StradVision reveals advanced ADAS features with surround view monitoring solution

StradVision reveals advanced ADAS features with surround view monitoring solution

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StradVisionStradVision, a notable player in AI-based camera perception software for ADAS (Advanced Driver Assistance Systems)  and Autonomous Vehicles , is introducing  its latest automotive Surround View Monitoring (SVM) technology at AutoSens 2020.

AutoSens 2020 is a top international conference for the automotive sensor industry.

Through an AutoSens 2020 online session titled ‘Discussion: How to run multi-channel cameras on a single automotive-grade SoC’, to be conducted  on November 19, StradVision is revealing  perception software that automotive OEMs can add to its SVM systems for Automatic Parking Assist (APA)  and  AVP  – both are highly advanced and fast-growing features in the ADAS technology area.

APA supports drivers to park a vehicle in a vacant parking lot, with or without driver’s intervention; while AVP offers a complete valet parking service controlled by ADAS , making the vehicle to drive itself to find a parking lot and returns to the driver once summoned.

As the demand for AVP and APA increasing rapidly, StradVision has been developing new technologies for more specific and precise recognition of parking areas.

Its SVM technology can detect various static objects including ground locks, stoppers and poles and road signs for path planning. It also integrates other cutting-edge technologies such as Visual Simultaneous Localization and Mapping (V-SLAM), Pseudo Lidar and depth estimation for accurate map generation, height classification and road profiling.

StradVision’s Chief Executive Officer Junhwan Kim, said, “We have been testing our SVM solutions either through our own projects or in collaboration with external partners. Through this process, we are solving challenges in order to provide robust and stable performance, and provide strong compatibility with a wide range of system-on-chips (SoCs),” said.

StradVision is advancing the future of autonomous vehicles through ‘SVNet’, an Artificial Intelligence-based object recognition software that allows for autonomous vehicles and ADAS to identify other vehicles, pedestrians, animals, lanes, free space, traffic signs, and lights, even in harsh weather conditions or poor lighting.

Presently, SVNet is utilized in mass production models of ADAS and autonomous driving vehicles that support safety function Levels 2 to 4, and will be deployed in more than 8.8 million vehicles worldwide.