Distributed Trafic Control System
Keywords:
Traffice Congestion, Distributed traffice control, edge detection, You only Look Once (Yolo)Abstract
If we live in a metropolitan city, traffic is an immense problem of our day to day life. The fundamental explanations for this is, increase of individual vehicles, poor street infrastructure, absence of appropriate road and old ordinary methods for managing traffic. We need to spend a lot of time in rush hour gridlock. Also this leads to a lot of fuel combustion which is a major cause of pollution and health hazards. We have seen that even though amount of vehicles along a particular traffic signal is less, it runs according to a particular allotted time. By using this algorithm we will predict the exact optimal time required by a traffic signal to be made green based on the amount of vehicles present in its lane. In this paper we are trying to minimize traffic clog issue with the assistance of distributive traffic control, using object identification strategy (YOLO) for vehicle counting. The productivity of our proposed framework lies in the fact that this system (DTCS) manages traffic signals depending on the present circumstance of vehicular volume present in its lane and not on pre-assigned time. We have compared two different techniques for counting vehicles which is edge detection and the current state of the art YOLO algorithm.
References
[1] Amrita Rai and Govind Singh Patel Multiple Traffic Control Using Wireless Sensor and Density Measuring Camera. Sensors & Transducers Journal Vol. 94, Issue 7, July 2008, pp. 126-132.
[2] W. Wen & C.L. Yang. “A dynamic and automatic traffic light control system for solving the road congestion problem”.
[3] Mithun, N.C.; Rashid, N.U.; Rahman, S.M.M., "Detection and Classification of Vehicles from Video Using Multiple Time-Spatial Images," Intelligent Transportation Systems, IEEE Transactions on, vol.13, no.3, pp.1215, 1225, Sept. 2012.
[4] Bin-Feng Lin; Yi-Ming Chan; Li-Chen Fu; Pei-Yung Hsiao; Li-An Chuang; Shin-Shinh Huang; Min-Fang Lo; "Integrating Appearance and Edge Features for Sedan Vehicle Detection in the Blind-Spot Area," Intelligent Transportation Systems, IEEE Transactions on , vol.13, no.2, pp.737,747, June 2012.
[5] P. Rajesh, M. Kalaiselvi Geetha and R.Ramu; “Traffic density estimation, vehicle classification and stopped vehicle detection for traffic surveillance system using predefined traffic videos”,Elixir Comp. Sci. & Engg. 56A (2013) 13671-13676.
[6] Deng-Yuan Huang, Chao-Ho Chen, Wu-Chih Hu, Shu-Chung Yi, and Yu-Feng Lin; “Feature-Based Vehicle Flow Analysis and Measurement for a Real-Time Traffic Surveillance System”, Journal of Information Hiding and Multimedia Signal Processing, Volume 3, Number 3, pp. 2073-4212, July 2012.
[7] Hashmi, M.F.; , A.G., "Analysis and monitoring of a high density traffic flow at T-intersection using statistical computer vision based approach," Intelligent Systems Design and Applications (ISDA), 2012 12th International Conference on , vol., no., pp.52,57, 27-29 Nov. 2012.
[8] Suvarna Nandyal1, Pushpalata Patil; “Vehicle Detection and Traffic Assessment Using Images”, International Journal of Computer Science and Mobile Computing, IJCSMC, Vol. 2, Issue. 9, September 2013, pg.8 – 17.
[9] Ravi Kumar Kota, Chandra Sekhar Rao T; “Analysis Of Classification And Tracking In Vehicles Using Shape Based Features”, International Journal of Innovative Research and Development, IJIRD, Vol 2. Issue 8, pp. 279-286, August 2013.
[10] Feris, R.S.; Siddiquie, B.; Petterson, J.; Yun Zhai; Datta, A.; Brown, L.M.; Pankanti, S., "Large-Scale Vehicle Detection, Indexing, and Search in Urban Surveillance Videos," Multimedia, IEEE Transactions on , vol.14, no.1, pp.28,42, Feb. 2012.
[11] Chieh-Ling Huang; Heng-Ning Ma, "A Moving Object Detection Algorithm for Vehicle Localization," Genetic and Evolutionary Computing (ICGEC), 2012 Sixth International Conference on , vol., no., pp.376,379, 25-28 Aug. 2012.
[12] R. B. Girshick. Fast R-CNN. CoRR, abs/1504.08083, 2015.
[13] Prashanth kumar, b. Karthik “micro controller based traffic light controller”, Department of Electrical & Electronics Engineering gokaraju rangaraju institute of engineering & technology, 2011.
[14] Sachin Jaiswal*, Tushar Agarwal*, Akanksha Singh*and Lakshita* ” Intelligent Traffic Control Unit”, *Department of Electronics and Communication Engineering, Bharati Vidyapeeth‟s College of Engineering, Paschim Vihar, New Delhi-110063.
[15] Rijurekhasen, Andrew Cross, adityavashistha, Venkata N. Padmanabhan, Edward Cutrell, and William Thies “Accurate Speed and Density Measurement for Road Traffic in India” IIT Bombay.
[16] Cihan Karakuzu. “Fuzzy logic based smart traffic light simulator design and hardware implementation”. Kocaeli University, Engineering Faculty, Electronics.
[17] Chandrasekaran, G., Periyasamy, S., & Rajamanickam, K. P. Minimization of test time in system on chip using artificial intelligence-based test scheduling techniques. Neural Computing and Applications, 1-10. https://doi.org/10.1007/s00521-019-04039-6.
[18] Highway traffic model-based density estimationIEEE paper by Morarescu, Nancy Univ., France, published in American Control Conference (ACC), 2011.
[19] Musa Mohd Mokji and Syed Abd. Rahman Syed Abu Bakar, “Directional Image Construction Based on Wavelet Transform for Fingerprint Classification and Matching”, National Conference on Computer Graphics and Multimedia, pp. 331 – 335, 2002.
[20] Naik, T., Roopalakshmi, R., Ravi, N. D., Jain, P., & Sowmya, B. H. (2018, April). RFID-Based Smart Traffic Control Framework for Emergency Vehicles. In 2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT) (pp. 398- 401). IEEE
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors contributing to this journal agree to publish their articles under the Creative Commons Attribution 4.0 International License, allowing third parties to share their work (copy, distribute, transmit) and to adapt it, under the condition that the authors are given credit and that in the event of reuse or distribution, the terms of this license are made clear.
