2020/03/05 by Rateb Jabbar, Jabbar, Rateb, Mohammed Shinoy +9
Engineering · #IoT and GPS-based Vehicle Safety Systems #Traffic Prediction and Management Techniques
paper · pdf · doi:10.48550/arxiv.2003.07672
Qatar expects more than a million visitors during the 2022 World Cup, which\nwill pose significant challenges. The high number of people will likely cause a\nrise in road traffic congestion, vehicle crashes, injuries and deaths. To\ntackle this problem, Naturalistic Driver Behavior can be utilised which will\ncollect and analyze data to estimate the current Qatar traffic system,\nincluding traffic data infrastructure, safety planning, and engineering\npractices and standards. In this paper, an IoT based solution to facilitate\nsuch a study in Qatar is proposed. Different data points from a driver are\ncollected and recorded in an unobtrusive manner, such as trip data, GPS\ncoordinates, compass heading, minimum, average, and maximum speed and his\ndriving behavior, including driver's drowsiness level. Analysis of these data\npoints will help in prediction of crashes and road infrastructure improvements\nto reduce such events. It will also be used for drivers risk assessment and to\ndetect extreme road user behaviors. A framework that will help to visualize and\nmanage this data is also proposed, along with a Deep Learning-based application\nthat detects drowsy driving behavior that netted an 82 percent accuracy.\n