Acceptable Planning: Influencing Individual Behavior to Reduce Transportation Energy Expenditure of a City

Acceptable Planning: Influencing Individual Behavior to Reduce Transportation Energy Expenditure of a City

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...

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Veröffentlicht in:The Journal of artificial intelligence research 2019-01, Vol.66, p.555-587
Hauptverfasser: Mohan, Shiwali, Rakha, Hesham, Klenk, Matt
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Sprache:eng
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Artificial intelligence
Machine learning
Reduction
Transportation energy
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container_title The Journal of artificial intelligence research
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creator Mohan, Shiwali
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description 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.   This article is part of the special track on AI and Society.
doi_str_mv 10.1613/jair.1.11352
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subjects Artificial intelligence
Machine learning
Reduction
Transportation energy
title Acceptable Planning: Influencing Individual Behavior to Reduce Transportation Energy Expenditure of a City
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