Results 61 to 70 of about 18,653 (224)
SubeYa: A System for Predicting Passenger Demand at Train Stations
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
Transit Ridership of Dhaka Metro Rail
This study focuses on the future ridership of Dhaka’s under-construction metro rail. Dhaka offers an exceptional context with the world’s highest density of population. How the sociocultural condition of the city’s population would impact the future ridership of the metro rail was an interesting question. The data for the study were collected through a
openaire +1 more source
Trip Purpose Prediction with Minimal Sequential Context: A Parsimonious Machine Learning Approach
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
What are the city-wide benefits of introducing a new transit mode? Justification of a new transit mode is often based on claims of transformational change regarding mode share, ridership, or passenger-kilometers travelled (PKT).
Durba Kundu +2 more
doaj +1 more source
Changes in Transit Use and Service and Associated Changes in Driving Near a New Light Rail Transit Line, MTI Report 12-44 [PDF]
Los Angeles is pursuing possibly the most ambitious rail transit investment program in the nation with plans to open six new rail transit lines between now and 2019.
Boarnet, Marlon +3 more
core +1 more source
Passenger Flow‐Aware Train Scheduling Model for Minimising Energy Consumption in Urban Rail Systems
This study proposes a dynamic‐programming (DP)‐based train scheduling framework that models the interaction among passenger flow, train mass, and energy consumption, enabling energy‐efficient operation under time‐varying demand. Case studies on a real metro line show that the method reduces energy consumption by up to 10.8% while maintaining transport ...
Haoran Geng +4 more
wiley +1 more source
Public transit ridership offers valuable opportunities for modest amounts of daily physical activity (PA). Transit is a more feasible option for most Canadian commuters who live too far from work to walk or cycle, yet public transit usage in midsized ...
Patricia A. Collins, Ajay Agarwal
doaj +1 more source
This paper studies the coordinated scheduling and management for hybrid DRT systems offering both direct door‐to‐door rides and feeder connections to mass transit, incorporating passenger mode choice behaviour to account for heterogeneous passenger preferences in a multimodal environment.
Jingxuan Ren, Wenzhou Jin
wiley +1 more source
Public Transportation Syntheses Series: Fare, Free or Something in Between? [PDF]
Lo digital ha cambiado nuestras vidas, nuestra rutina diaria, la forma de trabajar y las relaciones sociales. Es así, que en un donde lo digital lo aborda todo, donde nos podemos conectar desde cualquiera lugar del mundo, ¿es posible crear un espacio de ...
CUTR
core +2 more sources
Understanding the relationship between travel behavior and modifiable built environment attributes is essential for promoting low‐carbon urban mobility, particularly under emerging carbon peaking and neutrality targets. While previous studies have explored this relationship, limited attention has been paid to residents’ intentions for low‐carbon travel
Liyang Hu +5 more
wiley +1 more source

