MATEC Web Conf.
Volume 81, 20162016 5th International Conference on Transportation and Traffic Engineering (ICTTE 2016)
|Number of page(s)||5|
|Published online||25 October 2016|
Association Rule Mining on Five Years of Motor Vehicle Crashes
1 Department of Computer science and Software Engineering, Concordia University, Montreal, Canada
2 Qatar University, Doha, Qatar
Every year, road accidents kill more than a million people and injure more than 20 million worldwide. This paper aims to offer guidance on road safety and create awareness by pinpointing the major causes of traffic accidents. The study investigates motor vehicle crashes in the Genesee Finger Lakes Region of New York State. Frequency Pattern Growth algorithm is utilized to cultivate knowledge and create association rules to highlight the time and environment settings that cause the most catastrophic crashes. This knowledge can be used to warn drivers about the dangers of accidents, and how the consequences are worse given a specific context. For instance, a discovered rule from the data states that ‘most of the crashes occur between 12:00 pm and 6:00pm’; hence, it is suggested to modify existing navigation application to warn drivers about the increase in risk factor.
© The Authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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