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Deep Reinforcement Learning for Shared Autonomous Vehicles (SAV) Fleet Management

arXiv 2201.05720 ↗First posted 15 Jan 2022cs.LG cs.ROcited by 0

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Abstract (arXiv)

Shared Automated Vehicles (SAVs) Fleets companies are starting pilot projects nationwide. In 2020 in Fairfax Virginia it was announced the first Shared Autonomous Vehicle Fleet pilot project in Virginia. SAVs promise to improve quality of life. However, SAVs will also induce some negative externalities by generating excessive vehicle miles traveled (VMT), which leads to more congestions, energy consumption, and emissions. The excessive VMT are primarily generated via empty relocation process. Reinforcement Learning based algorithms are being researched as a possible solution to solve some of these problems: most notably minimizing waiting time for riders. But no research using Reinforcement Learning has been made about reducing parking space cost nor reducing empty cruising time. This study explores different textbfReinforcement Learning approaches and then decide the best approach to help minimize the rider waiting time, parking cost, and empty travel

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 2 of its 17 references that are in the map. First posted on arXiv 15 Jan 2022.

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2 of 17 references.

References · 2

  1. 2013Playing Atari with Deep Reinforcement Learningcited by 3,274
  2. 2017Adaptive Traffic Signal Control: Deep Reinforcement Learning Algorithm with Experience Replay and Target Networkcited by 16

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