Dassault Systemes-Capgemini ADAS Webinar 2023
While Advanced Driver Assistance System (ADAS) features are increasingly being introduced in new vehicles, their development faces significant challenges in terms of complex regulations, safety standards, and the lack of necessary tools and expertise in the industry.
Advanced Driver Assistance System (ADAS) technologies have emerged as promising solutions to reduce accidents as well as enhance driving convenience. ADAS features such as autonomous emergency braking (AEB) and lane-departure warning work on fusion of data from various sensors strategically placed in a vehicle. These sensors such as radar, lidar, ultrasonic sensors, as well as cameras, enable the vehicle to prevent an accident either by sounding an alarm, flashing a visual warning, or completely taking over from the driver in case of an emergency.
While ADAS features are increasingly becoming common in new vehicles, the development of ADAS is a complex process, which involves a mix of extensive virtual and real-world testing. It is further affected by challenges such as complex regulations, safety standards, as well as the lack of necessary tools and expertise to meet the rapidly evolving needs of autonomous mobility.
To solve these challenges, technology giants Dassault Systemes and Capgemini have joined forces to offer a comprehensive solution that covers the entire ADAS lifecycle, from its design to operation. This solution streamlines the ADAS development process, expedites market entry, and reduces costs, particularly in systems engineering, simulations, and verification and validation activities, for both system and software layers.
On September 15, Autocar Professional hosted the ADAS Webinar 2023, in association with Dassault Systemes and Capgemini. This webinar aimed at detailing the comprehensive joint solution that solves the key challenges in ADAS development, and helps understand how the end-to-end tool chain, based on the Dassault Systemes 3DEXPERIENCE platform, enables rigorous ADAS testing and validation by utilising digital twin and real-world data.
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