Submissions from 2023
Short-Term Passenger Flow Prediction Using a Bus Network Graph Convolutional Long Short-Term Memory Neural Network Model, Asiye Baghbani, Nizar Bouguila, and Zachary Patterson
Forecasting passenger flows and headway at train level for a public transport line: Focus on atypical situations, Thomas Bapaume, Etienne Côme, Mostafa Ameli, Jérémy Roos, and Latifa Oukhellou
Short-term forecasting of origin-destination matrix in transit system via a deep learning approach, Yuxin He, Yang Zhao, and Kwok-Leung Tsui
Predictability of short-term passengers’ origin and destination demands in urban rail transit, Fang Yang, Chunyan Shuai, Qian Qian, Wencong Wang, Mingwei He, Min He, and Jaeyoung Lee
Linkage mechanism of public transport subsidy: considering passenger ridership, cost, fare and service quality, Chunqin Zhang, Meng Liu, Daoyou Wang, Aning Ni, Guangnian Xiao, and Weite Lu
Improved imputation of rule sets in class association rule modeling: application to transportation mode choice, Jiajia Zhang, Tao Feng, Harry Timmermans, and Zhengkui Lin
Submissions from 2022
Intrapersonal variability in public transport path choice due to changes in service reliability, Ulrik Berggren, Carmelo D'Agostino, Helena Svensson, and Karin Brundell-Freij
A direct demand model for bus transit ridership in Bengaluru, India, L. Deepa, Abdul Rawoof Pinjari, Sangram Krishna Nirmale, Karthik K. Srinivasan, and Tarun Rambha
Forecasting using dynamic factor models with cluster structure at Barcelona subway stations, I. Mariñas-Collado, A. E. Sipols, M. T. Santos-Martin, and E. Frutos-Bernal
Traveller behaviour in public transport in the early stages of the COVID-19 pandemic in the Netherlands, Sanmay Shelat, Oded Cats, and Sander van Cranenburgh
Characterising public transport shifting to active and private modes in South American capitals during the COVID-19 pandemic, Jose Agustin Vallejo-Borda, Ricardo Giesen, Paul Basnak, José P. Reyes, Beatriz Mella Lira, Matthew J. Beck, David A. Hensher, and Juan de Dios Ortúzar
Bus OD matrix reconstruction based on clustering Wi-Fi probe data, Yunshan Wang, Wenbo Zhang, Tianli Tang, Dazhong Wang, and Zhiyuan Liu
Meta-analysis of price elasticities of travel demand in great britain: Update and extension, Mark Wardman
Submissions from 2021
Understanding Contextual Attractiveness Factors of Transit Orientated Shopping Mall Developments (Tosmds) for Shopping Mall Passengers on the Dubai Metro Red Line, Ayman Abutaleb, Kevin McDougall, Marita Basson, Rumman Hassan, and Muhammad Nateque Mahmood
Incorporating travel behavior regularity into passenger flow forecasting, Zhanhong Cheng, Martin Trépanier, and Lijun Sun
Medium-term public transit route ridership forecasting: What, how and why? A case study in Lyon, Oscar Egu and Patrick Bonnel
Mode shift to micromobility, M. Ensor, O. Maxwell, and O. Bruce
People-focused and Near-term Public Transit Performance Analysis, Alex Karner
Forecasting bus ridership using a “Blended Approach”, Catherine T. Lawson, Alex Muro, and Eric Krans
A multi-task memory network with knowledge adaptation for multimodal demand forecasting, Can Li, Lei Bai, Wei Liu, Lina Yao, and S. Travis Waller
Hybrid Approach Combining Modified Gravity Model and Deep Learning for Short-Term Forecasting of Metro Transit Passenger Flows, Loutao Shen, Zengzhe Shao, Yuansheng Yu, and Xiqun (Michael) Chen
Multi-stage deep learning approaches to predict boarding behaviour of bus passengers, Tianli Tang, Achille Fonzone, Ronghui Liu, and Charisma Choudhury
Short-term origin-destination demand prediction in urban rail transit systems: A channel-wise attentive split-convolutional neural network method, Jinlei Zhang, Hongshu Che, Feng Chen, Wei Ma, and Zhengbing He
A two-layer modelling framework for predicting passenger flow on trains: A case study of London underground trains, Qian Zhang, Xiaoxiao Liu, Sarah Spurgeon, and Dingli Yu
Short-term forecasts on individual accessibility in bus system based on neural network model, Yufan Zuo, Xiao Fu, Zhiyuan Liu, and Di Huang
Submissions from 2020
Addressing transit mode location bias in built environment-transit mode use research, Laura Aston, Graham Currie, Md. Kamruzzaman, Alexa Delbosc, Nicholas Fournier, and David Teller
Learning and Adaptation in Dynamic Transit Assignment Models for Congested Networks, Oded Cats and Jens West
How does the built environment affect transit use by train, tram and bus?, Chris De Gruyter, Tayebeh Saghapour, Liang Ma, and Jago Dodson
Integrating demand forecasts into the operational strategies of shared automated vehicle mobility services: spatial resolution impacts, Michael Hyland, Florian Dandl, Klaus Bogenberger, and Hani Mahmassani
