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System Level Behaviour

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Causal inference for Urban Systems

Causal effect of disruptions and policy changes on road, transit, and micro-mobility systems using observational data.

Keywords: non-parametric, causal random forest, synthetic control, difference-in-difference

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Data-driven Activity-based Modelling

New methods to fuse cellular signal, transit smart card, and travel survey data to generate synthetic population and its activity plans.

Keywords: deep generative models, cluster-based data fusion, passively-collected data

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Adaptive Infrastructure Planning

Developing surrogate models of complex activity-based models to design adaptive pathways for infrastructure interventions under uncertainties.

Keywords: charging infrastructure, uncertainties, reinforcement learning

Individual Level Behaviour

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Data-driven Choice Models

Marrying deep learning with econometrics to develop interpretable (theory-driven), yet flexible, choice models.

Keywords: deep learning, variational inference, lattice network, interpretability, monotonicity

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Modelling Neurophysiological Data

Joint modelling of lab-based brain and eye movement data of decision makers with large- scale web-based choice data.

Keywords: sequential sampling models, dynamic models, response time

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Built Environment and Human Perception

Causal effect of urban designs on the user’s perception of stress and safety by collecting brain data in immersive environment.

Keywords: virtual reality, EEG, controlled environment, objective measures

Research Articles

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

Anupriya, Prateek Bansal, and Daniel J. Graham.

Transportation Research Part A: Policy and Practice 174 (2023): 103726.

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A deep generative model for feasible and diverse population synthesis.

Kim, Eui-Jin, and Prateek Bansal.

Transportation Research Part C: Emerging Technologies 148 (2023): 104053.

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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.

Transportation Research Part C: Emerging Technologies 152 (2023): 104180.

Lab News

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Prof. Prateek Bansal received the Certificate of Recognition from the Transportation Research Board for his enthusiasm and hard work as the Stated Response Subcommittee co-chair.

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Dr. Eui-Jin Kim and Prof. Prateek Bansal presented results at the TRB 103rd Annual Meeting in Washington, DC, USA.

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Prof. Prateek Bansal and co-authors received the best paper award for the paper titled “Testing for non-linearity of agglomeration effects” at the 17th World Conference of Transport Research held in Montreal, Canada.

Team Bonding activities

Meet Our Team

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Prateek Bansal

Principal Investigator

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Vladimir Maksimenko

Research Fellow

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Canh Do Xuan

Research Fellow

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Khoa Dang Vo

Research Fellow

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Jiaxuan Ding

PhD Student

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Xinwei Li

PhD Student

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Zhuhan Jin

PhD Student

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Zheng Wu

Visiting PhD Student

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Mengyun Xu

Visiting PhD Student

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Qingyao Xin

Visiting PhD Student

Our Alumni

Eui-Jin Kim

Assistant Professor, Ajou University, South Korea