International Journal of Comprehensive and Multidisciplinary Research

Vol. 1 No. 01 (2026)
Articles

Navigating Fleet Repositioning and Battery Longevity in Shared Electric Transit: A Critical Survey

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  • David R. Karger

Published 2026-07-02

Keywords

  • Shared Electric Mobility,
  • Fleet Rebalancing,
  • Multi-Agent Deep Reinforcement Learning,
  • Battery Remaining Useful Life,
  • Cyber-Physical Transit Systems

Abstract

The rapid deployment of shared electric fleets intensifies the conflict between spatio-temporal fleet distribution and electrochemical battery aging. This survey critically evaluates recent frameworks integrating multi-agent reinforcement learning (MARL), remaining useful life (RUL) estimation, and cyber-physical charging coordination. While decentralized control improves fleet availability and narrows supply-demand disparities, real-world utility remains constrained by grid capacity limits and volatile commuting flows. We argue that existing performance gains often reflect idealized simulation boundaries rather than genuine metropolitan dynamics. Consequently, fleet rebalancing must transcend simple spatial logistics: it operates as a coupled socio-technical system balancing immediate service accessibility, electrochemical health, and grid load constraints. Moving forward, scalable dispatch architectures must explicitly incorporate degradation kinetics under non-stationary urban and thermal conditions.

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