Using Minimum Travel Time to Determine Factors Influencing Travel Time Discrepancy and Variability in Tram Transit
Source abstract
Abstract
Quality of service in urban surface transit has a great impact on sustainable urban mobility, with travel time being one of the most important indicators of service reliability. But urban surface transit is prone to many disturbance factors causing travel time discrepancy and variability, making transit less reliable for passengers. We conducted research in the City of Zagreb on a single tram line by splitting it into constant-frequency segments. The first phase was modeling minimum segment travel times to base the indicators and predictors upon, and the second phase was establishing correlation matrices between the predictors and travel time using Pearson correlation coefficients and significance. Variance inflation factors were used to check for collinearities. While predictors belonging to the transport supply irregularity group did not have an impact, the ones belonging to the disturbance factors group showed correlation, with six of them being significant. This research in rarely represented tram transit determined the most significant disturbance factors rich in traffic context that can be used to develop travel time prediction models.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Transportation Planning and Optimization · Traffic Prediction and Management Techniques · Vehicle emissions and performance
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
University of Zagreb Faculty of Transport and Traffic Sciences, HR-10000 Zagreb, Croatia
References (40)
Show source-provided references
1. van Oort, N. (2011). Service Reliability and Urban Public Transport Design. [Ph.D. Thesis, Delft University of Technology].
2. Ryus, P., Danaher, A., Walker, M., Nichols, F., Carter, B., and Ellis, E. (2013). Transit Capacity and Quality of Service Manual, Tranportation Research Board.
3. To travel or not to travel: ‘Weather’ is the question. Modelling the effect of local weather conditions on bus ridership10.1016/j.trc.2017.11.005 ↗
4. Using GPS data to gain insight into public transport travel time variability10.1061/(ASCE)TE.1943-5436.0000126 ↗
5. Vuchic, V.R. (2005). Urban Transit: Operations, Planning, and Economics, Wiley. [1st ed.].
6. Service reliability and hidden waiting time: Insights from automatic vehicle location data10.1177/0361198106195500110 ↗
7. Understanding the distribution characteristics of bus speed based on geocoded data10.1016/j.trc.2017.07.004 ↗
8. Determinants of Bus Dwell Time10.5038/2375-0901.7.1.2 ↗
9. Corazza, M.V., and Favaretto, N. (2019). A Methodology to Evaluate Accessibility to Bus Stops as a Contribution to Improve Sustainability in Urban Mobility. Sustainability, 11.10.3390/su11030803 ↗
10. Influence of Platform Height, Door Width, and Fare Collection on Bus Dwell Time: Laboratory Evidence for Santiago de Chile10.3141/2143-08 ↗
11. Bus dwell time: The effect of different fare collection systems, bus floor level and age of passengers
12. Crowding in public transport systems: Effects on users, operation and implications for the estimation of demand10.1016/j.tra.2013.06.005 ↗
13. Advanced public transport and intelligent transport systems: New modelling challenges
14. Elkosantini, S., and Darmoul, S. (2013, January 29–31). Intelligent Public Transportation Systems: A Review of Architectures and Enabling Technologies. Proceedings of the 2013 International Conference on Advanced Logistics and Transport, Sousse, Tunisia.10.1109/ICAdLT.2013.6568465 ↗
15. Modeling distributions of travel time variability for bus operations10.1002/atr.1314 ↗
16. Travel time variability on commuter journeys
17. Quantifying bus travel time variability and identifying spatial10.1016/j.ijtst.2021.07.004 ↗
18. Zone scheduling of bus routes to improve service reliability10.1287/trsc.13.3.242 ↗
19. Travel time variability—The case of two public modes10.1287/trsc.16.4.507 ↗
20. Using bus probe data for analysis of travel time variability10.1080/15472450802644439 ↗
21. Xue, Y., Jin, J., Lai, J., and Bin, Y.D. (2011, January 23–27). Empirical characteristics of transit travel time distribution for commuting routes. Proceedings of the Transportation Research Board 90th Annual Meeting, Washington, DC, USA.
22. Analysis of bus travel time distributions for varying horizons and real-time applications10.1016/j.trc.2017.11.023 ↗
23. Probability distributions analysis of travel time variability for the public transit system10.1016/j.ijtst.2021.10.006 ↗
24. Mazloumi, E., Currie, G., and Sarvi, M. (2008, January 13–17). Assessing measures of transit travel time variability and reliability using AVL data. Proceedings of the Transportation Research Board 87th Annual Meeting, Washington, DC, USA.
25. A running time model for bus operations in Singapore
26. Mazloumi, E., Currie, G., and Rose, G. (2008, January 2–3). Causes of travel time unreliability—A Melbourne case study. Proceedings of the 31st Australasian Transport Research Forum, Gold Coast, Australia.
27. The valuation of reliability for personal travel10.1016/S1366-5545(00)00011-9 ↗
28. Estimation of trip travel time distribution using a generalized Markov chain approach10.1016/j.trc.2016.11.008 ↗
29. Public Transit Bus Travel Time Variability Analysis Using Limited Datasets: A Case Study
30. Factors affecting running time on transit routes10.1016/0191-2607(83)90064-X ↗
31. Factors affecting reliability of urban bus services10.1061/TPEJAN.0000548 ↗
32. Analyzing transit travel time performance
33. Šojat, D. (2021). Prognostički Model Vremena Putovanja u Masovnom Javnom Gradskom Prijevozu. [Ph.D. Thesis, University of Zagreb Faculty of Transport and Traffic Sciences].
34. (2024, November 05). Statistički Ljetopis Grada Zagreba 2020. Available online: https://zagreb.hr/statisticki-ljetopis-grada-zagreba/1044.
35. (2024, November 05). Usluge. Available online: https://zet.hr/usluge/7.
36. (2024, December 06). Poslovno Izvješće 2021. Available online: https://www.zet.hr/UserDocsImages/Dokumenti%20i%20obrasci%20za%20preuzimanje/Poslovna%20izvje%C5%A1%C4%87a%20ZET/Poslovno%20izvje%C5%A1%C4%87e%202021.pdf.
37. (2024, December 06). EMTA Barometer 2016 Data—12th Edition. Available online: https://www.emta.com/wp-content/uploads/2018/04/2016_barometer_report.pdf.
38. (2024, November 05). Earth Versions. Available online: https://google.com/earth/versions/#earth-pro.
39. (2024, November 05). Downloading IBM SPSS Statistics 23. Available online: https://ibm.com/support/pages/node/581811.
40. Ott, R.L., and Longnecker, M. (2015). Statistical Methods & Data Analysis, Cengage Learning. [7th ed.].