Our Publications

2024

A new flexible and partially monotonic discrete choice model.

Eui-Jin Kim and Prateek Bansal. "A new flexible and partially monotonic discrete choice model." Transportation Research Part B: Methodological 183 (2024): 102947.

Getting it right with discrete choice experiments: Are we hot or cold?

Semra Ozdemir, Juan Marcos Gonzalez, Prateek Bansal, Vinh Anh Huynh, Ban Leong Sng, Eric Finkelstein. "Getting it right with discrete choice experiments: Are we hot or cold?" Social Science & Medicine 348 (2024): 116850.

Discrete choice experiments with eye-tracking: How far we have come and ways forward.

Prateek Bansal, Kim, Eui-Jin, and Semra Ozdemir. "Discrete choice experiments with eye-tracking: How far we have come and ways forward." Journal of Choice Modelling 51 (2024): 100478.

Inverse product differentiation logit model: Holy grail or not?

Jinghai Huo, Rubal Dua, and Prateek Bansal. Inverse product differentiation logit model: Holy grail or not? Energy Economics 131 (2024): 107379.

2023

A deep generative model for feasible and diverse population synthesis.

Kim, Eui-Jin, and Prateek Bansal. "A deep generative model for feasible and diverse population synthesis." Transportation Research Part C: Emerging Technologies 148 (2023): 104053.

Robust discrete choice models with t-distributed kernel errors

Krueger, Rico, Michel Bierlaire, Thomas Gasos, and Prateek Bansal. "Robust discrete choice models with t-distributed kernel errors." Statistics and Computing 33, no. 1 (2023): 2.

A data fusion approach for ride-sourcing demand estimation: A discrete choice model with sampling and endogeneity corrections

Krueger, Rico, Michel Bierlaire, and Prateek Bansal. "A data fusion approach for ride-sourcing demand estimation: A discrete choice model with sampling and endogeneity corrections." Transportation Research Part C: Emerging Technologies 152 (2023): 104180.

Congestion in cities: Can road capacity expansions provide a solution?

Anupriya, Prateek Bansal, and Daniel J. Graham. "Congestion in cities: Can road capacity expansions provide a solution?." Transportation Research Part A: Policy and Practice 174 (2023): 103726.

Eliciting preferences of Indians for air travel during COVID-19 pandemic

Singh, Manjinder, Prateek Bansal, Alok Raj, and Aasheesh Dixit. "Eliciting preferences of Indians for air travel during COVID-19 pandemic." Transportation Research Part A: Policy and Practice 176 (2023): 103830.

Examining the impacts of capital investment in London’s Underground: A long-term analysis

Xuto, Praj, Prateek Bansal, Richard J. Anderson, Daniel J. Graham, Daniel Hörcher, and Alexander Barron. "Examining the impacts of capital investment in London’s Underground: A long-term analysis." Transportation Research Part A: Policy and Practice 175 (2023): 103744.

Surge pricing and consumer surplus in the ride-hailing market: Evidence from China

Xu, Min, Prateek Bansal, Anupriya. "Surge pricing and consumer surplus in the ride-hailing market: Evidence from China." Travel Behaviour and Society 33 (2023): 100638.

The gender productivity gap in the ride-hailing market

Min, Xu, and Prateek Bansal. "The gender productivity gap in the ride-hailing market." Travel Behaviour and Society 32 (2023): 100569.

Eliciting mobility preferences of Indians for E-rickshaws: Evidence from Gurugram

Bansal, Prateek, Ravi Gadepalli, and Laila AitBihiOuali. "Eliciting mobility preferences of Indians for E-rickshaws: Evidence from Gurugram." Transport Policy 134 (2023): 19-30.

Optimal congestion control strategies for near-capacity urban metros: Informing intervention via fundamental diagrams

Anupriya, Graham, Graham, Daniel J., Prateek Bansal, Daniel Hörcher, and Richard Anderson. "Optimal congestion control strategies for near-capacity urban metros: Informing intervention via fundamental diagrams." Physica A: Statistical Mechanics and its Applications 609 (2023): 128390.

2022

A dynamic choice model to estimate the user cost of crowding with large scale transit data.

Bansal, Prateek, Daniel Hörcher, and Daniel J. Graham. "A dynamic choice model to estimate the user cost of crowding with large scale transit data." Journal of the Royal Statistical Society: Series A (2022): 1-25.

Fuel consumption elasticities, rebound effect and feebate effectiveness in the Indian and Chinese new car markets

Bansal, Prateek, and Rubal Dua. "Fuel consumption elasticities, rebound effect and feebate effectiveness in the Indian and Chinese new car markets." Energy Economics 113 (2022): 106192.

