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Autonomous Vehicles & ADAS

AImotive introduces AI-powered Level 5 self-driving technology ecosystem

Tom StoneBy Tom StoneNovember 16, 20163 Mins Read
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Hungarian company AImotive (formerly AdasWorks) says it is the first to enable an artificial intelligence (AI) ecosystem for SAE Level 5 autonomous driving, regardless of location, driving style, and weather or road conditions.

Headquartered in Budapest, AImotive delivers a full stack technology system and powerful artificial intelligence software for the automotive industry, designed to provide self-driving vehicles with better safety, improved comfort and increased productivity.

The company aims to bring global accessibility to autonomous vehicles, faster and safer than any other company in the world. The AImotive product suite delivers the robust technology required to operate self-driving vehicles in all conditions, and adapts in real time to different driving styles and cultures. In addition to its recent name change, AImotive has also announced its expansion into the US market with the opening of a new office in Mountain View, California.

AImotive offers the only SAE Level 5 architecture capable of robust scalability across the global market, using cameras as the primary sensors for greater affordability and accessibility. Unlike other systems on the market, AImotive’s full stack software does not require a mandatory chip, and it uses the power of AI intelligence to ‘see’ fine detail and predict behavior, making it easier to manage common driving concerns, such as poor visibility and adverse conditions.

The company’s testing technique is also scalable, with a real-time simulator tool that trains the AI for a wide variety of traffic scenarios and weather conditions. AImotive provides a full spectrum of automated driving functionality that will enable OEMs to move faster and more efficiently into fully autonomous car production.

The main component of AImotive’s suite of products is aiDrive, which includes four software ‘Engines’:

• Recognition Engine is a continuously learning engine that combines and analyses sensor data with AImotive’s pixel-precise segmentation tool to recognize up to 100 different object classes, such as pedestrians, bicycles, animals, buildings and obstacles;

• Location Engine provides a globally-scalable solution for precise self-localization of the vehicle that does not require HD maps for precise positioning, but uses 3D landmark point data on top of conventional GPS positioning;

• Motion Engine enables real-time tracking of moving objects, predicting future speed, location and behavior, allowing for optimal routing of the car, even in emergency situations;

• Control Engine is the execution component that manages acceleration, braking, steering, and gear shifting, as well as auxiliary functions, such as turn signals, headlights and the car horn.

The suite also includes:

• aiKit, which incorporates a complete ecosystem of tools that accelerate the training of the AI by enabling faster data collection and annotation, complete testing with real-time simulation of various driving conditions, and providing validated over-the-air updates for maximum travel safety;

• aiWare, which is a performance-efficient hardware design for automotive embedded solutions, offering low power consumption, high bandwidth and low latency Neural Network (NN) computation. While the goal of aiWare is to help bring truly efficient AI hardware to the market quicker, aiDrive itself is designed to be processor agnostic, allowing for seamless integration with GPU, FPGA or embedded technology based systems.

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Tom Stone

Tom has edited Traffic Technology International (TTi) magazine and its Traffic Technology Today website since May 2014. During his time at the title, he has interviewed some of the top transportation chiefs at public agencies around the world as well as CEOs of leading multinationals and ground-breaking start-ups. Tom's earlier career saw him working on some the UK's leading consumer magazine titles. He has a law degree from the London School of Economics (LSE).

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