RT journal article
T1 Big Data Analysis for Travel Time Characterization in Public Transportation Systems †
A1 Nesmachnow, Sergio
A1 Massobrio Lois, Renzo Martín
A1 Guridi, Santiago
A1 Olmedo, Santiago
A1 Tchernykh, Andrei
A2 Ingeniería Informática
K1 intelligent transportation systems
K1 public transportation
K1 travel time characterization
K1 urban data analysis
AB In this article, we introduces a model based on big data analysis to characterize the travel times of buses in public transportation systems. Travel time is a critical factor in evaluating the accessibility of opportunities and the overall quality of service of public transportation systems. The methodology applies data analysis to compute estimations of the travel time of public transportation buses by leveraging both open-source and private information sources. The approach is evaluated for the public transportation system in Montevideo, Uruguay using information about bus stop locations, bus routes, vehicle locations, ticket sales, and timetables. The estimated travel times from the proposed methodology are compared with the scheduled timetables, and relevant indicators are computed based on the findings. The most relevant quantitative results indicate a reasonably good level of punctuality in the public transportation system. Delays were between 10.5% and 13.9% during rush hours and between 8.5% and 13.7% during non-peak hours. Delays were similarly distributed for working days and weekends. In terms of speed, the results show that the average operational speed is close to 18 km/h, with short local lines exhibiting greater variability in their speed.
PB Multidisciplinary Digital / Publishing Institute (MDPI)
SN 2071-1050
YR 2023
FD 2023
LK http://hdl.handle.net/10498/32283
UL http://hdl.handle.net/10498/32283
LA eng
DS Repositorio Institucional de la Universidad de Cádiz
RD 11-nov-2026