Prateek Bansal
Biographic Data
| ID | 3930874 |
|---|---|
| NAME | Prateek Bansal |
| GIVEN NAMES | Prateek |
| FAMILY NAME | Bansal |
| SIGNATURE | BANSAL P |
| AFFILIATIONS | National University of Singapore |
| ORCID | 0000-0001-6851-8461 |
| VERIFIED | Yes |
| TOTAL WORKS | 8 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 8 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2016 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Strategic planning of charging infrastructure for shared electric vehicles
The rapid electrification of ride-hailing mobility requires that fast-charging infrastructure be ready to support the dynamic charging needs of shared electric vehicle (SEV) fleets. Deploying city-wide fast-charging stations requires determining the timing, locations, and number of chargers at each station over multiple planning phases, while managing stochastic charging demand, induced demand from enhanced services, and constraints like grid cap…
Multi-period Charging Infrastructure Planning under Uncertainty
Getting it right with discrete choice experiments
Electric bike navigation comfort in pedestrian crowds
The emergence of electric bikes (e-bikes) has brought a paradigm shift in shared mobility with a promise to move towards the mission of sustainable cities. Whereas an in-depth understanding of e-bike riding characteristics is crucial to effectively design the infrastructure for active mobility, it remains an open area of research. We take the first step towards modelling the e-bike navigation comfort in pedestrian crowds. Through a laboratory-con…
A causal inference approach to measure the vulnerability of urban metro systems
Transit operators need vulnerability measures to understand the level of service degradation under disruptions. This paper contributes to the literature with a novel causal inference approach for estimating station-level vulnerability in metro systems. The empirical analysis is based on large-scale data on historical incidents and population-level passenger demand. This analysis thus obviates the need for assumptions made by previous studies on h…
Are we ready to embrace connected and self-driving vehicles? A case study of Texans
Robust network pricing and system optimization under combined long-term stochasticity and elasticity of travel demand
Assessing public opinions of and interest in new vehicle technologies
No prominent works on this page.
Assessing public opinions of and interest in new vehicle technologies
Are we ready to embrace connected and self-driving vehicles? A case study of Texans
Robust network pricing and system optimization under combined long-term stochasticity and elasticity of travel demand
Electric bike navigation comfort in pedestrian crowds
The emergence of electric bikes (e-bikes) has brought a paradigm shift in shared mobility with a promise to move towards the mission of sustainable cities. Whereas an in-depth understanding of e-bike riding characteristics is crucial to effectively design the infrastructure for active mobility, it remains an open area of research. We take the first step towards modelling the e-bike navigation comfort in pedestrian crowds. Through a laboratory-con…
A causal inference approach to measure the vulnerability of urban metro systems
Transit operators need vulnerability measures to understand the level of service degradation under disruptions. This paper contributes to the literature with a novel causal inference approach for estimating station-level vulnerability in metro systems. The empirical analysis is based on large-scale data on historical incidents and population-level passenger demand. This analysis thus obviates the need for assumptions made by previous studies on h…
Multi-period Charging Infrastructure Planning under Uncertainty
Getting it right with discrete choice experiments
Strategic planning of charging infrastructure for shared electric vehicles
The rapid electrification of ride-hailing mobility requires that fast-charging infrastructure be ready to support the dynamic charging needs of shared electric vehicle (SEV) fleets. Deploying city-wide fast-charging stations requires determining the timing, locations, and number of chargers at each station over multiple planning phases, while managing stochastic charging demand, induced demand from enhanced services, and constraints like grid cap…
Computer Science (6 works) · Economics (5 works) · Transportation Planning and Optimization (5 works) · Engineering (4 works) · Transport engineering (4 works) · Transportation and Mobility Innovations (4 works) · Business (3 works) · Computer security (3 works) · Econometrics (3 works) · Urban Transport and Accessibility (3 works)