Tesla has been granted a patent for a system that uses image data captured by a vehicle’s camera to predict a three-dimensional trajectory of a machine learning feature. The trained machine learning model then automatically controls the vehicle based on this trajectory. GlobalData’s report on Tesla gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Tesla, Battery management systems was a key innovation area identified from patents. Tesla's grant share as of May 2024 was 35%. Grant share is based on the ratio of number of grants to total number of patents.
Machine learning system for three-dimensional vehicle trajectory prediction
A recently granted patent (Publication Number: US12014553B2) discloses a system designed to enhance vehicle operation through the use of sensor data and machine learning models. The system involves obtaining sensor data from a vehicle, determining a three-dimensional feature based on a machine learning model trained with a specific dataset, and adjusting the vehicle's operation accordingly. The machine learning model is trained to output a ground truth based on input sensor data elements, ultimately influencing the vehicle's behavior based on the identified three-dimensional feature.
Furthermore, the system can determine various real-world features such as vehicle lane lines or other vehicles, adjusting the vehicle's speed or steering as needed. The method also involves selecting portions of sensor data elements with the highest certainty in depicting real-world features, ensuring accurate determination of the ground truth. By incorporating elevation information associated with the identified features, the system can effectively adjust the vehicle's operation based on the three-dimensional feature determined through the machine learning model. This innovative approach aims to optimize vehicle performance and safety through advanced data processing and analysis techniques.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
