| A Causal Inference Approach to Measure the Vulnerability of Urban Metro Systems N Zhang, DJ Graham, D Hörcher, P Bansal Transportation, 2021 | 8 | 2021 |
| A data fusion approach for ride-sourcing demand estimation: A discrete choice model with sampling and endogeneity corrections R Krueger, M Bierlaire, P Bansal Transportation Research Part C: Emerging Technologies 152, 104180, 2023 | 4 | 2023 |
| A deep generative model for feasible and diverse population synthesis EJ Kim, P Bansal Transportation Research Part C: Emerging Technologies 148, 104053, 2023 | 7 | 2023 |
| A Dynamic Choice Model to Estimate the User Cost of Crowding with Large Scale Transit Data P Bansal, D Hörcher, DJ Graham Journal of the Royal Statistical Society Series A: Statistics in Society 185 …, 2022 | 19* | 2022 |
| A Framework to Integrate Mode Choice in the Design of Mobility-on-Demand Systems Y Liu*, P Bansal*, R Daziano, S Samaranayake Transportation Research Part C: Emerging Technologies 105, 648-655, 2019 | 152 | 2019 |
| A general framework to forecast the adoption of novel products: A case of autonomous vehicles S Dubey, I Sharma, S Mishra, O Cats, P Bansal Transportation research part B: methodological 165, 63-95, 2022 | 19 | 2022 |
| A Generalized Continuous-Multinomial Response Model with a t-distributed Error Kernel S Dubey*, P Bansal*, RA Daziano, E Guerra Transportation Research Part B: Methodological 133, 114-141, 2020 | 6* | 2020 |
| A Minorization-Maximization (MM) Algorithm for Semiparametric Logit Models: Bottlenecks, Extensions, and Comparisons P Bansal, R Daziano, E Guerra Transportation Research Part B: Methodological 115, 17-40, 2018 | 12 | 2018 |
| A Multicriteria Decision Making Approach to Study the Barriers to the Adoption of Autonomous Vehicles A Raj, JA Kumar, P Bansal Transportation Research Part A: Policy and Practice 133, 122-137, 2020 | 99 | 2020 |
| A multinomial probit model with Choquet integral and attribute cut-offs S Dubey, O Cats, S Hoogendoorn, P Bansal Transportation Research Part B: Methodological 158, 140-163, 2022 | 6 | 2022 |
| A new flexible and partially monotonic discrete choice model EJ Kim, P Bansal Transportation Research Part B: Methodological 183, 102947, 2024 | 3 | 2024 |
| A New Spatial Count Data Model with Bayesian Additive Regression Trees for Accident Hot Spot Identification R Krueger*, P Bansal*, P Buddhavarapu Accident Analysis & Prevention 144, 105623, 2020 | 27 | 2020 |
| A New Spatial Count Data Model with Time-varying Parameters P Buddhavarapu*, P Bansal*, JA Prozzi Transportation Research Part B: Methodological 150, 566-586, 2021 | 6 | 2021 |
| A novel data fusion method to leverage passively-collected mobility data in generating spatially-heterogeneous synthetic population K Vo, EJ Kim, P Bansal Available at SSRN, 2023 | | 2023 |
| A text mining approach to elicit public perception of bike-sharing systems B Kutela, N Langa, S Mwende, E Kidando, AE Kitali, P Bansal Travel Behaviour and Society 24, 113-123, 2021 | 31 | 2021 |
| Analytical Representations of the Fundamental Diagram of Traffic Flow for Highways: A Review of Theory and Empirics Anupriya, P Bansal, DJ Graham | 1 | 2022 |
| Are American electric vehicle owners quitting? R Dua, A Edwards, U Anand, P Bansal Transportation Research Part D: Transport and Environment 133, 104272, 2024 | | 2024 |
| Are we ready to embrace connected and self-driving vehicles? A case study of Texans P Bansal, KM Kockelman Transportation, 1-35, 2016 | 335 | 2016 |
| Arriving at a decision: A semi-parametric approach to institutional birth choice in India P Bansal, RA Daziano, N Sunder Journal of choice modelling 31, 86-103, 2019 | 6 | 2019 |
| Assessing public opinions of and interest in new vehicle technologies: An Austin perspective P Bansal, KM Kockelman, A Singh Transportation Research Part C: Emerging Technologies 67, 1-14, 2016 | 1134 | 2016 |
Dr. Kara Kockelman, P.E.Dewitt Greer Professor of Transportation Engineering, University of Texas at Austin在 mail.utexas.edu 的电子邮件经过验证
