Edge Computing and 5G are transforming autonomous vehicles into intelligent, real-time decision-makers, redefining the future of mobility with faster, safer, and more connected driving experiences, writes Navdeep Narula, Executive Director – Client & Endpoint Solutions, Ingram Micro India.
The last few decades have seen a fantastic evolution of automotive technology, increasingly balancing the contributions of mechanical and electronics engineering in a modern vehicle. In this context, Autonomous Vehicles (AVs) are among the most transformative innovations of our time and have been fueling science fiction movies and future speculation for a long time. Finally, the AV is now becoming a reality. And this is the subject I would like to talk about today. The Autonomous Vehicle is a techie’s dream-come true and promises to reduce road accidents, improve traffic efficiency and potentially reshape urban transportation. Let’s start with understanding how an autonomous vehicle is different from a conventional one. Most simplistically, it needs to remain connected and it should be able to make decisions. The connectivity needs to be reliable, low latency and perennial and the decision making needs sophisticated computing in real time.
Edge Computing and 5G Networks redefining Connected Mobility
Hence, this brilliant use case of connected mobility brings us to two of the most significant technological forces of today – i.e. Edge Computing and 5G. These two technologies are capable of turning ordinary vehicles into sophisticated digital platforms on wheels. Edge computing is a decentralized model of computing, where data is processed closer to where it is generated – at the “edge” of the network—rather than relying on a distant cloud server. In the context of autonomous vehicles, this means that decisions—like when to brake, accelerate, or turn etc. are made onboard the vehicle or through nearby edge infrastructure, rather than depending on a cloud interaction. This is critical for ensuring safety, speed and reliability in dynamic driving environments. Self-driving cars generate a massive amount of data, up to 5 Terabytes per hour from various sensors.
These sensors create a digital replica of the vehicle’s surroundings, which must be analyzed in real-time to navigate roads, avoid collisions, and obey traffic rules. Sending this data to the cloud for processing is neither fast nor practical. The round-trip lag even on a fast GSM network could result in a fatal delay. That is where edge computing steps in. Edge computing enables connected mobility in multiple ways like Real-Time Decision Making for instantaneous responses, Bandwidth optimization by sending only relevant data to the cloud for long-term learning, analytics or software updates, Enhanced Safety and Redundancy allowing the vehicle to continue operating safely even without external data and Reduced Latency in V2X (Vehicleto-everything) Communications involving interaction with traffic lights, pedestrians, other vehicles & roadside infrastructure to be made near-instantaneous. Edge computing is not just a support system for autonomous vehicles, it is the nervous system that enables them to perceive, think, and act in real time. By bringing computation closer to the car and reducing reliance on distant cloud servers, edge computing ensures faster decisions, safer navigation, and more efficient driving.
To complement the massive power of the edge server, the autonomous vehicle require the electronic expressway of 5G, which is the fifth generation and the most advanced mobile network of the GSM protocol offering ultra-low latency, high speed and massive device connectivity. While edge computing handles local processing, 5G networks provide the fast, reliable communication infrastructure needed to support edge and cloud coordination. 5G enables ultra-low latency as low as 1 millisecond, high bandwidth for rich sensor data exchange, and massive device connectivity supporting thousands of AVs per square kilometer. 5G networks are essential today for all enhanced connected vehicle features like Over-the-Air (OTA) Updates allowing for seamless software updates for vehicle systems, Advanced Infotainment supporting high-quality streaming, gaming, and personalized content delivery for passengers, enhancing the overall in-car experience, Real-time Information enabling real-time access to information about nearby services, weather/traffic conditions providing passengers with valuable insights. With 5G, autonomous vehicles can communicate with other cars, edge nodes, and the cloud efficiently, enabling a cohesive driving ecosystem.
Constraints
Despite the huge potential and obvious advantages, one does come across challenges with the integration of edge computing and 5G networks into connected mobility systems. Edge computing has limitations like the need to be compact & robust against heat, dust and vibration, Cybersecurity risks, Standardization and Scalability issues which make it prohibitive to manage thousands of distributed edge notes with a consistent performance. On the other hand, 5G networks have an inherent dependence on tower availability and unlike satellite internet, it will not work in areas having no 5G infrastructure or in difficult terrains like tunnels or hills or the sea, etc.
What the future has in store?
As the ecosystem and the popularity of autonomous vehicles continue to mature, the role of edge computing will only grow. Over the next decade, we can expect to see Wider deployment of edge data centers at intersections and highways, Integration of edge AI chips in all next-gen vehicle platforms, Collaborative learning models where AVs continuously learn from each other, Legislative frameworks that support edge infrastructure investments and potentially a Satellite aided Hybrid 5G (or next generation) network, which is all pervasive with no terrain limitations.
The synergy between 5G and edge computing is poised to redefine the mobility landscape. Analysts predict that by 2030, connected cars will generate more than 300 terabytes of data per year per vehicle, and realtime processing will be essential to harness this information effectively. Tech giants like NVIDIA, Intel, and Qualcomm are already investing in edge computing platforms specifically for autonomous driving. Automakers are partnering with telecom providers to build out 5G-enabled edge infrastructure. As we accelerate toward a future of fully autonomous transportation, edge computing and the 5G data highway will be the invisible force keeping everything running smoothly – right at the edge. And it also promises an edge of the seat experience to the travelers.■
Disclaimer: The views expressed by the author are his own and do not necessarily reflect the views of FMM magazine.
Navdeep Narula
Executive Director, Client & Endpoint Solutions
Ingram Micro India