Amelio-rater: Detection and Classification of Driving Abnormal Behaviours for Automated Ratings and Real-Time Monitoring

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Date

2018

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Type

Book chapter

Publisher

IEEE

Series Info

13th International Conference on Computer Engineering and Systems (ICCES) 2018;

Abstract

Real-time monitoring of the drivers may be a factor that would force them to drive safely. In this paper, we introduce a system named 'Amelio-Rater", that focuses on detection and classification of abnormal driving behaviours for automatically generating driver ratings and real-time monitoring. To reduce malicious ratings, the Amelio-rater introduces an automatic rating system which is calculated purely based on the driver's driving behaviours only. Each driver will be given his own Amelio-rater rate and a manual user rate. There are multiple types of driving abnormal behaviours monitored by the proposed system such as meandering, single weaves, sudden changing of lanes and speeding. The classification results achieved showed that the Amelio-rater reached an accuracy of 95%. Our experiments showed that the manual user rates given for the driving behaviour are not far from the rates given by Amelio-rater. Amelio-rater rates were very close to the actual rates given by the users

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Keywords

October University for University for Roads, Time series analysis, Automobiles, Intelligent sensors, Smart phones

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