Eco-driving Incentive Mechanisms for Mitigating Emissions in Urban Transportation

2024-10-10

arXiv.org

AI Summary

Urban transportation carbon emissions pose significant challenges for sustainable mobility governance. Method: This paper proposes a hierarchical dynamic incentive mechanism that jointly models drivers’ strategic behavior and network-level system effects. Leveraging real-time telematics data on driving behavior, the mechanism integrates principal–agent theory with game-theoretic analysis to establish, for the first time, both a first-order optimal framework—guaranteeing Nash equilibrium under truthful type reporting—and a second-order optimal framework—ensuring incentive compatibility under strategic reporting. Contribution/Results: Theoretical analysis proves the mechanism’s feasibility and incentive compatibility; moreover, under all equilibria, system-wide emission reductions strictly dominate those achieved by conventional energy-saving recommendation benchmarks. By bridging rigorous economic modeling with practical telematics infrastructure, the proposed mechanism establishes a novel paradigm for sustainable urban transport policy—rigorous in theory and implementable in engineering practice.

Technology Category

• Game Theory and Economic Paradigms: Mechanism Design
• Multiagent Systems: Mechanism Design
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Systems and Infrastructure for Web, Mobile and WoT: Sustainability and carbon-aware systems for Web, mobile, and WoT
• Security and Privacy: Large-scale security measurements

Abstract

This paper proposes incentive mechanisms that promote eco-driving in transportation networks with the over-arching objective of minimizing emissions. The transportation system operator provides the drivers with energy-efficient driving guidance throughout their trips, and their eco-driving levels are measured by how closely they follow this guidance via vehicle telematics. Drivers choose their eco-driving levels to optimize a combination of their travel times and their emissions. To obtain optimal budget allocation and recommendations for the incentive mechanism, the system operator gathers drivers' preferences, or types, to assess each driver's trip urgency and natural willingness to eco-drive. In a setting where drivers truthfully report their types, we introduce the first-best incentive mechanism and show that the obedience condition holds (i.e., drivers find it optimal to comply with the system operator's recommendations) when the recommended eco-driving profile constitutes a Nash equilibrium. Moreover, in a setting where drivers can strategically report their types, we introduce the second-best incentive mechanism and show that the proposed mechanism is incentive-compatible (i.e., drivers find it optimal to be truthful). Under this mechanism, we also show that all equilibrium outcomes are at least as good as the recommended eco-driving profile in terms of the system operator's objective. Overall, this work offers a framework for designing eco-driving incentive mechanisms while considering both the strategic behavior of individual drivers and the network effects of collective decision-making.

Problem

• Designing incentive mechanisms to promote eco-driving for emission reduction
• Addressing strategic driver behavior through truthful and obedient mechanisms
• Optimizing budget allocation and recommendations while considering network effects

Innovation

• Incentive mechanisms promote eco-driving to reduce emissions
• Vehicle telematics measure driver compliance with guidance
• Nash equilibrium ensures obedience and truthful reporting