Assessment of the transit ridership prediction errors using AVL/APC data, You-Jin Jung and Jeffrey M. Casello
Magnitude of mode constants in transit mode choice, You-Jin Jung and Jeffrey M. Casello
Demand forecast of public transportation considering positive and negative mass effects, Ngoc T. Nguyen, Tomio Miwa, and Takyuki Morikawa
Short-term metro passenger flow forecasting using ensemble-chaos support vector regression, Zhuangbin Shi, Ning Zhang, Paul M. Schonfeld, and Jian Zhang
Trust in forecasts? Correlates with ridership forecast accuracy for fixed-guideway transit projects, Carole Turley Voulgaris
Key determinants and heterogeneous frailties in passenger loyalty toward customized buses: An empirical investigation of the subscription termination hazard of users, Jiangbo Wang, Toshiyuki Yamamoto, and Kai Liu
Modeling demand for ridesourcing as feeder for high capacity mass transit systems with an application to the planned Beirut BRT, Najib Zgheib, Maya Abou-Zeid, and Isam Kaysi
Submissions from 2019
Geographic mobility of recent immigrants and urban transit demand in the U.S.: New evidence and planning implications, Sandip Chakrabarti and Gary Painter
Current State of Practice in Transit Ridership Prediction: Results from a Survey of Canadian Transit Agencies, Ehab Diab, Dena Kasraian, Eric J. Miller, and Amer Shalaby
GIS-based transit trip allocation methods converting stop-level boarding and alighting trips into TAZ trips, You-Jin Jung and Jeffrey M. Casello
DeepPF: A deep learning based architecture for metro passenger flow prediction, Yang Liu, Zhiyuan Liu, and Ruo Jia
Employing land value capture in urban rail transit public private partnerships: Retrospective analysis of Delhi's airport metro express, Xinjian Li and Peter E.D. Love
Review of asset management for metro systems: challenges and opportunities, Alireza Mohammadi, Luis Amador-Jimenez, and Fuzhan Nasiri
Aggregation techniques for frequency assignment in public transportation, Benjamin Otto
Examining determinants of rail ridership: a case study of the Orlando SunRail system, Moshiur Rahman, Shamsunnahar Yasmin, and Naveen Eluru
Ridership Ramp-Up? Initial Ridership Variation on New Rail Transit Projects, Jill Elizabeth Shinn and Carole Turley Voulgaris
The sensitivity of rail demand to variations in motoring costs: Findings from a comparison of methods, Mark Wardman, Andrew Hatfield, Jeremy Shires, and Mahmoud Ishtaiwi
Submissions from 2018
Evaluating the Ability of Transit Direct Ridership Models to Forecast Medium-Term Ridership Changes: Evidence from San Francisco, Richard A. Mucci and Gregory D. Erhardt
Modeling park-and-ride location choice of heterogeneous commuters, Hao Pang and Alireza Khani
Determining Effective Sample Size to Calibrate a Transit Assignment Model: A Bayesian Perspective, Mohadeseh Rahbar, Mark Hickman, Mahmoud Mesbah, and Ahmad Tavassoli
Train timetable design under elastic passenger demand, Tomáš Robenek, Shadi Sharif Azadeh, Yousef Maknoon, Matthieu de Lapparent, and Michel Bierlaire
Enhancing flexible transport services with demand-anticipatory insertion heuristics, Matti van Engelen, Oded Cats, Henk Post, and Karen Aardal
Improving predictions of public transport usage during disturbances based on smart card data, Menno D. Yap, S. Nijënstein, and Niels van Oort
Development of railway station choice models to improve the representation of station catchments in rail demand models, Marcus A. Young and Simon P. Blainey
Railway station choice modelling: a review of methods and evidence, Marcus Young and Simon Blainey
Submissions from 2017
Cost and time damping: evidence from aggregate rail direct demand models, Andrew Daly, Nobuhiro Sanko, and Mark Wardman
Short-term forecasting of passenger demand under on-demand ride services: A spatio-temporal deep learning approach, Jintao Ke, Hongyu Zheng, Hai Yang, and Xiqun (Michael) Chen
Ridership estimation of a new LRT system: Direct demand model approach, Konstantinos Kepaptsoglou, Antony Stathopoulos, and Matthew G. Karlaftis
A novel passenger flow prediction model using deep learning methods, Lijuan Liu and Rung-Ching Chen
Forecasting short-term subway passenger flow under special events scenarios using multiscale radial basis function networks, Yang Li, Xudong Wang, Shuo Sun, Xiaolei Ma, and Guangquan Lu
Measuring the Accuracy of Bus Rapid Transit Forecasts, John Perry
From trend spotting to trend ’splaining: Understanding modal preference shifts in the San Francisco Bay Area, Akshay Vij, Sreeta Gorripaty, and Joan L. Walker
Submissions from 2016
Transit passengers’ behavioural intentions: the influence of service quality and customer satisfaction, Juan de Oña, Rocio de Oña, Laura Eboli, Carmen Forciniti, and Gabriella Mazzulla
