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Title: | Travel time estimation in public transportation using bus location data |
Authors: | Massobrio, Renzo Nesmachnow, Sergio |
Type: | Preprint |
Keywords: | Travel time, public transportation, Data analysis, GPS data |
Issue Date: | 2022 |
Abstract: | The user experience of passengers using public transportation is highly sensitive to travel time. In this regard, travel time is a key input to assess the quality of service o ered by a public transportation system and to compute performance and service-level metrics. Moreover, travel time is needed to evaluate the accessibility to di erent opportunities in the city (e.g., employment, commercial activities, education) that can be reached using public transportation. This article presents a data analysis approach to estimate in-vehicle travel time in public transportation systems. Vehicle location data, bus stops locations, bus lines routes, and timetables from the public transportation system in Montevideo, Uruguay, are considered in the case study used to evaluate the
proposed approach. Results are compared against scheduled timetables and are used to compute several performance indicators of the public transportation system of the city. |
Description: | Publicado en Smart Cities. ICSC-Cities 2021. Communications in Computer and Information Science, vol 1555. Springer, Cham. |
Sponsors: | Proyecto ANII. FSDA_1_2018_1_154502 - Accesibilidad territorial, universal y sostenible: caracterización del sistema de transporte intermodal de Montevideo |
Citation: | Massobrio, R y Nesmachnow, S. Travel time estimation in public transportation using bus location data [Preprint] Publicado en: Smart Cities. ICSC-Cities 2021. Communications in Computer and Information Science, vol 1555, 2022. Springer, Cham. DOI: https://doi.org/10.1007/978-3-030-96753-6_14. |
Appears in Collections: | Publicaciones académicas y científicas - Facultad de Ingeniería |
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