Modelling animal-vehicle collision counts across large networks using a Bayesian Hierarchical model with time-varying parameters

Gurumurthy Krishna, Prateek Bansal, Kara M. Kockelman, and Zili Li. "Modelling animal-vehicle collision counts across large networks using a Bayesian Hierarchical model with time-varying parameters." Analytic Methods in Accident Research (2022): 100231.

A General Framework to Forecast the Adoption of Novel Products: A Case of Autonomous Vehicles

Dubey, Subodh, Ishant Sharma, Sabyasachee Mishra, Oded Cats, and Prateek Bansal. "A General Framework to Forecast the Adoption of Novel Products: A Case of Autonomous Vehicles." Transportation Research Part B: Methodological 165(2022):63-95.

A Multinomial Probit Model with Choquet Integral and Attribute Cut-offs

Dubey, Subodh, Oded Cats, Serge Hoogendoorn, and Prateek Bansal. "A Multinomial Probit Model with Choquet Integral and Attribute Cut-offs." Transportation Research Part B: Methodological 148(2022): 140-163.

Modelling the Propagation of Infectious Disease via Transportation Networks

Anupriya, Graham, Daniel J., and Prateek Bansal. "Modelling the Propagation of Infectious Disease via Transportation Networks." Nature Scientific Report, 12, 20572 (2022).

Designed quadrature to approximate integrals in maximum simulated likelihood estimation

Bansal, Prateek, Vahid Keshavarzzadeh, Angelo Guevara, Ricardo A. Daziano, and Shanjun Li. Designed quadrature to approximate integrals in maximum simulated likelihood estimation.” The Econometrics Journal 25, no. 2 (2022): 301-321.

Detecting metro service disruptions via large-scale vehicle location data

Zhang, Nan, Daniel J. Graham, Prateek Bansal, and Daniel Hörcher. "Detecting metro service disruptions via large-scale vehicle location data." Transportation Research Part C: Emerging Technologies 144 (2022): 103880.

Integration of Charging Behavior into Infrastructure Planning of Electric Vehicles: A Systematic Review and Framework

Patil, Priyadarshan, Khashayar Kazemzadeh, and Prateek Bansal. "Integration of Charging Behavior into Infrastructure Planning of Electric Vehicles: A Systematic Review and Framework." Sustainable Cities and Society (2022): 104265.

Preferences of using London Underground during the COVID-19 pandemic

Bansal Prateek, Roselinde Kessels, Rico Krueger, and Daniel J Graham. "Preferences of using London Underground during the COVID-19 pandemic". Transportation Research Part A: Policy and Practice 160(2022): 45-60.

COVID-19 vaccine preferences in IndiaCOVID-19 vaccine preferences in India

Bansal, Prateek, Alok Raj, Dhirendra Mani Shukla, and Naveen Sunder. "COVID-19 vaccine preferences in India." Vaccine 40, No. 15 (2022): 2242-2246.

Modeling automated vehicle crashes with a focus on vehicle at-fault, collision type, and injury outcome

Kutela, Boniphace, Raul Avelar, Prateek Bansal. "Modeling automated vehicle crashes with a focus on vehicle at-fault, collision type, and injury outcome." Journal of Transportation Engineering, Part A: Systems 148, no. 6 (2022): 04022024.

Cost drivers of electric bus contracts: analysis of 33 Indian cities

Gadepalli Ravi, Sushmitha Gumireddy, and Prateek Bansal. “Cost drivers of electric bus contracts: analysis of 33 Indian cities.” Transportation Research Record (2022): 03611981221088593.

Correlates of the COVID-19 vaccine hesitancy among Indians

Bansal, Prateek, Alok Raj, and Rajesh Kumar Sinha. "Correlates of the COVID-19 vaccine hesitancy among Indians." Asia Pacific Journal of Public Health (2022): 10105395221077065.

2021

A new spatial count data model with time-varying parameters

Buddhavarapu, Prasad*, Prateek Bansal*, and Jorge A. Prozzi. "A new spatial count data model with time-varying parameters." Transportation Research Part B: Methodological 150(2021): 566-586.

Fast Bayesian estimation of spatial count data models

Bansal, Prateek*, Rico Krueger*, and Daniel J. Graham. "Fast Bayesian estimation of spatial count data models." Computational Statistics and Data Analysis 157 (2021): 107152.

Electric bike level of service: A review and research agenda

Kazemzadeh, Khashayar, and Prateek Bansal. "Electric bike level of service: A review and research agenda." Sustainable Cities and Society (2021): 103413.

