Eco-driving Incentive Mechanisms for Mitigating Emissions in Urban Transportation

TL;DR

This paper introduces incentive mechanisms to promote eco-driving in urban transportation, aiming to reduce emissions by aligning driver behavior with energy-efficient guidance through strategic and truthful reporting frameworks.

Contribution

It presents novel incentive mechanisms that ensure driver compliance and truthful reporting, explicitly targeting emissions reduction in transportation networks.

Findings

Mechanisms ensure obedience and truthfulness under different driver reporting behaviors.

Numerical simulations show effective emissions reduction with budget and driver type considerations.

Framework addresses strategic behavior and network effects without revealing system parameters.

Abstract

This paper develops incentive mechanisms for promoting eco-driving with the overarching goal of minimizing emissions in transportation networks. The system operator provides drivers with energy-efficient driving guidance throughout their trips and measures compliance through vehicle telematics that capture how closely drivers follow this guidance. Drivers optimize their behaviors based on personal trade-offs between travel times and emissions. To design effective incentives, the operator elicits driver preferences regarding trip urgency and willingness to eco-drive, while determining optimal budget allocations and eco-driving recommendations. Two distinct settings based on driver behavior are analyzed. When drivers report their preferences truthfully, an incentive mechanism ensuring obedience (drivers find it optimal to follow recommendations) is designed by implementing eco-driving recommendations as a Nash equilibrium. When drivers may report strategically, the mechanism is extended to be both obedient and truthful (drivers find it optimal to report truthfully). Unlike existing works that focus on congestion or routing decisions in transportation networks, our framework explicitly targets emissions reduction by incentivizing drivers. The proposed mechanism addresses both strategic behavior and network effects arising from driver interactions, without requiring the operator to reveal system parameters to the drivers. Numerical simulations demonstrate the effects of budget constraints, driver types, and strategic misreporting on equilibrium outcomes and emissions reduction.