Causal AI Framework for Unit Selection in Optimizing Electric Vehicle Procurement

Published: 21 Feb 2024, Last Modified: 21 Feb 2024SAI-AAAI2024 PosterEveryoneRevisionsBibTeXCC BY 4.0
Keywords: Causality, Counterfactual, Electric Vehicle, Carbon Emission
Abstract: Electric vehicles (EVs) are generally considered more environmental sustainable than internal combustion engine vehicles (ICEVs). Government and policy makers may want to incentivize multi-vehicle households that, if purchsed a new EV, would use their EV to replace a large portion of their ICEV mileage. It is hence important to analyze how EV procurement affects annual EV mileage for different households. Given that many relevant data, especially experimental data are often unavailable in the real-world, we need causal analysis tools to answer this question. Additionally, we aim to compare the expected EV mileage of different combination of vehicles a household owns. It is impossible to observe both combinations since only one might happen, which makes causal inference challenging. In this paper, we construct a causal AI framework utilizing counterfactual reasoning methods to solve this problem.
Submission Number: 6