Naslov
Prediction of Traffic Accidents Severity Based on Machine Learning and Multiclass Classification Model

Autori
Iveta, Mateja ; Radovan, Aleksander ; Mihaljević, Branko

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of the 44th International Convention for Information and Communication Technology, Electronics and Microelectronics - MIPRO 2021 / Skala, Karolj - Opatija : Hrvatska udruga za informacijsku i komunikacijsku tehnologiju, elektroniku i mikroelektroniku - MIPRO, 2021, 1700-1705

Skup
44th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO 2021)

Mjesto i datum
Opatija, Hrvatska, 27.09.2021. - 01.10.2021

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
multiclass classification ; deep learning ; road accidents

Sažetak
Road traffic accidents are a common and seemingly inevitable problem. While its occurrences rely on many unpredictable factors, this paper shows how to utilize machine learning to predict the severity of the accident. The dataset used was related to road accidents in the United Kingdom over a period of a few years. Some of the parameters observed were the weather conditions, sun position, speed limit, and time of the day. To predict the severity of the accident given the circumstances and road conditions, a multiclass classification model is used. Different datasets were combined to cover different situations and scenarios that happen in traffic and taking the severity of accidents in prediction. The dataset values were normalized before the training process and the training set and validated on the validation dataset. The prediction results show the correlation between used weather conditions, daylight time, and traffic accident severity.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo

POVEZANOST RADA