Royle, M. C. The SCOOT on-line traffic signal optimisation technique. Traffic Engineering & Control, 23(4) (1982) 190-192.
  • Slavin, C., Feng, W., Figliozzi, M., and Koonce, P. (2013). Statistical study of the impact of adaptive traffic signal control on traffic and transit performance. Transportation Research Record, 2356(1), (2013) 117-126.
  • Homepage | SCATS. Available at: https://www.scats.nsw.gov.au/. Retrieved September 25, 2020.
  • Bretherton, D., Bodger, M., and Cowling, J. SCOOT-Managing congestion, communications and control. Traffic Engineering and Control, 47(3), (2006) 88-92.
  • SCOOTTM – TRL Software. Available at: https://trlsoftware.com/products/traffic-control/scoot/. Retrieved September 25, 2020.
  • Robertson, D. I., and Bretherton, R. D. Optimizing networks of traffic signals in real time-the SCOOT method. IEEE Transactions on vehicular technology, 40(1), (1991) 11-15.
  • Hellinga, B., and Van Aerde, M. An overview of a simulation study of the Highway 401 freeway traffic management system. Canadian Journal of Civil Engineering, 21(3), (1994) 439-454.
  • Stevanovic, A., Dakic, I., and Zlatkovic, M. Comparison of adaptive traffic control benefits for recurring and non-recurring traffic conditions. IET Intelligent Transport Systems, 11(3), (2016) 142-151.
  • Smith, S. F., G. J. Barlow, X. F. Xie, and Z. B. Rubinstein. Smart urban signal networks: initial application of the SURTRAC adaptive traffic signal control system. Proceedings of the Twenty-Third International Conference on Automated Planning and Scheduling, Rome, Italy, 2013, 1-9.
  • Nowacki, G. Development andStandardization of Intelligent Transport Systems. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, 6(4), (2012) 403-412.

An Adaptive, Distributed and Intelligent Traffic Light System

Yıl 2020, Sayı: 20, 866 - 871, 31.12.2020
https://doi.org/10.31590/ejosat.831348

Öz

In this study, it is aimed to create a low cost adaptive traffic light system. For this purpose, a probabilistic, discrete-time traffic simulator has been developed that can be used to model existing traffic networks. A unique adaptive traffic light system, which achieves higher service quality compared to a fixed time adjusted traffic light system, was developed and tested on the simulator. It has been shown that the developed system can manage the traffic flow in real time and is not affected by the information loss caused by the oversaturation of the modeled roads.

Kaynakça

  • Dimitrakopoulos, G., and Demestichas, P. Intelligent transportation systems. IEEE Vehicular Technology Magazine, 5(1), (2010) 77-84.
  • Studer, L., Ketabdari, M., and Marchionni, G. Analysis of adaptive traffic control systems design of a decision support system for better choices. Journal of Civil and Environmental Engineering, 5(6), (2015) 1-10.
  • Chintalacheruvu, N., and Muthukumar, V. Video based vehicle detection and its application in intelligent transportation systems. Journal of transportation technologies, 2(4), (2012) 305-314.
  • Gajda, J., Sroka, R., Stencel, M., Wajda, A., and Zeglen, T. A vehicle classification based on inductive loop detectors. Proceedings of the 18th IEEE Instrumentation and Measurement Technology Conference, (2001) pp. 460-464.
  • Garcia, F., Cerri, P., Broggi, A., de la Escalera, A., and Armingol, J. M. Data fusion for overtaking vehicle detection based on radar and optical flow. In IEEE Intelligent Vehicles Symposium (2012) pp. 494-499.
  • Hunt, P. B., Robertson, D. I., Bretherton, R. D., and Royle, M. C. The SCOOT on-line traffic signal optimisation technique. Traffic Engineering & Control, 23(4) (1982) 190-192.
  • Slavin, C., Feng, W., Figliozzi, M., and Koonce, P. (2013). Statistical study of the impact of adaptive traffic signal control on traffic and transit performance. Transportation Research Record, 2356(1), (2013) 117-126.
  • Homepage | SCATS. Available at: https://www.scats.nsw.gov.au/. Retrieved September 25, 2020.
  • Bretherton, D., Bodger, M., and Cowling, J. SCOOT-Managing congestion, communications and control. Traffic Engineering and Control, 47(3), (2006) 88-92.
  • SCOOTTM – TRL Software. Available at: https://trlsoftware.com/products/traffic-control/scoot/. Retrieved September 25, 2020.
  • Robertson, D. I., and Bretherton, R. D. Optimizing networks of traffic signals in real time-the SCOOT method. IEEE Transactions on vehicular technology, 40(1), (1991) 11-15.
  • Hellinga, B., and Van Aerde, M. An overview of a simulation study of the Highway 401 freeway traffic management system. Canadian Journal of Civil Engineering, 21(3), (1994) 439-454.
  • Stevanovic, A., Dakic, I., and Zlatkovic, M. Comparison of adaptive traffic control benefits for recurring and non-recurring traffic conditions. IET Intelligent Transport Systems, 11(3), (2016) 142-151.
  • Smith, S. F., G. J. Barlow, X. F. Xie, and Z. B. Rubinstein. Smart urban signal networks: initial application of the SURTRAC adaptive traffic signal control system. Proceedings of the Twenty-Third International Conference on Automated Planning and Scheduling, Rome, Italy, 2013, 1-9.
  • Nowacki, G. Development andStandardization of Intelligent Transport Systems. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, 6(4), (2012) 403-412.
Toplam 15 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Makaleler
Yazarlar

Mehmet Dinçer Erbaş 0000-0003-1762-0428

Yayımlanma Tarihi 31 Aralık 2020
Yayımlandığı Sayı Yıl 2020 Sayı: 20

Kaynak Göster

APA Erbaş, M. D. (2020). An Adaptive, Distributed and Intelligent Traffic Light System. Avrupa Bilim Ve Teknoloji Dergisi(20), 866-871. https://doi.org/10.31590/ejosat.831348