Results 41 to 50 of about 8,907 (220)
Findings, 2020 Strava Metro data are used in bicycle planning, but there are concerns it overrepresents fitness activity. The data include a commute label, but spatial patterns of commuting versus recreational ridership are underexplored.
Jaimy Fischer +2 more
doaj +1 more source
Bus Transit Operational Efficiency Resulting from Passenger Boardings at Park-and-Ride Facilities [PDF]
, 2016 In order to save time and money by not driving to an ultimate destination, some urban commuters drive themselves a few miles to specially designated parking lots built for transit customers and located where trains or buses stop.
Niles, John S., Pogodzinski, J. M.
core +1 more source
A Worldwide State-of-the-Art Analysis for Bus Rapid Transit: Looking for the Success Formula [PDF]
, 2015 This paper’s intended contribution, in terms of providing an additional angle in the existing Bus Rapid Transit (BRT) state-of-the-art knowledge spectrum, is a dual one.
Karlsson, MariAnne, Nikitas, Alexandros
core +2 more sources
A Tale of Two Stations: Analyzing Metro Ridership with Big Data
, 2017 This paper presents a multi-dimensional case study of the Beijing metro system. In particular, we examine two non-transfer stations, Zaoying and Jiangtai, which are on the same metro line in central Beijing. Multi-source and heterogeneous data are integrated to analyze and diagnose the drastically different metro ridership at the two stations.
Ma, L, Chen, Q, Han, K, Gao, Y, Li, D
openaire +2 more sources
Modifiable Areal Unit Problem on Network Topological Measures for Public Transit Flows
Transactions in GIS, Volume 30, Issue 2, April 2026.ABSTRACT Transit flows can provide useful insights into urban mobility patterns and dynamics. Generally, the transit flows between the origin and destination locations are aggregated into areal units for statistical analysis. A well‐known issue is the modifiable areal unit problem (MAUP), where its sensitivity depends on the basic areal units.
Jiwoo Kim, Gunhak Lee
wiley +1 more source
Promet (Zagreb)Previous studies have primarily focused on the effect of the built environment on ridership during weekdays and weekends. This paper aims to investigate the spatial heterogeneity of the effect of built environment factors on ridership at metro stations ...
Zhenbao WANG +4 more
doaj +1 more source
, 2003 Choices on public transit options are choices about a city's future. Will there be congestion? Will there be high levels of air and noise pollution? Will transport be affordable? Will services be available to all?
Fjellstrom, Karl, Wright, Lloyd
core
SubeYa: A System for Predicting Passenger Demand at Train Stations
IET Intelligent Transport Systems, Volume 20, Issue 1, January/December 2026.This study addresses the challenges of urban congestion and long wait times within EL1ML by introducing SubeYa, a web‐based platform designed to predict passenger demand. By utilizing the Prophet predictive model and analysing historical data from 2019 to 2025, the system achieves a global MAE of 259.10.
Angelo Meza +2 more
wiley +1 more source
Relationships between density, transit, and household expenditures in small urban areas
Transportation Research Interdisciplinary Perspectives, 2020 This study developed three models to estimate the relationships between density, transit ridership, and household expenditures, with a focus on small urban areas.
Jeremy Mattson
doaj +1 more source
Trip Purpose Prediction with Minimal Sequential Context: A Parsimonious Machine Learning Approach
IET Intelligent Transport Systems, Volume 20, Issue 1, January/December 2026.Trips labelled ’Home’ and ’School’ were predicted with the highest accuracy, correctly identifying about 92% of those trips. ’Shopping’ and ’Dining Out’ trips were moderately well classified (∼55% each), whereas ’Leisure’ trips were more often confused with other purposes (∼29% correct), likely because leisure activities are diverse and occur under ...
Jiho Kim, Jiwoo Kim, Kyusang Kwon
wiley +1 more source