DocumentCode
720153
Title
An automated system for Accident Detection
Author
Ali, Asad ; Eid, Mohamad
Author_Institution
Div. of Eng., New York Univ. Abu Dhabi, Abu Dhabi, United Arab Emirates
fYear
2015
fDate
11-14 May 2015
Firstpage
1608
Lastpage
1612
Abstract
Major accidents on highways, freeways and local roads can lead to huge social and economic impacts. Minor accidents may be resolved by the passengers themselves and do not require escorting to hospitals whereas major accidents where airbags are deployed require immediate attention of authorities. Automatic Smart Accident Detection (ASAD) is an auto-detection unit system that immediately notifies an Emergency Contact through a text message when an instant change in acceleration, rotation and an impact force in an end of the vehicle is detected by the system, detailing the location and time of the accident. The idea is that as soon as an accident is detected by the system, the authorities should immediately be notified to prevent further car congestion as well as allow the passengers to be escorted to the hospital in a timely fashion. The system involves the use of fuzzy logic as a decision support built into the smartphone application that analyzes the incoming data from the sensors and makes a decision based on a set of rules. The simulated results show a 98.67% accuracy of the system with failures resulting from the “gray regions” of the variable values.
Keywords
automobiles; emergency management; fuzzy logic; mobile computing; road accidents; road safety; smart phones; traffic engineering computing; ASAD; acceleration; accident location; accident time; airbags; auto-detection unit system; automated system; automatic smart accident detection; car congestion; decision support; economic impacts; emergency contact; freeway accidents; fuzzy logic; highway accidents; impact force; local road accidents; major accidents; minor accidents; rotation; smartphone application; social impacts; text message; Acceleration; Accelerometers; Accidents; Force; Fuzzy logic; Sensors; Vehicles; Accident; Accident Response Time; Crash Detection; Fuzzy Logic;
fLanguage
English
Publisher
ieee
Conference_Titel
Instrumentation and Measurement Technology Conference (I2MTC), 2015 IEEE International
Conference_Location
Pisa
Type
conf
DOI
10.1109/I2MTC.2015.7151519
Filename
7151519
Link To Document