Distance estimation is at the heart of automotive driver assistance systems (ADAS) and automated driving (AD). Simply stated, safe operation of vehicles requires robust distance estimation. Many different types of sensors (camera, radar, LiDAR, sonar) can be used for distance estimation, and different distance estimation techniques can be used with each type of sensor. Each type of sensor and technique has unique strengths and weaknesses. We’ll examine these techniques and their strengths and weaknesses, and show how multiple techniques using different sensor types can be fused to enable robust distance estimation for a specific automated driving application.
Distance Estimation Solutions for ADAS and Automated Driving
Session Speakers
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Gergely Debreczeni
Chief Scientist, Almotive
Gergely has 15+ years of R&D expertise in the fields of physics, mathematics, computer sciences and machine learning and a Ph.D. in particle physics. He has overseen AImotive's development of computer vision and machine learning algorithms since the early days of the company. Gergely also enjoys keeping his AImotive colleagues up to date on relevant scientific advances, and providing technical support to the company's business development team.
