Car accidents in Lebanon : automated prevention and detection, and improvement of emergency response time

Abstract

Nearly 1.3 million people die in road crashes each year and 20 to 50 million people are injured or disabled. This made automated car accident prevention and detection a topic of extreme interest worldwide. However, as of yet, the different systems that have been proposed and implemented, do not take underdeveloped countries into account despite their greater need. This is probably due to the fact that this problem is already hard enough to tackle without adding more constraints to it. In addition, these constraints have not been identified and lack of awareness regarding the importance of this problem in underdeveloped countries has led to a lack of research. Furthermore, while there is a general agreement that automated car crash notification will improve emergency time, no studies have been made concerning the degree of improvement and whether it is significant or not. The objective of this work is to propose an automated car accident prevention and detection system that is able to function in underdeveloped countries. In addition, a comparison between traditional notification and automate notification sheds more light on the degree of improvement and the importance of automated notification. In the thesis, a prototype of an automated accident detection and prevention system was developed in the form of a smartphone application. The system was designed with the ability to function in underdeveloped countries in spite of the constraints they present. Based on their testing and feedback, 65% of participating users stated the application’s geofencing system to delimit danger zone was helpful in raising driver awareness. The application also showed a 100% accuracy rate when detecting a car accident. As for improving emergency response time, simulations showed a significant improvement compared to conventional notification methods.