Solution Study
Monday, September 29
12:30 PM - 01:00 PM
Live in Berlin
Less Details
Validating ADAS and AD systems is increasingly complex, requiring a balance between exhaustive testing, regulatory compliance, and development speed. This presentation introduces a scenario-based verification solution that streamlines validation by intelligently selecting test cases, reducing redundancy, and ensuring compliance with ISO 26262, ISO/TS 5083, and UNECE regulations. Attendees will learn how this approach enhances efficiency, improves coverage, and accelerates certification for safer and faster AV deployment.
In this session, you will learn more about:
Alex is a mechanical engineer, graduated from the Polytechnic University of Turin in Italy. His background is mainly in the software industry where he has started initially as a support engineer, system integrator and later a sales director, at first in the area of passive safety and later also within the active safety domain.
Today Alex is a Business Development Manager at ESTECO specialized in the automotive industry and in particular within the AD/ADAS verification and validation domain on top of its initially developed passive safety experience. He mainly operates in Europe and collaborates with a number of different companies to address the validation and verification challenges of autonomous driving vehicles. This involves data generation (lidar & GNSS/IMU providers), testing, data mining as well as understanding how to identify most critical conditions in a simulation environment while using real test data as a starting point, and last but not least to measure the risk of the simulated scenarios.
The Pop in Your Job – What drives you? Why do you love your job?
Very simple: people and technology. Validating and verifying an autonomous driving vehicle requires multiple companies to work together each with their level of expertise. The fun is meeting people with different technical and cultural backgrounds. And of course let’s not forget the technology: you get to play with very advanced sensors and use all sorts of AI based algorithms. In this domain you think less as a traditional engineer where use cases are well defined and more as a data scientist, where all is driven by statistics and probabilities.