Biblio
Found 180 results
Filters: Author is Jinhua Zhao [Clear All Filters]
Robust Matching-Integrated Vehicle Rebalancing in Ride-hailing System with Uncertain Demand. Transportation Research Part B. 2021.
Theory-based residual neural networks: A synergy of discrete choice models and deep neural networks. Transportation Research Part B. 2021.
Adoption of Exclusive and Pooled TNC Services in Singapore and the U.S. ASCE Journal of Transportation Engineering, Part A: Systems. 2020;146(9).
Adoption of Exclusive and Pooled TNC Services in Singapore and the U.S.. In: Transportation Research Board 99th Annual Meeting. Washington, D.C.; 2020.
Aptitudes for Regulating Autonomous Vehicles: A Survey of Municipal Officials. In: Transportation Research Board 99th Annual Meeting. Washington, D.C.; 2020.
Automated Information Extraction From Textual Data: Application In Transit Disruption Management. In: Transportation Research Board 99th Annual Meeting. Washington, D.C.; 2020.
Behavioral Response to Discounted Fares for Low-income Transit Riders in Boston. In: Transportation Research Board 99th Annual Meeting. Washington, D.C.; 2020.
Bundled Mobility Passes in Chicago: Consumer Preference and Revenue Implications. In: Transportation Research Board 99th Annual Meeting. Washington, D.C.; 2020.
Capacity-Constrained Network Performance Model for Urban Rail Systems. Transportation Research Record. 2020.
Deep Neural Networks for Choice Analysis: Architecture Design with Alternative-Specific Utility Functions. Transportation Research Part C. 2020.
Deep Neural Networks for Choice Analysis: Extracting Complete Economic Information for Interpretation. Transportation Research Part C: Emerging Technologies. 2020.
Discovering Latent Activity Patterns from Transit Smart Card Data: A Spatiotemporal Topic Model. Transportation Research Part C. 2020.
Dynamic Origin-Destination Prediction in Urban Rail Systems: A Multi-resolution Spatio-Temporal Deep Learning Approach. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS. 2020.
Estimating the Potential for Shared Autonomous Scooters. IEEE Transactions on Intelligent Transportation Systems. 2020.
How does public support of transportation policies vary across countries?. In: Transportation Research Board 99th Annual Meeting. Washington, D.C.; 2020.
How does Ridesourcing Substitute for Public Transit? A geospatial perspective in Chengdu, China. Journal of Transport Geography. 2020.
ICT’s Impacts on Ride-hailing Use and Individual Travel. Transportation Research Part A. 2020.
Latent Attitudes of Existing Travel Modes on Autonomous Vehicle Adoption. In: Transportation Research Board 99th Annual Meeting. Washington, D.C.; 2020.
Machine-learning-augmented analysis of textual data: application in transit disruption management. IEEE Open Journal of Intelligent Transportation Systems. 2020.
Measuring Policy Leakage of Beijing's Car Ownership Restriction in Neighboring Cities. In: Transportation Research Board 99th Annual Meeting. Washington, D.C.; 2020.
Modeling Epidemic Spreading through Public Transit using Time-Varying Encounter Network. Transportation Research Part C. 2020.
Multitask Learning Deep Neural Networks to Combine Revealed and Stated Preference Data. Journal of Choice Modelling. 2020.
Policies for autonomy: How American cities envision regulating automated vehicles. Urban Science. 2020.
Predicting Travel Mode Choice with 86 Machine Learning Classifiers: An Empirical Benchmark Study. In: Transportation Research Board 99th Annual Meeting. Washington, D.C.; 2020.
The Price of Privacy Control in Mobility Sharing. Journal of Urban Technology. 2020.