An NTUA Diploma Thesis titled “Critical factors for the identification of traffic safety events in urban areas” was recently presented by Foteini Bardi. According to the results, the random forest model proved to produce more reliable results predicting traffic safety events with a lower false alarm rate, when compared to binomial logistic regression. Moreover, factor analysis demonstrated that data representing one minute before the event can be described by speed, the deviation of the vehicle from the middle of the road and the distance from the right boundary line. Similarly, data during the event can be better described through speed and longitudinal and lateral acceleration.
Critical factors for the identification of traffic safety events in urban areas, October 2020
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