Research
Posts
2024
Fair Incentive Mechanisms for Differentiated Services in a Public Electric Vehicle Charging Station
A major barrier to electric vehicle (EV) adoption is the lack of affordable and accessible public chargers. This thesis proposes a fair incentive mechanism for operating a public EV charging station with access to renewable energy, prioritizing users without home-based chargers, and minimizing grid power usage.
Fair Artificial Currency Incentives in Repeated Weighted Congestion Games: Equity vs. Equality
Incentive schemes utilizing artificial currencies have been explored to achieve a system-optimal resource allocation that is also fair, contrarily to state-of-the-art monetary schemes. This paper delves into the comprehensive notion of fairness by meticulously optimizing for the societal metrics of equity and equality.
2023
Urgency-aware Routing in Single Origin-destination Itineraries through Artificial Currencies
Within mobility systems, the presence of self-interested users can lead to aggregate routing patterns that are far from the societal optimum that could be achieved by centrally controlling the user’s choices. We design an urgency-aware fair incentive mechanism through artificial currencies so that the selfish behavior of the users aligns with the societally-optimal aggregate routing for single origin-destination inteneraries.
Publications
Abstract
When users access shared resources in a selfish manner, the resulting societal cost and perceived users' cost is often higher than what would result from a centrally coordinated optimal allocation. While several contributions in mechanism design manage to steer the aggregate users choices to the desired optimum by using monetary tolls, such approaches bear the inherent drawback of discriminating against users with a lower income. More recently, incentive schemes based on artificial currencies have been studied with the goal of achieving a system-optimal resource allocation that is also fair. In this resource-sharing context, this paper focuses on repeated weighted congestion game with two resources, where users contribute to the congestion to different extents that are captured by individual weights. First, we address the broad concept of fairness by providing a rigorous mathematical characterization of the distinct societal metrics of equity and equality, i.e., the concepts of providing equal outcomes and equal opportunities, respectively. Second, we devise weight-dependent and time-invariant optimal pricing policies to maximize equity and equality, and prove convergence of the aggregate user choices to the system-optimum. In our framework it is always possible to achieve system-optimal allocations with perfect equity, while the maximum equality that can be reached may not be perfect, which is also shown via numerical simulations.
BibTeX
@inproceedings{PedrosoAgazziEtAl2024EqtEql,
author = {Leonardo Pedroso and Andrea Agazzi and W. P. M. H. Heemels and Mauro Salazar},
title = {Fair Artificial Currency Incentives in Repeated Weighted Congestion Games: Equity vs. Equality},
booktitle = {63nd IEEE Conference on Decision and Control},
year = {2024},
doi = {10.48550/arXiv.2403.03999},
note = {in press}
}
[1] L. Pedroso, W.P.M.H. Heemels and M. Salazar, 'Urgency-aware Routing in Single Origin-destination Itineraries through Artificial Currencies', 62nd IEEE Conference on Decision and Control, 2023. doi: 10.1109/CDC49753.2023.10383739.
Abstract
Within mobility systems, the presence of self-interested users can lead to aggregate routing patterns that are far from the societal optimum which could be achieved by centrally controlling the users' choices. In this paper, we design a fair incentive mechanism to steer the selfish behavior of the users to align with the societally optimal aggregate routing. The proposed mechanism is based on an artificial currency that cannot be traded or bought, but only spent or received when traveling. Specifically, we consider a parallel-arc network with a single origin and destination node within a repeated game setting whereby each user chooses from one of the available arcs to reach their destination on a daily basis. In this framework, taking faster routes comes at a cost, whereas taking slower routes is incentivized by a reward. The users are thus playing against their future selves when choosing their present actions. To capture this complex behavior, we assume the users to be rational and to minimize an urgency-weighted combination of their immediate and future discomfort. To design the optimal pricing, we first derive a closed-form expression for the best individual response strategy. Second, we formulate the pricing design problem for each arc to achieve the societally optimal aggregate flows, and reformulate it so that it can be solved with gradient-free optimization methods. Our numerical simulations show that it is possible to achieve a near-optimal routing whilst significantly reducing the users' perceived discomfort when compared to a centralized optimal but urgency-unaware policy.
BibTeX
@inproceedings{PedrosoHeemelsEtAl2023KarmaParallel,
author = {Leonardo Pedroso and W. P. M. H. Heemels and Mauro Salazar},
title = {Urgency-aware Routing in Single Origin-destination Itineraries through Artificial Currencies},
booktitle = {62nd IEEE Conference on Decision and Control},
year = {2023},
doi = {10.1109/CDC49753.2023.10383739}}