Density Based Traffic Controller with Emergency Override using CCTV Camera
Venkat G1, Arulananth T S2, Baskar M3
1Venkat G, PG Student, Department of Electronics and Communication Engineering, MLR Institute of Technology, Hyderabad (Telangana), India.
2Arulananth T S, Professor, Department of Electronics and Communication Engineering, MLR Institute of Technology, Hyderabad (Telangana), India.
3Baskar M, Professor, Department of Computer Science and Engineering, MLR Institute of Technology, Hyderabad (Telangana), India.
Manuscript received on 21 July 2019 | Revised Manuscript received on 03 August 2019 | Manuscript Published on 10 August 2019 | PP: 866-869 | Volume-8 Issue-2S3 July 2019 | Retrieval Number: B11620782S319/2019©BEIESP | DOI: 10.35940/ijrte.B1162.0782S319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The aim of this project is to provide alternative solution for the traffic signal system in clearing high density traffic jam. Now a day’s more number of vehicles is coming on to the road creating more traffic congestion at any junction. The traffic congestion is a severe problem when there arises high density at a particular junction. Especially when there is an emergency like ambulance, fire brigade stuck in the traffic they require priority to go first. In such cases it is necessary to override the normal signal timings automatically. To overcome this problem, this project uses CCTV cameras on each side of junction. It assigns longer green light with the help of the micro controller whenever it sensing the heavy density and whenever it finds emergency vehicles stuck in traffic like ambulance, fire brigade etc they require priority to go first. In this manner it overrides the standard signal timings there by it saves the waiting time of the vehicular. This project uses micro controller interfacing with CCTV aligned in the sight configuration across the load for detecting the density. Once the image is captured from the CCTV footage, it is converted into greyscale image. The greyscale image is passed through the median filter in order to reduce the noise present in it. Further Canny edge detection finds the intensity gradients of the images by suppressing all the other edges that weak and not connected to the strong edges. Then based on the canny image the density is calculated and turns the green light on at the heavy density road side of junction.
Keywords: Traffic Patterns, Traffic Density, Image Acquisition, Canny Edge Detection, Median Filter.
Scope of the Article: Network Traffic Characterization and Measurements