A self-driving car’s learning system works
Posted: Tue Feb 04, 2025 4:38 am
What is deep learning?
Whether you know it or not, you've probably already been exposed to deep learning applications. It's what Siri can answer your questions, Google uses it to find the results you're looking for, and Amazon uses it to recommend a product. In the automotive field, deep learning allows engineers to avoid having to program every possible event and action that would occur on a journey. Instead, the computer collects experiences and generates inferences from this data to make decisions.
By learning to detect objects and patterns brazil consumer email list automatically. As more data is fed to it, its accuracy increases. The system is trained through repetition, continually receiving input data and optimizing its ability to make predictions about what the data means and what to do with it. By deploying such a system across a fleet of vehicles, the entire fleet benefits from the collective knowledge generated by each of the vehicles. When one car encounters something new—for example, an unmapped road or an action not contemplated by another car—it sends the experience to the learning system, which analyzes it and sends the learning out to the entire fleet.
In this way, deep learning has the ability to solve one of the main challenges of autonomous driving: dealing with the unpredictable. It would be virtually impossible for human engineers to manually program algorithms to adequately express all possible driving scenarios.
Whether you know it or not, you've probably already been exposed to deep learning applications. It's what Siri can answer your questions, Google uses it to find the results you're looking for, and Amazon uses it to recommend a product. In the automotive field, deep learning allows engineers to avoid having to program every possible event and action that would occur on a journey. Instead, the computer collects experiences and generates inferences from this data to make decisions.
By learning to detect objects and patterns brazil consumer email list automatically. As more data is fed to it, its accuracy increases. The system is trained through repetition, continually receiving input data and optimizing its ability to make predictions about what the data means and what to do with it. By deploying such a system across a fleet of vehicles, the entire fleet benefits from the collective knowledge generated by each of the vehicles. When one car encounters something new—for example, an unmapped road or an action not contemplated by another car—it sends the experience to the learning system, which analyzes it and sends the learning out to the entire fleet.
In this way, deep learning has the ability to solve one of the main challenges of autonomous driving: dealing with the unpredictable. It would be virtually impossible for human engineers to manually program algorithms to adequately express all possible driving scenarios.