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View all- Wang JGuo XYang X(2021)Efficient and Safe Strategies for Intersection Management: A ReviewSensors10.3390/s2109309621:9(3096)Online publication date: 29-Apr-2021
Adaptive traffic signal optimization considering emergency vehicle preemption and tram priority using PVS algorithm
Article No.: 76, Pages 1 - 8
Abstract
The tram has been known as a modern, environmentally friendly, quick and safe means of transportation; hence, giving the signal priority for trams on arterial streets at signalized intersections is crucial to improve tram service efficiency. However, tram priority can impact the movement of emergency vehicles (ambulances, police cars, fire engines, etc) which required quick response to save lives and properties. Therefore, to organize the traffic road, it is necessary to make the urban road network more efficient by considering both tram and emergency vehicles priority. In this paper we propose a new approach, a system that can adapt efficiently with a priority signal control. Thereof, we have used Transit Signal Priority (TSP) techniques to adjust signal phasing in order to serve emergency vehicles and manage the tram priority in a coordinated tram intersection. The system used in this study provides acyclic signal operation based on a real time control approach including: - An optimization process using passing vehicle search algorithm (PVS) to control the flow through the network. - A database to manage the sensor data from detectors for real time predictions of emergency vehicle and tram arrival time. - A traffic road simulation module to evaluate best timing plans at the intersection.
References
[1]
Boillot, F., Blosseville, Lesort, Motyka, papageorgiou, sellam, Optimal signal control of urban traffic networks, sixth international conference on road traffic monitoring and control, IEEE london april 1992.
[2]
Boumghar, S. (2000). Nouvelle approche de l'optimisation en temps réel des feux d'un carrefour complexe isolé par la programmation linéaire mixte en nombres entiers. Thèse de doctorat, Lamsade, Université Paris Dauphine, Paris, France.
[3]
Farges (J.L.), Khoudour (L.), Lesort (J.B.). - PRODYN: On Site Evaluation. IEE Conference, Publication N 320, 1990, pp 62--66.
[4]
Lowrie, P. (1982). The Sydney co-ordinated adaptive traffic system: Principles, methodology, and algorithms. In Proceedings of the IEE conference on Road Traffic Signaling, numero 207, pages 67 to 70. IEE Pub.
[5]
Gartner, N., F. J. Pooran, and C. Andrews. Implementation of the OPAC Adaptive Control Strategy in a Traffic Signal Network. Proc., Intelligent Transportation Systems, Oakland, Calif., IEEE, New York, 2001, pp. 195--200.
[6]
Bretherton, R., Hunt, P., Robertson, D. et Royle, M. (1982). The SCOOT on-line traffic signal optimization technique. In International Conference on Road- Traffic Signalling, London, UK.
[7]
Gazis, D. C. Optimum Control of a System of Oversaturated Intersections. Operation Research, Vol. 12, No. 6, 1964, pp. 815--831.
[8]
Gazis, D. C., and R. B. Potts. The Oversaturated Intersection. Proc., 2nd International Symposium on the Theory of Road Traffic Flow, Paris, 1965.
[9]
D'Ans, G. C., and D. C. Gazis. Optimal Control of Oversaturated Storeand-Forward Transportation Networks. Transportation Science, Vol. 10, No. 1, 1976, pp. 1--19.
[10]
Michalopoulos, P. G., and G. Stephanopoulos. Oversaturated Signal System with Queue Length Constraints I. Transportation Research, Vol. 11, No. 6, 1977, pp. 413--421.
[11]
Zhang, L., Y. Yin, and Y. Lou. Robust Signal Timing for Arterials Under Day-to-Day Demand Variations. In Transportation Research Record: Journal of the Transportation Research Board, No. 2192, Transportation Research Board of the National Academies, Washington, D.C., 2010, pp. 156--166.
[12]
Lo, H. L., and H. F. Chow. Control Strategies for Oversaturated Traffic. Journal of Transportation Engineering, Vol. 130, No. 4, 2004, pp. 466--478.
