Trustworthy Intelligent Vehicular Networks: A Survey

Abstract

Intelligent Vehicular Networks (IVNs) serve as a core infrastructure for next-generation smart transportation, yet their large-scale deployment is severely hindered by insufficient trustworthiness, fragmented technologies, and difficult integration of multi-domain systems. Existing IVN surveys often lack a systematic taxonomy for trustworthy design and fail to comprehensively address practical challenges in V2X deployment and emerging 6G-enabled evolution. Most prior reviews overlook the joint optimization of cognition, communication, and computation layers, and rarely conduct a unified analysis of security, privacy, ethics, and trust issues across the full IVN pipeline. They also provide limited insights into real-world indoor and outdoor use cases and long-term developmental trends toward 2030. This survey proposes a three-layer hierarchical taxonomy of trustworthy IVNs, encompassing cognition, communication, and computation, to systematically organize and evaluate state-of-the-art technologies. We review sensing, communication, and computing in IVNs, while analyzing trustworthy risks and ethical dilemmas within each layer. We further validate practical IVN implementations through representative indoor and outdoor case studies and forecast key trends including 6G, AI-native networking, intelligent reflecting surfaces, integrated sensing and communication, and large language models. This survey provides a standardized analytical framework for researchers and offers actionable references for the secure, ethical, and trustworthy development and deployment of next-generation IVNs.