Acceptable planning: Influencing individual behavior to reduce transportation energy expenditure of a city

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Abstract

Our research aims at developing intelligent systems to reduce the transportation-related energy expenditure of a large city by influencing individual behavior. We introduce Copter - an intelligent travel assistant that evaluates multi-modal travel alternatives to find a plan that is acceptable to a person given their context and preferences. We propose a formulation for acceptable planning that brings together ideas from AI, machine learning, and economics. This formulation has been incorporated in Copter that produces acceptable plans in real-time. We adopt a novel empirical evaluation framework that combines human decision data with a high fidelity multi-modal transportation simulation to demonstrate a 4% energy reduction and 20% delay reduction in a realistic deployment scenario in Los Angeles, California, USA.

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Mohan, S., Rakha, H., & Klenk, M. (2019). Acceptable planning: Influencing individual behavior to reduce transportation energy expenditure of a city. Journal of Artificial Intelligence Research, 66, 555–587. https://doi.org/10.1613/jair.1.11352

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