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Accelerating Discoveries in Traffic Science

Accelerating Discoveries in Traffic Science

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PUBLISHED
20.06.2024
DOI
https://doi.org/10.7307/ptt.v36i3.543
ISSUE
2024 (Vol 36), Issue 3
LICENSE
Copyright (c) 2024 Juraj Leonard VERTLBERG, Marko ŠVAJDA, Marijan JAKOVLJEVIĆ, Marko ŠEVROVIĆ
Creative Commons 4.0 logo
This work is licensed under a
Creative Commons Attribution-NonCommercial-
NoDerivatives 4.0 International License.

Operating Vehicles’ Speed Prediction Models

Authors:Juraj Leonard VERTLBERG, Marko ŠVAJDA, Marijan JAKOVLJEVIĆ, Marko ŠEVROVIĆ

Abstract

Vehicle speed is one of the main factors that influence the occurrence and severity of the consequences of road traffic accidents. Operating speed can be defined, among other things, as the actual speed at which the largest number of road users drive in conditions of free traffic flow. It can be measured on existing roads, however, on newly designed roads it can only be predicted. For this reason, many researchers have examined the correlation between the elements of the road as well as its surroundings and operating speed. By determining the correlation, models for predicting operating speed were created. As part of this paper, the most significant models for predicting operating speed were analysed. Of course, the largest number of models are stochastic, but in recent years, models based on artificial intelligence, more precisely on deep learning, have also been created. Accordingly, the goal of this paper is to review the model for predicting the operating speed of vehicles while identifying opportunities for further research and improvement in this area.

Keywords:operating speed, prediction models, road safety, road infrastructure

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