Eco-driving Incentive Mechanisms for Mitigating Emissions in Urban Transportation
<|reference_start|>Eco-driving Incentive Mechanisms for Mitigating Emissions in Urban Transportation: 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.<|reference_end|>
@article{niazi2024eco-driving,
    title={Eco-driving Incentive Mechanisms for Mitigating Emissions in Urban
  Transportation},
    author={M. Umar B. Niazi, Jung-Hoon Cho, Munther A. Dahleh, Roy Dong, Cathy Wu},
    journal={arXiv preprint arXiv:2410.07952},
    year={2024},
    archivePrefix={arXiv},
    eprint={2410.07952},
    primaryClass={cs.GT cs.SY eess.SY math.OC}
}