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08/09/2023
MetRoBERTa: Leveraging Traditional Customer Relationship Management Data to Develop a Transit-Topic-Aware Language Model
Transit riders' feedback provided in ridership surveys, customer relatio...
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05/24/2023
Reconstructing Transit Vehicle Trajectory Using High-Resolution GPS Data
High-resolution location (“heartbeat”) data of transit fleet vehicles is...
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05/10/2023
ST-GIN: An Uncertainty Quantification Approach in Traffic Data Imputation with Spatio-temporal Graph Attention and Bidirectional Recurrent United Neural Networks
Traffic data serves as a fundamental component in both research and appl...
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03/10/2023
The impacts of remote work on travel: insights from nearly three years of monthly surveys
Remote work has expanded dramatically since 2020, upending longstanding ...
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03/10/2023
Examining the interactions between working from home, travel behavior and change in car ownership due to the impact of COVID-19
COVID-19 has disrupted society and changed how people learn, work and li...
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03/10/2023
Fairness-enhancing deep learning for ride-hailing demand prediction
Short-term demand forecasting for on-demand ride-hailing services is one...
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03/07/2023
Deep hybrid model with satellite imagery: how to combine demand modeling and computer vision for behavior analysis?
Classical demand modeling analyzes travel behavior using only low-dimens...
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03/07/2023
Uncertainty Quantification of Spatiotemporal Travel Demand with Probabilistic Graph Neural Networks
Recent studies have significantly improved the prediction accuracy of tr...
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01/10/2023
Passenger Path Choice Estimation Using Smart Card Data: A Latent Class Approach with Panel Effects Across Days
Understanding passengers' path choice behavior in urban rail systems is ...
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01/10/2023
Predicting Drivers' Route Trajectories in Last-Mile Delivery Using A Pair-wise Attention-based Pointer Neural Network
In last-mile delivery, drivers frequently deviate from planned delivery ...
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01/06/2023
Modeling Virus Transmission Risks in Commuting with Emerging Mobility Services: A Case Study of COVID-19
Commuting is an important part of daily life. With the gradual recovery ...
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11/22/2022
TranViT: An Integrated Vision Transformer Framework for Discrete Transit Travel Time Range Prediction
Accurate travel time estimation is paramount for providing transit users...
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11/09/2022
Inferring Mobility of Care Travel Behavior From Transit Origin-Destination Data
There are substantial differences in travel behavior by gender on public...
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08/11/2022
Uncertainty Quantification of Sparse Travel Demand Prediction with Spatial-Temporal Graph Neural Networks
Origin-Destination (O-D) travel demand prediction is a fundamental chall...
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03/07/2022
The Braess Paradox in Dynamic Traffic
The Braess's Paradox (BP) is the observation that adding one or more roa...
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01/04/2022
The emerging spectrum of flexible work locations: implications for travel demand and carbon emissions
In this paper, a model is developed to predict the use of third places b...
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01/03/2022
Impact of unplanned service disruptions on urban public transit systems
This paper proposes a general unplanned incident analysis framework for ...
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09/25/2021
Equality of opportunity in travel behavior prediction with deep neural networks and discrete choice models
Although researchers increasingly adopt machine learning to model travel...
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06/24/2021
Identifying Hidden Visits from Sparse Call Detail Record Data
Despite a large body of literature on trip inference using call detail r...
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05/04/2021
Quantifying the Tradeoff Between Cybersecurity and Location Privacy
Previous data breaches that occurred in the mobility sector, such as Ube...
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04/11/2021
Proof of Travel for Trust-Based Data Validation in V2I Communication Part I: Methodology
Previous work on misbehavior detection and trust management for Vehicle-...
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02/01/2021
Comparing hundreds of machine learning classifiers and discrete choice models in predicting travel behavior: an empirical benchmark
Researchers have compared machine learning (ML) classifiers and discrete...
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01/11/2021
Individual Mobility Prediction: An Interpretable Activity-based Hidden Markov Approach
Individual mobility is driven by demand for activities with diverse spat...
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11/23/2020
Calibrating Path Choices and Train Capacities for Urban Rail Transit Simulation Models Using Smart Card and Train Movement Data
Transit network simulation models are often used for performance and ret...
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10/22/2020
Theory-based residual neural networks: A synergy of discrete choice models and deep neural networks
Researchers often treat data-driven and theory-driven models as two disp...
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01/09/2020
Dynamic Interaction between Shared Autonomous Vehicles and Public Transit: A Competitive Perspective
The emergence of autonomous vehicles (AVs) is anticipated to influence t...
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01/09/2020
Assignment-based Path Choice Estimation for Metro Systems Using Smart Card Data
Urban rail services are the principal means of public transportation in ...
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09/16/2019
Deep Neural Networks for Choice Analysis: Architectural Design with Alternative-Specific Utility Functions
Whereas deep neural network (DNN) is increasingly applied to choice anal...
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09/09/2019
Estimating the potential for shared autonomous scooters
Recent technological developments have shown significant potential for t...
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01/02/2019
Multitask Learning Deep Neural Network to Combine Revealed and Stated Preference Data
It is an enduring question how to combine revealed preference (RP) and s...
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12/11/2018
Using Deep Neural Network to Analyze Travel Mode Choice With Interpretable Economic Information: An Empirical Example
Deep neural network (DNN) has been increasingly applied to microscopic d...
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08/05/2018