Autonomous Driving: The Importance of In-Car AI Over GPS or 5G
The evolution of technology has birthed an unprecedented era of autonomous vehicles. However, the established myth is that self-driving cars are vastly reliant on GPS or 5G technology, with the latter carving its way as the newest technological Holy Grail. However, this paradigm is being progressively debunked. Instead, the spotlight is now on the evolving necessity of built-in AI, rightfully so.
The Downside of GPS and 5G
Though Global Positioning System (GPS) and 5G networks are powerful tools, they cannot entirely ensure the safety, functionality, and reliability of self-driving cars. GPS signals can be obstructed, inaccurate and unresponsive. Obstructions such as tunnels, tall buildings, or even heavy weather conditions can disrupt the signal. Furthermore, a GPS may provide a general route, but it struggles with exact positioning. When it comes to autonomous vehicles, inaccuracy is not an option, the margin for error is nil.
When we consider 5G technology, though it is highly anticipated, we realize that its full rollout will not be immediate and will take quite some time. This means that relying on it for autonomous driving today would mean innumerable vehicles unable to function if they move into areas where the 5G network is non-existent or weak. Furthermore, 5G installation costs could be prohibitive in some areas leading to delayed or no deployment at all.
The Power of In-Car AI
The introduction of Artificial Intelligence (AI) in autonomous cars has been a game-changer. AI in autonomous vehicles is not a luxury, it's a necessity. This technology enables the car to make complex decisions in real time, learn from its past experiences, and respond quickly to its environment. Unlike GPS and 5G networks that may not always deliver due to various limitations, an in-built AI system functions independently.
Machine learning and AI can help cars recognize stop signs, traffic lights, pedestrians, and other vehicles, and make quick judgements in response to these factors. AI can adjust to changes in weather, handle nighttime driving, and make decisions when GPS signals falter or during low connectivity.
Another major advantage of in-vehicle AI is its robustness against hacking. The 'always-on' nature of 5G and GPS implies a persistent potential for remote cyber attacks. However, the deployment of AI software within the car effectively reduces this risk. The AI doesn't necessarily need to 'talk' to the outside world all the time, therefore the potential points of intrusion for hackers significantly decrease.
The Future of Autonomous Driving
The conferences, debates, and developments around autonomous driving are experiencing a subtle yet powerful shift in focus. This focus is moving from over-reliance on GPS and 5G networks to smart cars powered by in-built AI systems. In other words, autonomous driving technology is being built to function independently with minimum deviation regardless of the external factors.
Manufacturers are not only looking to build vehicles that can automatically react to their surroundings, but vehicles that can also predict and plan. AI and machine learning capabilities are gearing towards improving the vehicles' 'thinking' time. Manufacturers are aiming for cars that can manage real-time data processing, abstract data analysis, prediction, complex rule-based decisions, and function on minimum to no human supervision.
Conclusion
As the autonomous driving industry leaps forward, incorporating AI into vehicles' system design is, at present, the most reliable and efficient option. The technology that powers these vehicles should operate predictably across all geographical locations and conditions. Therefore, it must be something inherently part of the vehicle, hence in-car AI. As improvements continue, the possibilities seem endless. AI marks an impressive era of automotive precision, safety, and reliability, far beyond what sole reliance on GPS and 5G networks can provide.
