2 citations · 4 across the 5 of their papers we have counts for
4 papers · 1 filter
Causal inference for data centric engineering
Daniel J Graham
The paper reviews methods that seek to draw causal inference from observational data and demonstrates how they can be applied to empirical problems in engineering research. It pres…
Face masks, vaccination rates and low crowding drive the demand for the London Underground during the COVID-19 pandemic
Prateek Bansal, Roselinde Kessels, Rico Krueger +1
The COVID-19 pandemic has drastically impacted people's travel behaviour and out-of-home activity participation. While countermeasures are being eased with increasing vaccination r…
A Dynamic Choice Model with Heterogeneous Decision Rules: Application in Estimating the User Cost of Rail Crowding
Prateek Bansal, Daniel Hörcher, Daniel J. Graham
Crowding valuation of subway riders is an important input to various supply-side decisions of transit operators. The crowding cost perceived by a transit rider is generally estimat…
A Causal Inference Approach to Measure the Vulnerability of Urban Metro Systems
Nan Zhang, Daniel J. Graham, Daniel Hörcher +1
Transit operators need vulnerability measures to understand the level of service degradation under disruptions. This paper contributes to the literature with a novel causal inferen…