Research on Intelligent Edge Computing for the Internet of Vehicles (IoV) focuses on leveraging edge computing and AI-driven intelligence to enable low-latency, reliable, and context-aware services for connected vehicles and transportation systems. This area addresses challenges such as high mobility, dynamic network topology, heterogeneous vehicular devices, massive data streams from sensors, and stringent latency and safety requirements. Key research directions include AI-assisted task offloading and resource allocation at edge nodes, real-time traffic prediction and route optimization, and edge-enabled vehicular data analytics for autonomous driving and safety applications. Other emerging topics involve collaborative edge–cloud frameworks for vehicular applications, security- and privacy-preserving communication, vehicular network slicing, and intelligent decision-making for cooperative vehicular networks. Additionally, research on multi-objective optimization for latency, energy efficiency, and reliability, as well as integration with 5G/6G networks and IoT infrastructures, represents significant avenues for advancing efficient, intelligent, and resilient edge computing solutions for the IoV ecosystem.