НА ПУТИ К ИНТЕРНЕТУ ВЕЩЕЙ В УПРАВЛЕНИИ ТРАНСПОРТНЫМИ ПОТОКАМИ: ОБЗОР СУЩЕСТВУЮЩИХ МЕТОДОВ УПРАВЛЕНИЯ ДОРОЖНЫМ ДВИЖЕНИЕМ
Ключевые слова:
IoT, управление дорожным движением, интеллектуальные транспортные системы, ИТС, транспортные потоки, транспортные заторы
Аннотация
Интернет вещей (IoT) – это одна из важнейших технологий будущего, позволяющая сде-лать окружающую инфраструктуру разумной и адаптируемой к потребностям пользователей. Один из типов подобных инфраструктур - транспорт. Связь между дорогами и городами оче-видна. Основными особенностями дорожной инфраструктуры являются длительный срок службы и высокая стоимость, а это значит, что эту проблему можно решить в настоящий момент, сохранив эти объекты в их первоначальном состоянии. Экономические расчеты пока-зывают, что эффективно управлять движением на существующих дорогах выгоднее, чем стро-ить новые, хотя это и не очень дешево с экономической точки зрения. Исследуя опыт многих крупных мегаполисов мира можно сделать вывод, что строительство новых и реконструкция существующих автомобильных дорог из-за постоянного увеличения количества транспортных средств не позволяет полностью сократить разницу между пропускной способностью дорог и уровнем спроса необходимого для автомобильного транспорта. Высокие затраты на строи-тельство новой дорожной инфраструктуры, постоянные транспортные заторы и экологиче-ские факторы подталкивают компании и правительство к поиску решений для более эффектив-ного управления транспортными потоками. Мы ищем возможности для минимизации негатив-ных последствий заторов и оптимизации использования ограниченных государственных средств. В этой статье рассматриваются существующие методы и алгоритмы для автоматического управления транспортными потоками с целью определения точек воздействия на них и методов для применения IoT в транспортном секторе. Обсуждаются преимущества и недостатки суще-ствующих методов, в том числе оценивается их эффективность.
Литература
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25. Miz Volodymyr, and Vladimir Hahanov. Smart traffic light in terms of the cognitive road traf-fic management system (CTMS) based on the Internet of Things, Proceedings of IEEE East-West Design & Test Symposium (EWDTS 2014). IEEE, 2014.
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31. Nor, Ruhaizan Fazrren Ashraff Mohd, Fadhlan HK Zaman, and Shamry Mubdi. Smart traffic light for congestion monitoring using LoRaWAN, 2017 IEEE 8th Control and System Gradu-ate Research Colloquium (ICSGRC). IEEE, 2017.
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34. Keertikumar M., M. Shubham, and R.M. Banakar. Evolution of IoT in smart vehicles: An overview, 2015 International Conference on Green Computing and Internet of Things (ICGCIoT). IEEE, 2015.
35. Kaminski Nicholas J., Maria Murphy, and Nicola Marchetti. Agent-based modeling of an IoT network, 2016 IEEE international symposium on systems engineering (ISSE). IEEE, 2016.
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2. Wallace C. E. et al. TRANSYT-7F user's manual, 1984, No.UF-TRC-U32 FP-06/07.
3. Hunt, P. B., et al. SCOOT-a traffic responsive method of coordinating signals. No. LR 1014 Monograph. 1981.
4. Gartner N.H., Tarnoff P.J., Andrews C.M. Evaluation of optimized policies for adaptive con-trol strategy, Transportation Research Record, 1991, No. 1324.
5. Sims, A.G., and Dobinson, K.W. The Sydney coordinated adaptive traffic (SCAT) system philos-ophy and benefits, IEEE Transactions on vehicular technology, 1980, Vol. 29.2, pp 130-137.
6. Mauro, Vito, and C. Di Taranto. Utopia, IFAC Proceedings, 1990, Vol. 23.2, pp. 245-252.
7. Zhao, Yi, and Zong Tian. An overview of the usage of adaptive signal control system in the United States of America, Applied Mechanics and Materials, Vol. 178. Trans Tech Publica-tions, 2012.
8. Misbahuddin Syed, et al. IoT based dynamic road traffic management for smart cities, 2015 12th International Conference on High-capacity Optical Networks and Enabling/Emerging Technologies (HONET). IEEE, 2015.
9. Chong Hon Fong, and Danny Wee Kiat Ng. Development of IoT device for traffic management system, 2016 IEEE Student Conference on Research and Development (SCOReD). IEEE, 2016.
10. Slavin Courtney et al. Statistical study of the impact of adaptive traffic signal control on traffic and transit performance,Transportation Research Record, 2013, Vol. 2356.1, pp. 117-126.
11. Ozbay, Kaan et al. Evaluation of adaptive control strategies for NJ highways. No. FHWA-NJ-2006-001. 2006.
12. Pavleski, Daniel, Daniela Koltovska-Nechoska, and Edouard Ivanjko. Evaluation of adaptive traffic control system UTOPIA using microscopic simulation, 2017 International Symposium ELMAR. IEEE, 2017.
13. Kanungo, Anurag, Ayush Sharma, and Chetan Singla. Smart traffic lights switching and traffic density calculation using video processing, 2014 Recent Advances in Engineering and Compu-tational Sciences (RAECS). IEEE, 2014.
14. Milanes Vicente, et al. An intelligent V2I-based traffic management system, IEEE Transac-tions on Intelligent Transportation Systemsm 2012, Vol. 13.1, pp. 49-58.
