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May 29, 2026Results in EngineeringOpen Access

AI-Driven Path Planning for Autonomous Vehicles: A Review of Algorithms, Optimization, and Cooperative Strategies

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Authors

BPBaskar Ponnusamy

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Overview

Review synthesizes AI path planning advancements in autonomous vehicles, highlighting algorithms and challenges.

Key Points

  • This review aims to categorize and discuss recent advancements in AI-driven path planning for autonomous vehicles.
  • Synthesized and categorized algorithms into graph-based, sampling-based, optimization-based, learning-based, and hybrid frameworks.
  • Discussed performance objectives including collision avoidance, energy efficiency, and ride comfort.
  • Analyzed cooperative path planning methods enabled by V2X connectivity.
  • Highlighted key algorithms such as A*, D*, RRT/RRT*, and deep reinforcement learning techniques.
  • Identified major challenges including uncertainty handling, computational constraints, and safety assurance.
  • Presented future research directions focusing on unified benchmarks and robust planning solutions.

Cite This Study

Baskar Ponnusamy (2026) studied this question.

synapsesocial.com/papers/6a192cf8fab5b468c4415c2ahttps://doi.org/10.1016/j.rineng.2026.111245
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