Evaluating the predictive abilities of mixed logit models with unobserved inter- and intra-individual heterogeneity

Krueger Rico, Michel Bierlaire, Ricardo A. Daziano, Taha H. Rashidi, and Prateek Bansal. "Evaluating the predictive abilities of mixed logit models with unobserved inter- and intra-individual heterogeneity." Journal of Choice Modelling (2021):100323.

Willingness to pay and attitudinal preferences of Indian consumers for electric vehicles

Bansal, Prateek, Rajeev Ranjan Kumar, Alok Raj, Subodh Dubey, and Daniel J. Graham “Willingness to pay and attitudinal preferences of Indian consumers for electric vehicles.” Energy Economics (2021):105340.

Electric bike riding navigation comfort in pedestrian crowds

Kazemzadeh, Khashayar, and Prateek Bansal. "Electric bike riding navigation comfort in pedestrian crowds." Sustainable Cities and Society (2021): 102841.

Fuel economy valuation and preferences of Indian two-wheeler buyers

Bansal, Prateek, Rubal Dua, Rico Krueger, and Daniel J. Graham. “Fuel economy valuation and preferences of Indian two-wheeler buyers.” Journal of Cleaner Production (2021): 126328.

A causal inference approach to measure the vulnerability of urban metro systems

Zhang, Nan, Daniel J. Graham, Daniel Hörcher, and Prateek Bansal. "A causal inference approach to measure the vulnerability of urban metro systems." Transportation (2021).

A text mining approach to elicit the public perception of bike-sharing systems

Kutela, Boniphace, Neema Langa, Sia Mwende, Emmanuel Kidando, Angela Kitali, and Prateek Bansal. "A text mining approach to elicit the public perception of bike-sharing systems." Travel Behaviour and Society 24(2021): 113-123.

2020

Bayesian estimation of mixed multinomial logit models: Advances & simulation-based evaluations

Bansal, Prateek*, Rico Krueger*, Michel Bierlaire, Ricardo A. Daziano, and Taha H. Rashidi. "Bayesian estimation of mixed multinomial logit models: Advances & simulation-based evaluations." Transportation Research Part B: Methodological 131(2020): 124-142.

A generalized continuous-multinomial response model with a t-distributed error kernel

Dubey, Subodh*, Prateek Bansal*, Ricardo A. Daziano, and Erick Guerra. "A generalized continuous-multinomial response model with a t-distributed error kernel." Transportation Research Part B: Methodological 133(2020): 114-141.

A new spatial count data model with Bayesian Additive Regression Trees for accident hot spot identification

Krueger, Rico*, Prateek Bansal*, and Prasad Buddhavarapu. "A new spatial count data model with Bayesian Additive Regression Trees for accident hot spot identification." Accident Analysis and Prevention 144(2020): 105623.

A new spatial count data model with Bayesian Additive Regression Trees for accident hot spot identification

Krueger, Rico*, Prateek Bansal*, and Prasad Buddhavarapu. "A new spatial count data model with Bayesian Additive Regression Trees for accident hot spot identification." Accident Analysis and Prevention 144(2020): 105623.

Understanding the costs of urban rail transport operations

Jose M. Carbo, Richard J. Anderson, Prateek Bansal. “Understanding the costs of urban rail transport operations.” Transportation Research Part B: Methodological 138(2020): 292-316.

Eliciting Preferences of Ridehailing Users and Drivers: Evidence from the United States

Bansal, Prateek, Akanksha Sinha, Rubal Dua, and Ricardo Daziano. "Eliciting Preferences of Ridehailing Users and Drivers: Evidence from the United States." Travel Behaviour and Society 20(2020): 225-236.

Quantifying the ex-post causal impact of differential pricing on commuter trip scheduling in Hong Kong

Anupriya, Daniel J. Graham, Daniel Hörcher, Richard J. Anderson, Prateek Bansal. "Quantifying the ex-post causal impact of differential pricing on commuter trip scheduling in Hong Kong." Transportation Research Part A: Policy and Practice 141(2020): 16-34.

A multicriteria decision making approach to study the barriers to the adoption of autonomous vehicles

Raj, Alok, J. Ajith Kumar, and Prateek Bansal. "A multicriteria decision making approach to study the barriers to the adoption of autonomous vehicles." Transportation Research Part A: Policy and Practice 133(2020): 122-137.

2019

A framework to integrate mode choice in the design of mobility-on-demand systems

Liu, Yang*, Prateek Bansal*, Ricardo Daziano, and Samitha Samaranayake. "A framework to integrate mode choice in the design of mobility-on-demand systems." Transportation Research Part C: Emerging Technologies 105(2019): 648-665.

Impact of discerning reliability preferences of riders on the demand for mobility-on-demand services

Bansal, Prateek*, Yang Liu*, Ricardo Daziano, and Samitha Samaranayake. "Impact of discerning reliability preferences of riders on the demand for mobility-on-demand services." Transportation Letters (2019): 1-5.