Experience conditioning in commuter modal choice modelling – Does it make a difference?, David A. Hensher and Chinh Q. Ho
Use of Agent-Based Crowd Simulation to Investigate the Performance of Large-Scale Intermodal Facilities: Case Study of Union Station in Toronto, Ontario, Canada, Gregory Hoy, Erin Morrow, and Amer Shalaby
Perception of Mode-Specific Travel Time Reliability and Crowding in Multimodal Trips, Hao Li, Kun Gao, Huizhao Tu, Yueming Ding, and Lijun Sun
Factors affecting temporal changes in mode choice model parameters, Nobuhiro Sanko
Tailoring empirical research on transit access premiums for planning applications, Tao Xu and Ming Zhang
Submissions from 2015
An investigation on the performances of mode shift models in transit ridership forecasting, Ahmed Osman Idris, Khandker M. Nurul Habib, and Amer Shalaby
Dynamic Estimates of Fare Elasticity for U.S. Public Transit, Paul Schimek
Passengers’ valuations of train seating layout, position and occupancy, Mark Wardman and Paul Murphy
Submissions from 2014
Potential for mitigating greenhouse gases through expanding public transport services: A case study for Gauteng Province, South Africa, Steffen Bubeck, Jan Tomaschek, and Ulrich Fahl
Sequential Framework for Short-Term Passenger Flow Prediction at Bus Stop, Min Gong, Xiang Fei, Zhi Hu Wang, and Yun Jie Qiu
Transportation Futures: Policy Scenarios for Achieving Greenhouse Gas Reduction Targets, Andrew I. Kay, Robert B. Noland, and Caroline J. Rodier
Predicting short-term bus passenger demand using a pattern hybrid approach, Zhenliang Ma, Jianping Xing, Mahmoud Mesbah, and Luis Ferreira
A self-learning advanced booking model for railway arrival forecasting, Tsung-Hsien Tsai
Evaluating light rail sketch planning: actual versus predicted station boardings in Phoenix, Christopher Upchurch and Michael Kuby
Submissions from 2013
A GIS-based appraisal framework for new local railway stations and services, Simon P. Blainey and John M. Preston
Public transport use in Australia’s capital cities: Modelling and forecasting, Bureau of Infrastructure, Transport and Regional Economics (BITRE)
Forecasting Paratransit Services Demand – Review and Recommendations, Jay A. Goodwill and Ann Joslin
The cross elasticity between gasoline prices and transit use: Evidence from Chicago, William P. Nowak and Ian Savage
Transit Boardings Estimation and Simulation Tool (TBEST) Calibration for Guideway and BRT Modes, Steven Polzin, Rodney Bunner, and Xuehao Chu
Submissions from 2012
Improving ADA Paratransit Demand Estimation: Regional Modeling, Mark Bradley and David Koffman
Application of geographically weighted regression to the direct forecasting of transit ridership at station-level, Osvaldo Daniel Cardozo, Juan Carlos García-Palomares, and Javier Gutiérrez
A simulation of the simple Mohring model to predict patronage and value of resources consumed for enhanced bus services, Geoffrey T. Clifton and John M. Rose
Half-Mile Circle. Does It Best Represent Transit Station Catchments?, Erick Guerra, Robert Cervero, and Daniel Tischler
Forecasting the short-term metro passenger flow with empirical mode decomposition and neural networks, Yu Wei and Mu-Chen Chen
Submissions from 2011
Local station catchments: reconciling theory with reality, Simon Blainey and Samantha Evens
Development of a Mode Choice Model for Bus Rapid Transit in Santa Clara County, CA, Chun-Hung Peter Chen and George A. Naylor
Forecasting ridership for a metropolitan transit authority, Wen-Chyuan Chiang, Robert A. Russell, and Timothy L. Urban
Understanding the market for "out of normal hours" train services in Great Britain, Gareth Davies, John Segal, and Ben Condry
On the state-of-the-art demand forecasting model developed by Netherlands Railways, Bert de Vries and Jasper Willigers
Transit ridership forecasting at station level: an approach based on distance-decay weighted regression, Javier Gutiérrez, Osvaldo Daniel Cardozo, and Juan Carlos García-Palomaresa
Open Government Data and Public Transportation, Kenneth Kuhn
ClicSim - real time simulation of passenger crowding on trains and at stations, Naomi Langdon and Craig McPherson
Forecasting annual train boardings in Melbourne using time series data, John F. Odgers and Laura Andreoli van Schijndel
Spatial distribution of the journey to work by sustainable modes in Australian cities, John Stone and Paul Mees
Appraisal of factors influencing public transport patronage, Judith Wang
Submissions from 2010
Direct ridership model of Bus Rapid Transit in Los Angeles County, California, Robert Cervero, Jin Murakami, and Mark Miller
Dynamic Multi-interval Bus Travel Time Prediction Using Bus Transit Data, Hyunho Chang, Dongjoo Park, Seungjae Lee, Hosang Lee, and Seungkirl Baek
