Nissan Motor had 16 patents in artificial intelligence during Q4 2023. Nissan Motor Co Ltd filed patents related to methods for autonomous decision-making based on environment states, an information processing system for controlling devices based on line-of-sight data, a display control device for seamless transition between animations, and a data processing system for generating output data from input data by adding dummy data. GlobalData’s report on Nissan Motor gives a 360-degreee view of the company including its patenting strategy. Buy the report here.
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Nissan Motor grant share with artificial intelligence as a theme is 50% in Q4 2023. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Online state space refinement for competence-aware systems (Patent ID: US20230382433A1)
The patent filed by Nissan Motor Co Ltd describes methods and systems for autonomous driving by autonomous vehicles (AVs). The first method involves detecting environment states based on sensor data, selecting actions, determining autonomy levels, and performing actions based on autonomy levels. The autonomy levels can range from "no autonomy" to "unsupervised autonomy," with actions being performed according to the selected level, including receiving feedback signals for approval or disapproval. The second method focuses on calculating policies for solving tasks by solving an extended Stochastic Shortest Path (SSP) problem, mapping environment states and autonomy levels to actions, and generating plans that operate across multiple levels of autonomy.
The patent also includes a system for autonomous driving that involves a processor executing instructions to calculate policies, identify discriminators, and train feedback models. The system generates plans operating across various autonomy levels subject to constraints and updates feedback models, human transition functions, and autonomy profiles based on actions performed. Additionally, a method for autonomous driving is outlined, involving calculating policies, identifying discriminators, training feedback models, and generating plans across multiple autonomy levels. Constraints on allowed autonomy levels in states are considered, and feedback models, human transition functions, and autonomy profiles are updated based on actions taken. Overall, the patent details comprehensive methods and systems for autonomous driving, emphasizing the importance of autonomy levels, feedback mechanisms, and policy calculations in ensuring safe and efficient autonomous vehicle operations.
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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.
