Comparative Assessment of 5G Core Network Analytics and Aerial Imagery in Vehicle Navigation Systems

Abstract

The rapid advancements in vehicle navigation systems have ushered in a new era of intelligent transportation, leveraging both network-centric and sensory data approaches. This paper provides a comparative assessment of two key technologies: 5G core network analytics and aerial imagery, for enhancing vehicle navigation systems. 5G networks, with their ultra-low latency and massive device connectivity, enable real-time traffic monitoring and predictive analytics, enhancing navigation efficiency. In parallel, aerial imagery, particularly through drones and satellite-based systems, offers high-resolution geospatial data for mapping and obstacle detection. We examine the integration challenges, data processing frameworks, and communication latencies associated with these technologies. By employing a qualitative and quantitative comparison, the study evaluates key performance indicators (KPIs) such as accuracy, latency, scalability, and computational complexity. The results highlight the complementary nature of these technologies while emphasizing the need for hybrid approaches to achieve optimal navigation performance. This paper concludes with a discussion on future research directions, focusing on edge computing, 6G advancements, and multi-modal data fusion for next-generation vehicle navigation systems.