Social Resource Allocation in a Mobility System with Connected and Automated Vehicles: A Mechanism Design Problem
Ioannis Vasileios Chremos, Andreas Malikopoulos
TL;DR
The paper tackles social resource allocation in urban mobility with connected and automated vehicles by formulating a centralized travel-time optimization and then designing an indirect mechanism to implement the optimum through strategic travelers. It introduces an indirect mechanism with messages $m_i=(\tilde{\theta}_i,\tau_i)$ and payments $t_i(\mu)$ that incorporate edge-specific tolls, price alignment, and penalties, guaranteeing a Nash equilibrium that coincides with the centralized solution. The mechanism achieves budget balance, individual rationality, and strong implementation by leveraging Lagrange multipliers and KKT conditions to ensure truthful reporting and socially efficient travel-time allocations. The work provides a rigorous framework for mitigating rebound effects in CAV-enabled mobility and sets the stage for simulation-based validation under varying traffic scenarios and socio-economic traveler models.
Abstract
In this paper, we investigate the social resource allocation in an emerging mobility system consisting of connected and automated vehicles (CAVs) using mechanism design. CAVs provide the most intriguing opportunity for enabling travelers to monitor mobility system conditions efficiently and make better decisions. However, this new reality will influence travelers' tendency-of-travel and might give rise to rebound effects, e.g., increased-vehicle-miles traveled. To tackle this phenomenon, we propose a mechanism design formulation that provides an efficient social resource allocation of travel time for all travelers. Our focus is on the socio-technical aspect of the problem, i.e., by designing appropriate socio-economic incentives, we seek to prevent potential rebound effects. In particular, we propose an economically inspired mechanism to influence the impact of the travelers' decision-making on the well-being of an emerging mobility system.