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Penalty-based strategies, such as congestion pricing, have been employed to improve traffic network efficiency, but they face criticism for their negative impact on users and equity concerns. Collaborative routing, which allows users to negotiate route choices, offers a solution that considers individual heterogeneity. Personalized incentives can encourage such collaboration and are more politically acceptable than penalties. This study proposes a collaborative routing strategy that uses personalized incentives to guide users towards desired traffic states while promoting multidimensional equity. Three equity dimensions are considered: accessibility equity (equal access to jobs, services, and education), inclusion equity (route suggestions and incentives that do not favor specific users), and utility equity (envy-free solutions where no user feels others have more valuable incentives). The strategy prioritizes equitable access to societal services and activities, ensuring accessibility equity in routing solutions. Inclusion equity is maintained through non-negative incentives that consider user heterogeneity without excluding anyone. An envy-free compensation mechanism achieves utility equity by eliminating envy over incentive-route bundles. A constrained traffic assignment (CTA) formulation and consensus optimization variant are then devised to break down the centralized problem into smaller, manageable parts and a decentralized algorithm is developed for scalability in large transportation networks and user populations. Numerical studies investigate the model's enhancement of equity dimensions and the impact of hyperparameters on system objective tradeoffs and demonstrate the algorithm convergence.
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This content will become publicly available on June 1, 2026
Differential Game Theoretic Models for Designing Water Conservation Incentives
The growing concern over water scarcity and the management of freshwater is common worldwide. Voluntary incentives, such as payments offered to water users, are recognized as a strategy for reducing conflicts and water consumption. A primary challenge lies in determining the allocation of these incentives among water users, taking into account socio-environmental factors. This study leverages differential game theoretic models to design incentive schemes for the network of water users, geographically distributed across a river network. Two networks of water users are considered: those who utilize groundwater and those who rely on surface water for agricultural purposes. A nongovernmental organization (NGO) participates as another key player, providing conservation incentives to encourage water users to reduce their consumption. The proposed model considers both vertical and horizontal interactions within the network of players. By considering the unique characteristics of each water user, the NGO aims to introduce an incentive scheme designed for each water user. Addressing the challenge of model scalability becomes crucial as the number of players or water users within each network increases, in order to identify optimal decisions. Thus, we propose solution methods for both convex and nonconvex decision problems using Karush-Kuhn-Tucker conditions, Value Iteration, and Basis Function Approximation methods. Finally, we perform parametric analyses to examine how parameters influence the choice of solution methods and affect the decision-making processes. Funding: Financial support from the U.S. National Science Foundation [Grant 2108003] is gratefully acknowledged.
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- Award ID(s):
- 2108003
- PAR ID:
- 10655657
- Publisher / Repository:
- Decision Analysis
- Date Published:
- Journal Name:
- Decision Analysis
- Volume:
- 22
- Issue:
- 2
- ISSN:
- 1545-8490
- Page Range / eLocation ID:
- 120 to 146
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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