OPTIS presents its latest technology in LiDAR simulation at the Autonomous Vehicle Technology World Expo 2018

June 6th, 2018 | OPTIS group

AVTWE

OPTIS ANSYS, a global virtual prototyping company, now allows transportation companies to virtually test and integrate their next-generation LiDARs before their actual release. This innovative new validation system, which increases vehicle and pedestrian safety, will be available for demonstration for the first time in Europe at the Autonomous Vehicle Technology World Expo 2018 at OPTIS’s booth, located at Hall C2, Messe Stuttgart – Booth #AV6008.

 

Presented for the first time during CES 2018 with LeddarTech, the developer of a digital signal processing technology used in automotive solid-state LiDARs, OPTIS ANSYS’ virtual experience of LiDAR recreates their operations on autonomous cars and simulates their use in real life scenarios, allowing for safer, more cost-effective virtual tests of LiDAR systems.

 

With the accelerated development pace of autonomous driving capabilities and the ongoing race to commercialize mass-market solution on production vehicles, any solution that optimizes the development and integration cycles of new technologies adds significant value. OPTIS ANSYS provides an autonomous vehicle simulator that makes the same decisions as a real-world connected vehicle, helping to eliminate costly and risky real-world tests ofa new LiDAR systems and contribute to reducing their time-to-market.

 

OPTIS ANSYS simulates the electronics of the camera as well as the digital conversion to reproduce the data generated in real situation as precisely as possible – including the effects of noise and glare that may impact the sensors.

 

OPTIS ANSYS’ 29 years of expertise in optical and light simulation makes it possible, in a CAD environment, to design optical sensors (cameras and LiDARs), and to validate the sensor performance virtually. OPTIS also helps OEMs and their suppliers to experience intelligent lighting with smart camera sensor model, test camera detection and automated driving systems algorithms in driving scenarios, and evaluate human factor in a unique autonomous driving simulator.