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Intelligent system for improved safety of pedestrian traffic lights

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The high concentration of vehicles and pedestrians at traffic lights makes them a common place for road accidents to occur. The main reason for them is the behavior of vehicle drivers and pedestrians, who often violate the traffic law because of incorrect judgments. This study investigates a special type of traffic lights, which are located on places without roads intersection. In the present study, a concept for improving the safety of such traffic lights is suggested. The method suggests a novel algorithm for the detection of pedestrians, based on image processing and a background pattern. The concept of the detection system makes it applicable in different climatic conditions, such as rain, snow, dust, etc., and offers many advantages over the current situation in Bulgaria. The intelligent system only detects pedestrians in the waiting zones, in order to optimize the traffic problems, such as traffic delays, use by disabled people, protection against troublesome users, etc.
Czasopismo
Rocznik
Strony
35--43
Opis fizyczny
Bibliogr. 17 poz.
Twórcy
  • University of Ruse „Angel Kanchev“8 Studentska, Ruse, 7017, Bulgaria
  • University of Ruse „Angel Kanchev“8 Studentska, Ruse, 7017, Bulgaria
autor
  • University of Ruse „Angel Kanchev“8 Studentska, Ruse, 7017, Bulgaria
  • University of Ruse „Angel Kanchev“8 Studentska, Ruse, 7017, Bulgaria
Bibliografia
  • 1. UN General Assembly. Decade of Action for Road Safety 2011–2020. 2010.
  • 2. Ministry council of the Republic of Bulgaria. National strategy for improving road safety in Bulgaria for the period 2011–2020. 2011.
  • 3. Vishnuvardhan Reddy, K. & Laxman Shanigarapu, L. Design and implementation of inteligent traffic light system. International Journal of Computer Science and Mobile Computing. 2015. Vol. 4. No. 7. P. 93-102.
  • 4. Vilarinho, C. & Tavares, J.P. & Rossetti, R.J.F. Intelligent Traffic Lights: Green Time Period Negotiation. Transportation Research Procedia. 2017. Vol. 22. P. 325-334.
  • 5. Министерство на регионалното развитие и благоустройството. НАРЕДБА № 17 от 23.07.2001 г. за регулиране на движението по пътищата със светлинни сигнали. Обн. ДВ, бр. 72 от 17.08.2001 г., доп., бр. 18 от 05.03.2004 г., изм. и доп., бр. 35 от 15.05.2015 г., в сила от 18.05.2015 г. [In Bulgarian: Ministry of the reginal development and public works. Ordinance № 17 from 23 .07.2001 for regulation of the road traffic with light signals].
  • 6. Национален статистически институт. Пътнотранспортни произшествия в Република България 2016. София, 2017. [In Bulgarian: National statistical institute. Road accidents in the Republic of Bulgaria 2016. Sofia, 2017].
  • 7. European Commission. White paper: Roadmap to a Single European Transport Area – Towards a competitive and resource efficient transport system. 2011.
  • 8. Ministry of the Internal Affairs of Bulgaria. State-Public advisory committee on the problems of road safety. Available at: https://www.mvr.bg/dokkpbdp/безопасност-на-пътя/статистика/обща-статистика.
  • 9. Anciaes, P.R. & Jones, P. Estimating preferences for different types of pedestrian crossing Facilities. Transportation Research Part F. 2018. Vol. 52. P. 222-237.
  • 10. Hirsh, Majid & Chao, Lu & Hardy, Karim. An integrated approach for dynamic traffic routing and ramp metering using sliding mode control. J. Traffic Transp. Eng. (Engl. Ed.) 2018. Vol. 5. No. 2. P. 116-128.
  • 11. Chao, K.H. & Chen, P.Y. An Intelligent Traffic Flow Control System Based on Radio Frequency Identification and Wireless Sensor Networks. International Journal of Distributed Sensor Networks. 2014. Article ID 694545. 10 p.
  • 12. Osigbemeh, M. & Onuu, M. & Asaolu, O. Design and development of an improved traffic light control system using hybrid lighting system. J. Traffic Transp. Eng. (Engl. Ed.) 2017. Vol. 4(1). P. 88-95.
  • 13. Pau, G. & Campisi, T. & Canale, A. & Collotta, M. & Tesoriere, G. Smart Pedestrian Crossing Management at Traffic Light Junctions through a Fuzzy-Based Approach. Future Internet. 2018. Vol. 10(15). doi: 10.3390/fi10020015.
  • 14. Soares Leala, S. & Maciel de Almeidaa, P.E. & Chung, E. Active control for traffic lights in regions and corridors: an approach based on evolutionary computation. Transportation Research Procedia. 2017. Vol. 25. P. 1769-1780.
  • 15. Tettamanti, T. & Mohammadi, A. & Asadi, H. & Varga, I. A two-level urban traffic control for autonomous vehicles to improve network-wide performance. Transportation Research Procedia. 2017. Vol. 27. P. 913-920.
  • 16. Galatioto, F. & Giuffrè, T. & Bell, M. & Tesoriere, G. & Campisi, T. Traffic microsimulation model to predict variability of red-light running influenced by traffic light operations in urban area. Procedia - Social and Behavioral Sciences. 2012. Vol. 53. P. 872-880.
  • 17. Collotta, M. & Pau, G. & Scatà, G. & Campisi, T. A dynamic traffic light management system based on wireless sensor networks for the reduction of the red-light running phenomenon. Transport and Telecommunication. 2014. Vol. 15(1). P. 1-11.
Uwagi
PL
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-61b297a5-35c8-4fdc-bb66-c0c9a8afff40
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