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Solutions

Ric🔥h Experience in Mass Production of Before-market Products

Take the lead to realize mass production in OEMs of passenger vehicles in China, which has been applied to several before-market and after-market projects for mass production. Cond🤡uct joint research and devel꧋opment cooperation with several autonomous driving programs of first-line auto OEMs.

Widely Recogn🧔ized Timeliness, Accuracy and Rob🍌ustness

FPGA is used to realize flexible deep learning network, which has low power consumption, high stability and reliability, high object detection rate, low false detect♕ion rate, and has realized accurate detection of various targets.

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Support Autonomous Driving at Different Levels

With front-view and multi-camera surrou🎶nd-view visual perception based on deep learning and adva💯nced VSLAM technology, we provide L0-L2 advanced driving assistance systems, L3/L4 Auto Parking Assist (APA) / Auto Valet Parking (AVP) and high-level Autonomous driving.

Provide Efficient and Convenient Localized 🔯Service

Rooted in the Chinese market, we are committed to introducing internationally advanced artificial intelligence technologies to China for industrial applications, and is always list꧟ening t💞o the needs of Chinese automobile customers, and responding to market changes quickly so as to help our customers launch more competitive product solutions timely for win-win cooperation.

Support Autonomous Driving at Different Levels

Support L0-L2 adꩵvanced driving assistance system (ADAS) based on monocular vision deep learning, which 🐠can provide LDW, FCW, PCW, SLI and other functions.

Support L3/L4 Auto Parking Assist (APA) / Auto Valet Parking ꦦ(AVP) based on surround-view vision and deep learning, which can identify the surrounding environment of the car in real-time and output information such as detected vehicles, pedestrians, obstacles, parking spaces, traffic lanes, etc.

Support L3-L4 high-level Autonomo൩us driving scheme based on deep learning and visual SLAM. The world’s top visual perception, fusion, positioning, path planning and control algorithms are implemented on the embedded low-power-consumption chip in line with s﷽pecifications and standards for automobiles to achieve Autonomous driving under different scenes and conditions.

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