Open AccessPublic Opinion Analysis of Road Accidents & Review of Conventional and Combinational Driver Safety Methodologies with SelfLearning Algorithms
Author(s) -
A. Tamilarasi
Publication year - 2021
Publication title -
türk bilgisayar ve matematik eğitimi dergisi
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.218
H-Index - 3
ISSN - 1309-4653
DOI - 10.17762/turcomat.v12i2.2383
Subject(s) - computer science , public security , algorithm , accident analysis , computer security , accidental , transport engineering , risk analysis (engineering) , engineering , business , public administration , political science , physics , acoustics
Advanced driver assistance and accident detection system is significantlyneeded to ensure safety for drivers. Drowsiness detection, collision detection and various driver alert systems have penetrated into market with an aim to provide higher security for driver but due to population of vehicle and modification in structure of roads these system fails to answer safety problems that results in severe accidents.In this paper we provide accurate analysis of past recorded accidents in Tamil Nadu state and analysis of public opinion on Accident detection system is carried out using 1004 licensed persons under different ages in three cities (Coimbatore, Erode and Nilgiris) by focusing the major 10 parameters carrying 48 Questions. Findings and implications of this analysis is also discussed in this article. A thorough analysis of recent techniques that are used for AAD (Automatic Accident Detection) and road safety programmes that resolve the pre and post cautionary concerns of accidents in developing countries is addressed with the review of most 4 influencing algorithms in ITS for AAD.. 1 Vehicle Detection using Wheel arc Counter Detection Algorithm, 2 Enhancement of V2X Communication using Multi-RAT,3Road Curvature Estimation using Circle Fitting Algorithm and4Driver Safety Systemis discussed in this paper. To understand recent computational challenges and extended areas of research in ITS, anhybrid approach of CNN with VANETs for accident detection has been suggested to enumerate the obtained accidental information.