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Accelerating Discoveries in Traffic Science

Accelerating Discoveries in Traffic Science

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PUBLISHED
13.02.2023
DOI
https://doi.org/10.7307/ptt.v35i1.29
ISSUE
2023 (Vol 35), Issue 1
LICENSE
Copyright (c) 2024 Stanko Bajčetić, Predrag Živanović, Slaven Tica, Branko Milovanović, Andrea Nađ
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This work is licensed under a
Creative Commons Attribution-NonCommercial-
NoDerivatives 4.0 International License.

Factors Influencing Driving Time in Public Transport – A Multiple Regression Analysis

Authors:Stanko Bajčetić, Predrag Živanović, Slaven Tica, Branko Milovanović, Andrea Nađ

Abstract

Deviations in driving time (DT), or significant variations, occur frequently on urban public transport (PT) lines, except in subsystems with separate routes. DT variability is the main reason for disturbances in operation, leading to unstable and unreliable transport service. Moreover, it also causes variability in total user travel time, which is one of the main parameters of transport service quality. Identifying and quantifying factors that influence PT vehicle DT characteristics is significant for designing advanced prediction and  passenger information systems and prioritising investments to reduce bus travel time and improve the scheduling process, and thus the level of transport service quality. An analysis of the elements of the route and other static elements of the line that influence DT was carried out in this paper. A model for determining and quantifying influential factors and methodologies for collecting all necessary data was created. The multiple regression model, developed as a result of the conducted multivariate statistical analysis using the specialised SPSS software, was applied to the selected representative set of lines in a real urban PT system. The created regression model explains between 18.2% and 97.4% of the variance of average, minimum and maximum DT and its deviation in the peak and off-peak periods.

Keywords:public transport, driving time, influence factors, multiple regression

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