MOBILEYE VISION TECHNOLOGIES LTD. (Jerusalem, IL)

The present disclosure relates to methods and systems for road edge detection and mapping, for vehicle wheel identification and navigation based thereon as well as for identifying objects as moving or non-moving. The systems and methods described may utilize trained systems, such as one or more neural networks. Further autonomous vehicle systems could include elements of any of the techniques and systems.

Technical Field

The disclosed disclosure is of a general nature and is related to methods and systems to recognize and classify the elements in the environment that is a vehicle’s. Particularly, the disclosure relates to systems and methods for detecting a road boundary edge, detecting awheel of the vehicle, and classifying objects as moving or not.

Background Information

As technology advances in the field of technology, the possibility of a fully autonomous vehicle capable of driving on roads is near. Autonomous vehicles could have to consider various aspects and make the right decisions based on those factors to safely and accurately reach an intended destination. For example an autonomous vehicle could require processing and interpretation of images (e.g. images taken from a camera) and could also rely on information gathered from other sources (e.g., from an GPS device, a speed sensor, an accelerometer, a suspension sensor, etc.). The autonomous vehicle may require a location in a roadway to get to a location. This could include identifying the location of the vehicle in a multi-lane roadway, following other vehicles and pedestrians, and avoiding obstacles and pedestrians. There are many design issues involved in interpreting and harnessing the vast quantities of data that an autonomous vehicle collects as it journeys to its destination. The sheer amount of information (e.g. images captured data, maps data, GPS data, sensor data, etc. )that an autonomous vehicle may require to access, analyze, and/or store presents challenges that can in fact restrict or negatively impact autonomous navigation. Additionally, an autonomous vehicle that relies on the traditional technology of mapping for navigation faces daunting challenges due to the sheer volume of data needed to maintain and update the map.

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