[13]
Lucas, D. E., P. B. Mirchandani, and K. L. Head. Using Remote Simulation to Evaluate Real-Time Traffic Control Strategies. In Transportation Research Record: Journal of the Transportation Research Board, No. 1727, TRB, National Research Council, Washington, D.C., 2000, pp. 10--15.
[14]
Mirchandani, P., and L. Head. A Real-Time Traffic Signal Control System: Architecture, Algorithms, and Analysis. Transportation Research Part C: Emerging Technologies, Vol. 9, No. 6, 2001, pp. 415--432.
[15]
Van Katwijk, R. Multi-Agent Look-Ahead Traffic Adaptive Control. PhD dissertation. Delft University of Technology, Netherlands, 2008.
[16]
X. Qin and A. M. Khan, "Control strategies of traffic signal timing transition for emergency vehicle preemption," Transportation research part C: emerging technologies, vol. 25, pp. 1--17, 2012.
[17]
W. Kang, G. Xiong, Y. Lv, X. Dong, F. Zhu, and Q. Kong, "Traffic signal coordination for emergency vehicles," in 17th International IEEE Conference on Intelligent Transportation Systems (ITSC). IEEE, 2014, pp. 157--161.
[18]
Brenner, M. F. (2007). "LRT-and tramway priority in the course of "Green Waves" a planning method to integrate public transport into progressive signal systems." Proceedings of the 14th World Congress on Intelligent Transport Systems, Beijng.
[19]
Min Yang, Jian Ding, Wei Wang, and Yi-Yuan Ma. A Coordinated Signal Priority Strategy for Modern Trams on Arterial Streets by Predicting the Tram Dwell Time. KSCE Journal of Civil Engineering (0000) 00(0):1--14
[20]
Foy, M. D., R.F. Benekohal, and D.E. Goldberg. "Signal Timing Determination Using Genetic Algorithms", Transportation Research Record 1365, TRB, Washington D.C., 1992, 108--115
[21]
Hadi, M.A., and C. E. Wallace. "Hybrid Genetic Algorithm to Optimize Signal Phasing and Timing", Transportation Research Record 1421, TRB, Washington D.C., 1993, 104--112.
[22]
Park, B.B., C.J. Messer, and T. Urbanik II. "Traffic Signal Optimization Program for Oversaturated Conditions - Genetic Algorithm Approach", Transportation Research Record 1683, TRB, Washington D.C., 1999, 133--142.
[23]
Park, B.B., Rouphail, N.M., and J. Sacks. Assessment of a Stochastic Signal Optimization Method Using microsimulation. Technical Report No 110, National Institute of Statistical Sciences.
[24]
Abu-Lebdeh, G., and R. F. Benekohal. "Development of a Traffic Control and Queue Management Procedure for Oversaturated Arterials", Transportation Research Record 1603, TRB, Washington D.C., 1997, 119--127.
[25]
Abu-Lebdeh, G., and R. F. Benekohal. "Convergence Variability and Population Sizing in Micro-Genetic Algorithms", Computer-Aided Civil and Infrastructure Engineering, 14 (1999), 321--334.
[26]
Park, B., and J.D. Schneeberger. Evaluation of Traffic Signal Timing Optimization Methods Using a Stochastic and Microscopic Simulation Program. Research Report No UVACTS-5-0-4, University of Virginia, Charlottesville, Virginia, January 2003.
[27]
N. M. Rouphail, B. B. Park, and J. Sacks, Direct signal timing optimization: strategy development and results. technical report, in XI Pan American conference in Traffic and Transportation Engineering, 2000.
[28]
Park, B. B., and I. Yun. Stochastic Optimization Method for Coordinated Actuated Signal Systems. UVACTS-15-0-102, University of Virginia, Charlottesville, Virginia, January 2006.
[29]
A.M. Turky, M.S. Ahmad, M.Z.M. Yusoff, and B.T. Hammad, "Using Genetic Algorithm for Traffic Light Control System with a Pedestrian Crossing", In Proceeding of the 4th International Conference on Rough Sets and Knowledge Technology, Gold Coast, Australia, July 14-16, 2009.
