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The other day me and my colleague were discussing about how difficult it is to find a parked car in a multi-level parking lot because we may forget the floor number, and everything looks identical. He looked at me and asked me how do you think our ADAS (Advanced Driver-Assistance Systems) vehicle handles it? While I had a few answers in my mind I wanted to write an article about it, and there by research a few more ways that the engineers thought of to solve this problem. To

Deep learning breaks the V-Cycle because you can't unit test a neuron. The future of ADAS requires wrapping AI in deterministic safety.

The world of automotive technology is rapidly evolving, and one of the most exciting areas of development is Advanced Driver Assistance Systems (ADAS). These systems are designed to enhance vehicle safety and improve the driving experience. As we look to the future, reinforcement learning is emerging as a powerful tool in the development of ADAS. This blog post will explore how reinforcement learning is being applied in ADAS systems, its benefits, and some real-world examples

The world of transportation is changing rapidly, and at the forefront of this transformation is autonomous driving technology. Imagine a future where cars drive themselves, allowing passengers to relax, work, or enjoy the scenery. This vision is becoming a reality, thanks to significant advancements in technology. In this blog post, we will explore the latest innovations in autonomous driving, the challenges that lie ahead, and what the future may hold for this exciting field

The world of self-driving cars is both exciting and complex. As technology advances, the need for effective motion planning techniques becomes more critical. These techniques allow autonomous vehicles to navigate safely and efficiently in various environments. In this post, we will explore the key motion planning methods used in self-driving cars, their applications, and the challenges they face. Motion planning is the process of determining a sequence of movements that a veh