Flexible estimates of heterogeneity in crowding valuation in the New York City subway

Bansal, Prateek, Ricardo Hurtubia, Alejandro Tirachini, and Ricardo A. Daziano. "Flexible estimates of heterogeneity in crowding valuation in the New York City subway." Journal of Choice Modelling 31(2019): 124-140.

Arriving at a decision: A semi-parametric approach to institutional birth choice in India

Bansal, Prateek, Ricardo A. Daziano, and Naveen Sunder. "Arriving at a decision: A semi-parametric approach to institutional birth choice in India." Journal of Choice Modelling 31(2019): 86-103.

2018

Minorization-Maximization (MM) algorithms for semiparametric logit models: Bottlenecks, extensions, and comparisons

Bansal, Prateek, Ricardo A. Daziano, and Erick Guerra. "Minorization-Maximization (MM) algorithms for semiparametric logit models: Bottlenecks, extensions, and comparisons." Transportation Research Part B: Methodological 115(2018): 17-40 .

Extending the logit-mixed logit model for a combination of random and fixed parameters

Bansal, Prateek, Ricardo A. Daziano, and Martin Achtnicht. "Extending the logit-mixed logit model for a combination of random and fixed parameters." Journal of Choice Modelling 27(2018): 88-96.

Robust network pricing and system optimization under combined long-term stochasticity and elasticity of travel demand

Bansal, Prateek, Rohan Shah, and Stephen D. Boyles. "Robust network pricing and system optimization under combined long-term stochasticity and elasticity of travel demand." Transportation 45(2018): 1389-1418.

Indian vehicle ownership and travel behaviour: A case study of Bengaluru, Delhi and Kolkata

Bansal, Prateek, Kara M. Kockelman, Will Schievelbein, and Scott Schauer-West. "Indian vehicle ownership and travel behaviour: A case study of Bengaluru, Delhi and Kolkata." Research in Transportation Economics 71(2018): 2-8.

Comparison of parametric and semiparametric representations of unobserved preference heterogeneity in logit models

Bansal, Prateek, Ricardo A. Daziano, and Martin Achtnicht. "Comparison of parametric and semiparametric representations of unobserved preference heterogeneity in logit models." Journal of Choice Modelling 27(2018): 97-113.

Influence of choice experiment designs on eliciting preferences for autonomous vehicles

Bansal, Prateek, and Ricardo A. Daziano. "Influence of choice experiment designs on eliciting preferences for autonomous vehicles." Transportation Research Procedia 32 (2018): 474-481.

Are we ready to embrace connected and self-driving vehicles? A case study of Texans

Bansal, Prateek, and Kara M. Kockelman. "Are we ready to embrace connected and self-driving vehicles? A case study of Texans." Transportation 45, no. 2 (2018): 641-675.

2017 and Earlier

Forecasting Americans’ long-term adoption of connected and autonomous vehicle technologies

Bansal, Prateek, and Kara M. Kockelman. "Forecasting Americans’ long-term adoption of connected and autonomous vehicle technologies." Transportation Research Part A: Policy and Practice 95(2017): 49-63.

Indian vehicle ownership: insights from literature review, expert interviews, and state-level model

Bansal, Prateek, and Kara M. Kockelman. "Indian vehicle ownership: insights from literature review, expert interviews, and state-level model." Journal of the Transportation Research Forum 56 (2017).

Assessing public opinions of new vehicle technologies: An Austin perspective

Bansal, Prateek, Kara M. Kockelman, and Amit Singh. "Assessing public opinions of new vehicle technologies: An Austin perspective." Transportation Research Part C: Emerging Technologies 67(2016): 1-14 .

Hybrid electric vehicle ownership and fuel economy across Texas: an application of spatial models

Bansal, Prateek, Kara M. Kockelman, and Yiyi Wang. "Hybrid electric vehicle ownership and fuel economy across Texas: an application of spatial models." Transportation Research Record 2495(2015): 53-64.

Operations of a shared autonomous vehicle fleet for the Austin, Texas market

Fagnant, Daniel J., Kara M. Kockelman, and Prateek Bansal. "Operations of a shared autonomous vehicle fleet for the Austin, Texas market." Transportation Research Record 2536(2015): 98-106.

Impacts of bus-stops on the speed of motorized vehicles under heterogeneous traffic conditions

Bansal, Prateek, Rishabh Agrawal, and Geetam Tiwari. "Impacts of bus-stops on the speed of motorized vehicles under heterogeneous traffic conditions." International Journal of Transportation Science and Technology 3(2014): 167-178.