A Survey of the Algorithms Used for Traffic Light Scheduling Systems
Abstract
Abstract Views: 184
Traffic congestion are among the most important issue that a country needs to confront due to increasing volume of vehicles around the world, particularly in the large urban areas. As a result, the requirement begins for modeling and improving traffic management procedures to improve the growing need. In order to address traffic problems in urban areas a smart traffic management method is the need of time. The solution in this paper is found through the dimensions of traffic mass on the roads. The core objective of this paper is to highlight latest techniques algorithm which has been used for scheduling traffic lights and a comparison based on achieved accuracy.
Downloads
References
S. Ibarra-Martínez, J. A. Castán-Rocha, and J. Laria-Menchaca, "Optimizing urban traffic control using a rational agent," Journal of Zhejiang University SCIENCE C, vol. 15, pp. 1123-1137, 2014.
J. García-Nieto, E. Alba, and A. C. Olivera, "Swarm intelligence for traffic light scheduling: Application to real urban areas," Engineering Applications of Artificial Intelligence, vol. 25, pp. 274-283, 2012.
I. J. Timóteo, M. R. Araújo, R. J. Rossetti, and E. C. Oliveira, "Using TraSMAPI for the assessment of multi-agent traffic management solutions," Progress in Artificial Intelligence, vol. 1, pp. 157-164, 2012.
M. Collotta, A. Messineo, G. Nicolosi, and G. Pau, "A self-powered bluetooth network for intelligent traffic light junction management," WSEAS Transactions on Information Science and Applications, vol. 11, pp. 12-23, 2014.
Y. Zhu, X. Liu, M. Li, and Q. Zhang, "POVA: Traffic light sensing with probe vehicles," IEEE Transactions on Parallel and Distributed Systems, vol. 24, pp. 1390-1400, 2012.
M. Khanjary, K. Faez, M. R. Meybodi, and M. Sabaei, "Shortest paths in synchronized traffic-light networks," in 2011 24th Canadian Conference on Electrical and Computer Engineering (CCECE), 2011, pp. 000882-000886.
B. Fan, W. Lin, and X. Yang, "An efficient framework for recognizing traffic lights in night traffic images," in 2012 5th International Congress on Image and Signal Processing, 2012, pp. 832-835.
M. Seredynski, W. Mazurczyk, and D. Khadraoui, "Multi-segment green light optimal speed advisory," in 2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum, 2013, pp. 459-465.
S. Faye, C. Chaudet, and I. Demeure, "A distributed algorithm for multiple intersections adaptive traffic lights control using a wireless sensor networks," in Proceedings of the first workshop on Urban networking, 2012, pp. 13-18.
B. Zhou, J. Cao, and J. Li, "An Adaptive Traffic Light Control Scheme and Its Implementationin WSN-Based Its," International Journal on Smart Sensing and Intelligent Systems, vol. 6, 2013.
J. Garcia-Nieto, A. C. Olivera, and E. Alba, "Optimal cycle program of traffic lights with particle swarm optimization," IEEE Transactions on Evolutionary Computation, vol. 17, pp. 823-839, 2013.
S. Faye, C. Chaudet, and I. Demeure, "Multiple intersections adaptive traffic lights control using a wireless sensor networks," Département Informatique et Réseaux Groupe RMS: Réseaux, Mobilité et Services, 2013.
J. Huang, H. Wang, Y. Qian, and C. Wang, "Priority-based traffic scheduling and utility optimization for cognitive radio communication infrastructure-based smart grid," IEEE Transactions on Smart Grid, vol. 4, pp. 78-86, 2013.
M. Collotta, M. Denaro, G. Scatà, A. Messineo, and G. Nicolosi, "A self-powered wireless sensor network for dynamic management of queues at traffic lights," Transport and telecommunication, vol. 15, pp. 42-52, 2014.
K. Pandit, D. Ghosal, H. M. Zhang, and C.-N. Chuah, "Adaptive traffic signal control with vehicular ad hoc networks," IEEE Transactions on Vehicular Technology, vol. 62, pp. 1459-1471, 2013.
T. Brys, T. T. Pham, and M. E. Taylor, "Distributed learning and multi-objectivity in traffic light control," Connection Science, vol. 26, pp. 65-83, 2014.
Madhavi Arora and V. K. Banga, “Real Time Traffic Light Control System Using Morphological Edge Detection and Fuzzy Logic” 2nd International Conference on Electrical, Electronics and Civil Engineering (ICEECE'2012) Singapore April 28-29, 2017
B. Zaman, W. Jatmiko, A. Wibowo, and E. M. Imah, "Implementation vehicle classification on Distributed Traffic Light Control System neural network based," in 2011 International Conference on Advanced Computer Science and Information Systems, 2011, pp. 107-112
UMT-AIR follow an open-access publishing policy and full text of all published articles is available free, immediately upon publication of an issue. The journal’s contents are published and distributed under the terms of the Creative Commons Attribution 4.0 International (CC-BY 4.0) license. Thus, the work submitted to the journal implies that it is original, unpublished work of the authors (neither published previously nor accepted/under consideration for publication elsewhere). On acceptance of a manuscript for publication, a corresponding author on the behalf of all co-authors of the manuscript will sign and submit a completed the Copyright and Author Consent Form.
