Autonomous Driving

Event Detection is a core function of autonomous vehicles

With advancements in artificial intelligence and related technologies, cars will eventually become autonomous vehicles that are entrusted with human lives. In order for these autonomous vehicles to function properly, they must be equipped with capabilities that enable them to make the best and safest decisions in any situation. To ensure this, the images produced by the vehicles' cameras are analyzed to identify the position of objects, the associated category, and related events to better understand the images and the situations. The systems currently available were inspired by computer vision and deep learning methods. However, they have difficulties when trying to detect small objects, objects with random geometric transformations, and when there is a lack of contrast For this reason, EDI GmbH is working on an algorithm that will improve the detection of critical events by recognizing contexts and correlations in situations where the sensors have weak points. EDI GmbH's algorithm will also be helpful in avoiding accidents in road traffic. The detection of object and events covers a variety of important techniques, especially image processing, pattern recognition, artificial intelligence, and machine learning.

Failure strategies for robot taxis

The AnRox research project aims to develop an optimized drive system for automated electric vehicles. As a project partner, EDI GmbH has the task of developing and validating a substitute system that steps in if the primary system fails Many well-known companies and institutions such as Bosch, Siemens, Infineon, and RWTH Aachen are working closely as partners to develop the efficient and fail-safe electrical system for robot taxis. Using its dynamic risk management algorithm and predictive behavior, EDI GmbH's task is to develop strategies based on existing data to tell the system how to react, if the primary system or parts of it fail In case of a breakdown, the intelligent ADAS (Advanced Driver Assistance System) will assess the situation and will stop the vehicle safely, so that the passengers are not endangered and safe. Moreover, in the event of a breakdown occurring while driving as well, if the vehicle detects an object such as a person or another vehicle in a place where the driver may not be able to notice them, the system will alert the driver. Likewise, if the car's battery becomes weak or the brake does not work properly the intelligent ADAS can alert the driver. If the system determines that the vehicle is leaving its lane, it can activate the lane departure warning. In a nutshell, artificial intelligence is used to make the right as to how the vehicle should react to the error situation so as not to endanger the passengers and to bring the vehicle to a safe stop. The validation of these scenarios is carried out in a simulation.

AI-based Safe Navigation and Driving

Risk Estimation with a Learning AI - RELAI

Dynamic Risk Management (DRM)