Scholarlink

This paper presents a Smart Parking System Architecture enhanced by Machine Learning to enhance parking efficiency in the Smart City. The proposed system enables Value Co-creation among vehicles, parking manager, and city environment, allowing optimal city space allocation. However, ensuring cooperation across multiple city actors presents challenges in coordination and shared benefits. To address these challenges, we integrate a Multi-Agent Reinforcement Learning that improves system responsiveness by aligning with an optimized city policy.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Machine Learning Enhanced Architecture for Smart Parking Value Co-Creation

  • 会议论文

  • 发表日期：

    2026年

查看全文
  • Meryeme El Houari,
  • M’barek Elhaloui,
  • Badia Ettaki

摘要

This paper presents a Smart Parking System Architecture enhanced by Machine Learning to enhance parking efficiency in the Smart City. The proposed system enables Value Co-creation among vehicles, parking manager, and city environment, allowing optimal city space allocation. However, ensuring cooperation across multiple city actors presents challenges in coordination and shared benefits. To address these challenges, we integrate a Multi-Agent Reinforcement Learning that improves system responsiveness by aligning with an optimized city policy.