Algorithm of Intelligent Urban Traffic
Abstract
The aim of this work is solution of a specific issue – traffic problem in a big city. To solve this problem we examined the city roads intersection - the main source of the traffic congestion. Intersection is a basic element in the technology of urban traffic regulation. Therefore, first of all, it is necessary to implement the intellectual regulation of vehicles movement through a separate intersection. Such regulation is carried out with a help of a computer program that takes into account the vehicle road situation at the intersection and the corresponding adjustment of the traffic lights signal phases. At a second stage it is necessary to plan an optimal route for each vehicle using, for example, A*-algorithm and the spectrum of data received from an infrastructure of the urban network. As a result of an application of these two phases of urban traffic regulation, an optimal movement regime of all city mobile transport is achieved.
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D.G. Bohuto, V.I. Volynets, P.K. Nikoluk, P.P. Nikolyuk, “Automated management system of vehicles movement within the city”. Bulletin of the Kharkov University, series “Math. Mod., Inform. Technol., Automated Cont. Syst.”, vol.35, pp. 5 –12, 2017. [in Ukrainian]
D.G. Bohuto, V.F. Komarov, P.K. Nikoluk, P.P. Nikolyuk, “Intelligent urban traffic management algorithm”. Bulletin of the Kharkov University, series “Math. Mod., Inform. Technol., Automated Cont. Syst.”, vol.39, pp. 51-62, 2018. [in Ukrainian]
Piezoelectric RoadTraxBL, http://www.irdinc.com/pcategory/axle-sensors-accessories/ piezoelectric-roadtrax-bl.html. [May 06.2018].
Vehicle Sensing: Ten Technologies to Measure Traffic, https://www. azosensors. com/article.aspx?ArticleID=95. 06.06.2018.
Jun Liu, Chuan-Wei Liang, Min Li, Ke Jian, Lan Qin, and Jing-Cheng Liu, “Principle Research on a Novel Piezoelectric 12-DOF Force/Acceleration Sensor”. J. of Sensors, ID 2836365, pp. 116 – 124, 2017.
Yingfeng Cai, Ze Liu, Xiaoqiang Sun, Long Chen, Hai Wang, and Yong Zhang, “Vehicle Detection Based on Deep Dual-Vehicle Deformable Part Models”. J. of Sensors, ID 5627281, pp. 103 – 117, 2017.
Jiyuan Tan, Xiangyun Shi, Zhiheng Li, Kaidi Yang, Na Xie, Haiyang Yu, Li Wang, Zhengxi Li, “Continuous and Discrete-Time Optimal Controls for an Isolated Signalized Intersection”. Journal of Sensors, ID 6290248, pp.11 – 19, 2017.
Ilya Ioslovich, Jack Haddad, Per-Olof Gutman, David Mahalel, “Optimal traffic control synthesis for an isolated intersection”, Control Engineering Practice, vol.19, no.8, pp. 900 –911, 2011.
Pang-wei Wang, Hong-bin Yu, Lin Xiao, Li Wang, “Online Traffic Condition Evaluation Method for Connected Vehicles Based on Multisource Data Fusion”. J. of Sensors, ID 7248189, pp. 123–131, 2017.
Java Programming Examples on Graph Problems & Algorithms, https://www. sanfoundry.com/ java-programming-examples-graph-problems -algorithms.[May 06.2018].
Mohammed Quddu, Simon Washing-ton, “Shortest path and vehicle trajectory aided map-matching for low frequency GPS data”. Transportation Research Part C, vol.55, pp. 328-339, 2015.
Sina Dabiri, Kevin Heaslip, “Inferring transportation modes from GPS trajectories using a convolutional neural network”. Transportation Research, Part C, vol.86, pp. 360–37, 2018.
Feilong Wang, Cynthia Chen, “On data processing required to derive mobility patterns from passively-generated mobile phone data”. Transportation Research, Part C, vol.87, pp. 58–74, 2018.
X. Ma, H. Yu, Y. Wang, Y. Wang, and J. Gomez-Gardenes, “Large-scale transportation network congestion evolution prediction using deep learning theory”. PLoS ONE, vol.10, no.3, pp. 171 – 185, 2015.
Mahdi Hashemi, Hassan A. Karimi, “A weight-based map-matching algorithm for vehicle navigation in complex urban networks”. J. of Intel. Transp. Systems, vol. 20, no.6, pp. 45-76, 2016.
Mahmood Rahmani, Eric Jenelius, Harilaos N. Koutsopoulos, “Floating car and camera data fusion for non-parametric route travel time estimation”. Procedia Comp. Science, vol.37, pp. 390-395, 2014.
