A Control Framework for Socially-Optimal Emerging Mobility Systems

TL;DR

This paper proposes a control framework for connected and automated vehicles to optimize travel demand, improve efficiency, and ensure equity in transportation, addressing rebound effects and promoting socially optimal mobility.

Contribution

It introduces a novel control framework that distributes travel demand among CAVs to achieve a socially optimal, efficient, and equitable transportation system.

Findings

Framework effectively reduces vehicle miles traveled.

System improves energy efficiency and travel time.

Ensures equitable access in mobility systems.

Abstract

Connected and automated vehicles (CAVs) provide the most intriguing opportunity for enabling users to significantly improve safety and transportation efficiency by monitoring network conditions and making better operating decisions. CAVs, however, could alter the tendency to travel, eventually leading to a high traffic demand and causing rebound effects (e.g., increasing vehicle miles traveled). This chapter provides a control framework to distribute travel demand in a given transportation network, resulting in a socially optimal mobility system that travelers would be willing to accept. A "socially optimal mobility system" implies a mobility system that (1) is efficient (in terms of energy consumption and travel time), (2) mitigates rebound effects, and (3) ensures equity in transportation.