[30]
L. Singh, S. Tripathi, and H. Arora, "Time Optimization for Traffic Signal Control Using Genetic Algorithm", International Journal of Recent Trends in Engineering, 2 (2), (November 2009), 4-6.
[31]
C. Colombaroni, G. Fusco, and A. Gemma, "Optimization of Traffic Signals on Urban Arteries through a Platoon-Based Simulation Model", In Proceedings of the 11th WSEAS International Conference on Automatic Control, Modeling and Simulation, Istanbul, Turkey, May 30 - June 1, 2009.
[32]
F. Teklu, A. Sumalee, and D. Watling, A genetic algorithm approach for optimizing traffic control signals considering routing, Comput. Aided Civil and Infrastruct. Eng., vol. 22, no. 1, pp. 31 to 43, 2007.
[33]
J. Sanchez, M. Galan, and E. Rubio, Applying a traffic lights evolutionary optimization technique to a real case: las ramblas area in santa cruz de tenerife, IEEE Trans. Evol. Comput., vol. 12, no. 1, pp. 25 to 40, 2008.
[34]
Phuong Thi Mai Nguyen, Benjamin N. Passow, Yingjie Yang, Improving Anytime Behavior for Traffic Signal Control Optimization Based on NSGA-II and Local Search, 2016 International Joint Conference on Neural Networks (IJCNN)
[35]
J. Chen and L. Xu, Road-junction traffic signal timing optimization by an adaptive particle swarm algorithm, in Proceedings 9th International Conference on Control, Automation, Robotics and Vision, 2006, pp. 1 to 7.
[36]
S. Kachroudi and N. Bhouri, A multimodal traffic responsive strategy using particle swarm optimization, in Proceedings of the 12th IFAC Symposium on Transportation Systems, 2009.
[37]
J. Garcia-Nieto, E. Alba, and A. Carolina Olivera, Swarm intelligence for traffic light scheduling: Application to real urban areas, Engineering Applications of Artificial Intelligence, vol. 25, no. 2, pp. 274 to 283, 2012.
[38]
Garcia-Nieto, J. Ferrer, and E. Alba, Optimising traffic lights with metaheuristics: Reduction of car emissions and consumption, in IJCNN, 2014, pp. 48 to 54.
[39]
A. Carolina Olivera, J. Garcia-Nieto, and E. Alba, Reducing vehicle emissions and fuel consumption in the city by using particle swarm optimization, Applied Intelligence, vol. 42, no. 3, pp. 389 to 405, 2015
[40]
M A Gokçe, E Oner and G Isik, Traffic signal optimization with Particle Swarm Optimization for signalized roundabouts, Transactions of the Society for Modeling and Simulation International 2015, Vol. 91(5) 456 to 466
[41]
Sina Dabiri and Montasir Abbas,"Arterial traffic signal optimization using Particle Swarm Optimization in an Integrated VISSIM-MATLAB simulation environment", 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC) Windsor Oceanico Hotel, Rio de Janeiro, Brazil, November 1-4, 2016.
[42]
J. Lee, B. Abdulhai, A. Shalaby, E. Chung,"Real-time optimization for adaptive traffic signal control using genetic algorithms", Journal of Intelligent Transportation Systems Technology, Planning, and Operation, 2005.
[43]
PoonamSavsani, VimalSavsani. (2016), Passing vehicle search (PVS): A novel metaheuristic algorithm, Applied Mathematical Modeling Volume 40, Pages 3951--3978
[44]
Data provided by "TRANSITEC": independent engineering consultancy firm, specialized in mobility. www.transitec.net
Index Terms
- Adaptive traffic signal optimization considering emergency vehicle preemption and tram priority using PVS algorithm
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October 2018
580 pages
ISBN:9781450365628
DOI:10.1145/3286606
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Published: 10 October 2018
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SCA '18
SCA '18: 3rd International Conference on Smart City Applications
October 10 - 11, 2018
Tetouan, Morocco
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View all- Wang JGuo XYang X(2021)Efficient and Safe Strategies for Intersection Management: A ReviewSensors10.3390/s2109309621:9(3096)Online publication date: 29-Apr-2021
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