Masoud Fadaei Oshyaniv, Marcus Sundberg, Anders Karlstrӧm, “Consistently estimating link speed using sparse GPS data with measured errors”. Procedia – Social and Behavioral Sciences, vol. 111, pp. 829-838, 2014.
Ashish Kumar Patnaika, Prasanta Kumar Bhuyan, K.V. Krishna Rao, “Divisive Analysis (DIANA) of hierarchical clustering and GPS data for level of service criteria of urban streets”. AEJ, vol.55, pp. 407-418, 2016.
Богуто Д.Г., Волинець В.І., Ніколюк П.К., Ніколюк П.П. Автоматизована система керування рухом транспортних засобів в межах міста. Вісник ХНУ серія «Математичне моделювання. Інформаційні технології. Автоматизовані системи управління».2017. Вип.35. С.5 – 12.
Богуто Д.Г., Комаров В.Ф., Ніколюк П.К., Ніколюк П.П. Інтелектуальний алгоритм управління міським трафіком. Вісник ХНУ серія «Математичне моделювання. Інформаційні технології. Автоматизовані системи управління». 2017. Вип.38. С.46 – 57.
Piezoelectric RoadTraxB. URL:http://www.irdinc.com/pcategory/axle-sensors-accessories/ piezoelectric-roadtrax-bl.html. (дата звернення: 15.05.2019).
Vehicle Sensing: Ten Technologies to Measure Traffic. URL: https://www. azosensors. com/article.aspx?ArticleID=95. 06.06.2018 (дата звернення: 16.05.2019).
Jun Liu, Chuan-Wei Liang, Min Li, Ke Jian, Lan Qin, Jing-Cheng Liu. Principle Research on a Novel Piezoelectric 12-DOF Force/Acceleration Sensor. J. of Sensors. ID 2836365. 2017. P.116 –124.
Yingfeng Cai, Ze Liu, Xiaoqiang Sun, Long Chen, Hai Wang, and Yong Zhang. Vehicle Detection Based on Deep Dual-Vehicle Deformable Part Models. J. of Sensors. ID 5627281. 2017. P.103 –117.
Jiyuan Tan, Xiangyun Shi, Zhiheng Li, Kaidi Yang, Na Xie, Haiyang Yu, Li Wang, Zhengxi Li. Continuous Discrete-Time Optimal Controls for an Isolated Signalized Intersection. Journal of Sensors. ID 6290248. 2017. P. 11 – 19.
Ilya Ioslovich, Jack Haddad, Per-Olof Gutman, David Mahalel. Optimal traffic control synthesis for an isolated intersection. Control Engineering Practice. 2011. V.19, №8. P. 900-911.
Pang-wei Wang, Hong-bin Yu, Lin Xiao, Li Wang. Online Traffic Condition Evaluation Method for Connected Vehicles Based on Multisource Data Fusion. J. of Sensors. ID 7248189. 2017. P. 123 – 131.
Java Programming Examples on Graph Problems & Algorithms. URL: https://www. sanfoundry.com/ java-programming-examples-graph-problems -algorithms (дата звертання: 06.04.2019).
Mohammed Quddu, Simon Washing-ton. Shortest path and vehicle trajectory aided map-matching for low frequency GPS data. Transportation Research. Part C. 2015. V.55. P. 328-339.
Sina Dabiri, Kevin Heaslip. Inferring transportation modes from GPS trajectories using a convolutional neural network. Transportation Research, Part C. 2018. V.86. P. 360–37.
Feilong Wang, Cynthia Chen. On data processing required to derive mobility patterns from passively-generated mobile phone data. Transportation Research, Part C. 2018. V.87. P. 58–74.
X. Ma, H. Yu, Y. Wang, Y. Wang, J. Gomez-Gardenes. Large-scale transportation network congestion evolution prediction using deep learning theory. PLoS ONE. 2015. V.10. №3. P. 171–185.
Mahdi Hashemi, Hassan A. Karimi. A weight-based map-matching algorithm for vehicle navigation in complex urban networks. J. of Intel. Transp. Systems. 2016. V.20, №6. P. 45-76.
Mahmood Rahmani, Eric Jenelius, Harilaos N. Koutsopoulos. Floating car and camera data fusion for non-parametric route travel time estimation. Procedia Comp. Science. 2014. V.37. P. 390-395.
Masoud Fadaei Oshyaniv, Marcus Sundberg, Anders Karlstrӧm. Consistently estimating link speed using sparse GPS data with measured errors. Procedia – Social and Behavioral Sciences. 2014. V.111. P. 829-838.
Ashish Kumar Patnaika, Prasanta Kumar Bhuyan, K.V. Krishna Rao. Divisive Analysis (DIANA) of hierarchical clustering and GPS data for level of service criteria of urban streets. AEJ. 2016. V. 55. P. 407-418.