Active Safety with Traffic Sign Recognition System in Vehicular Ad-Hoc Network (Vanet) using Classifier Techniques
T. Rajasekaran1, Sumathi Eswaran2, A. Rengarajan3, T.V. Ananthan4 

1T. Rajasekaran, Research Scholar, Department of Computer Science, Dr. M.G.R. Educational and Research Institute, Chennai.
2Sumathi Eswaran, Dean-Department of CSE/IT, Dr. M.G.R Educational and Research Institute, Chennai.
3A. Rengarajan, Professor, Computer Science and Engineering, Vel Tech Multitech Dr. RR Dr.SR Engg. College, Chennai.
4T.V. Ananthan, Professor, Department of CS, Dr. M.G.R Educational and Research Institute, Chennai.

Manuscript received on 10 March 2019 | Revised Manuscript received on 18 March 2019 | Manuscript published on 30 July 2019 | PP: 6186-6190 | Volume-8 Issue-2, July 2019 | Retrieval Number: B3813078219/19©BEIESP | DOI: 10.35940/ijrte.B3813.078219
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Abstract: Intelligent Transportation System (ITS) is one of the major research areas where the researchers focus on Vehicle traffic prediction, efficient routing algorithms, security in vehicle communication, various QoS parameters and so on. Wireless technology is progressing faster with time. People are doing research these days generally in the field of Wireless communication. VANET is the most developing exploration territory in remote correspondence. With the headway and development of the VANET, there will be an incredible upheaval in the field of telecommunication regarding quick handovers, arrange accessibility, security, wellbeing with the utilization of cutting edge applications and so on. VANET innovation is progressing with the progression of time however there are numerous issues that must be routed to make the system more overwhelming. In perspective of aforementioned, in this paper we have proposed an effective mechanism for object detection in highways using Neural Networking and proving driver assistance to enhance the existing system to the next level as Intelligent Transportation System.
Keywords: Vehicular Ad-hoc Network (VANET), Intelligent Transportation System (ITS), LIDAR, Ultrasonic Sensor, Convolution Neural Networks (CNN), HOG and Haar Classifier.
Scope of the Article: Mobile Ad Hoc Network