15. Wang Hongwei. A reservation-based smart parking system, 2011.
16. He Wu, Gongjun Yan, and Li Da Xu. Developing vehicular data cloud services in the IoT envi-ronment, IEEE Transactions on Industrial Informatics, 2014, Vol. 10.2, pp. 1587-1595.
17. Khanna Abhirup, and Rishi Anand. IoT based smart parking system, 2016 International Con-ference on Internet of Things and Applications (IOTA). IEEE, 2016.
18. Al-Sakran, Hasan Omar. Intelligent traffic information system based on integration of Internet of Things and Agent technology, International Journal of Advanced Computer Science and Applications (IJACSA), 2015, Vol. 6.2, pp. 37-43.
19. Roess R. P., Prassas E. S., McShane W. R. Traffic engineering. Pearson/Prentice Hall, 2004.
20. De Souza, Allan M., et al. Traffic management systems: A classification, review, challenges, and future perspectives, International Journal of Distributed Sensor Networks, 2017, Vol. 13.4, 1550147716683612.
21. Rizwan Patan, K. Suresh, and M. Rajasekhara Babu. Real-time smart traffic management system for smart cities by using Internet of Things and big data, 2016 international conference on emerging technological trends (ICETT). IEEE, 2016.
22. He Wu, Gongjun Yan, and Li Da Xu. Developing vehicular data cloud services in the IoT envi-ronment, IEEE Transactions on Industrial Informatics, 2014, Vol. 10.2, pp. 1587-1595.
23. Bui, Khac‐Hoai Nam, Jai E. Jung, and David Camacho. Game theoretic approach on Re-al‐time decision making for IoT‐based traffic light control, Concurrency and Computation: Practice and Experience, 2017, Vol. 29.11, e4077.
24. Yu Minghe, et al. An RFID electronic tag based automatic vehicle identification system for traffic IOT applications, 2011 Chinese Control and Decision Conference (CCDC). IEEE, 2011.
25. Miz Volodymyr, and Vladimir Hahanov. Smart traffic light in terms of the cognitive road traf-fic management system (CTMS) based on the Internet of Things, Proceedings of IEEE East-West Design & Test Symposium (EWDTS 2014). IEEE, 2014.
26. Thakur Tanvi Tushar, et al. Real time traffic management using Internet of Things, 2016 In-ternational Conference on Communication and Signal Processing (ICCSP). IEEE, 2016.
27. Phan Cao Tho, et al. Applying the IoT platform and green wave theory to control intelligent traffic lights system for urban areas in Vietnam, TIIS, 2019, Vol. 13.1, pp. 34-51.
28. Chowdhury Abdullahi. Priority based and secured traffic management system for emergency vehicle using IoT, 2016 International Conference on Engineering & MIS (ICEMIS). IEEE, 2016.
29. Mzahm Anas M., Mohd Sharifuddin Ahmad, and Alicia YC Tang. Agents of Things (AoT): An intelligent operational concept of the Internet of Things (IoT), 2013 13th International Conference on Intellient Systems Design and Applications. IEEE, 2013.
30. Jabbarpour Mohammad Reza, Armin Nabaei, and Houman Zarrabi. Intelligent guardrails: an IoT application for vehicle traffic congestion reduction in smart city, 2016 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData). IEEE, 2016.
31. Nor, Ruhaizan Fazrren Ashraff Mohd, Fadhlan HK Zaman, and Shamry Mubdi. Smart traffic light for congestion monitoring using LoRaWAN, 2017 IEEE 8th Control and System Gradu-ate Research Colloquium (ICSGRC). IEEE, 2017.
32. Turcu Cristina Elena, Vasile Gheorghiţă Găitan, and Corneliu Octavian Turcu. An internet of things-based distributed intelligent system with self-optimization for controlling traffic-light intersections, 2012 International Conference on Applied and Theoretical Electricity (ICATE). IEEE, 2012.
33. Masek Pavel, et al. A harmonized perspective on transportation management in smart cities: The novel IoT-driven environment for road traffic modeling, Sensors, 2016, Vol. 16.11, 1872.
34. Keertikumar M., M. Shubham, and R.M. Banakar. Evolution of IoT in smart vehicles: An overview, 2015 International Conference on Green Computing and Internet of Things (ICGCIoT). IEEE, 2015.
35. Kaminski Nicholas J., Maria Murphy, and Nicola Marchetti. Agent-based modeling of an IoT network, 2016 IEEE international symposium on systems engineering (ISSE). IEEE, 2016.
36. Venkatesh H., Shrivatsa D. Perur, and M. C. Jagadish. An approach to make way for intelligent ambulance using IoT, International Journal of Electrical and Electronics Research, 2015, Vol. 3.1.
37. Tielert Tessa, et al. The impact of traffic-light-to-vehicle communication on fuel consumption and emissions, 2010 Internet of Things (IOT). IEEE, 2010.
38. Anass Rghioui, Hernafi Yassine, and Bouhorma Mohammed. IoT for ITS: a dynamic traffic lights control based on the Kerner three phase traffic theory, International Journal of Comput-er Applications, 2016, Vol. 145.1, pp. 0975-8887.
39. Liu Ying, Lei Liu, and Wei-Peng Chen. Intelligent traffic light control using distributed multi-agent Q learning, 2017 IEEE 20th International Conference on Intelligent Transportation Sys-tems (ITSC). IEEE, 2017.
40. Bui Khac-Hoai Nam, and Jason J. Jung. Internet of agents framework for connected vehicles: A case study on distributed traffic control system, Journal of Parallel and Distributed Compu-ting, 2018, Vol. 116, pp. 89-95.
