Results 31 to 40 of about 15,432 (158)
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
Improving Demand Modeling in California\u27s Rail Transit System [PDF]
, 2018 This paper analyzes urban rail-fare elasticity and compares the results across four California transit systems. A method of Internet search is adopted to collect monthly transit-fare records from 2002 to 2013.
Liu, Rui
core +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
, 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
Passenger Flow‐Aware Train Scheduling Model for Minimising Energy Consumption in Urban Rail Systems
IET Intelligent Transport Systems, Volume 20, Issue 1, January/December 2026.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
IET Intelligent Transport Systems, Volume 20, Issue 1, January/December 2026.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
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
The eyes of the beholder: Perceived barriers to successful drug repurposing
British Journal of Pharmacology, Volume 183, Issue 2, Page 219-233, January 2026.Despite tremendous advances in new drug development over recent decades, the medical needs of an ever increasing and ageing global population are still significantly unmet. Drug repurposing (DR)—finding new therapeutic uses for existing medicinal substances and products—offers a promising strategy by potentially reducing development time, costs and ...
Zsuzsanna Ida Petykó +11 more
wiley +1 more source
Full Potential of Future Robotaxis Achievable with Trip-Based Subsidies and Fees Applied to the For-Hire Vehicles of Today [PDF]
, 2019 As described by Grush and Niles in their textbook, The End of Driving: Transportation Systems and Public Policy Planning for Autonomous Vehicles, there are two distinct market states for the future of automobility as vehicles become increasingly ...
Niles, John
core +1 more source
Journal of Advanced Transportation, Volume 2026, Issue 1, 2026.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