Lyft had 14 patents in artificial intelligence during Q1 2024. Lyft Inc’s patents filed in Q1 2024 focus on systems and methods for analyzing sensor data from vehicles to identify agents in the environment, address emergency situations with customized user interfaces, manage emergency communications, extract features from sensor data to create map representations of road segments, detect unexpected events in personal mobility vehicles, and correct errors in transportation routes by generating route predictions based on previously completed routes. GlobalData’s report on Lyft gives a 360-degree view of the company including its patenting strategy. Buy the report here.

Lyft grant share with artificial intelligence as a theme is 57% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.

Recent Patents

Application: Approaches for encoding environmental information (Patent ID: US20240104932A1)

The patent filed by Lyft Inc. describes a system, method, and computer-readable media for accessing parameter-based encodings that represent an environment captured by sensors in vehicles. These encodings identify agents detected in the environment and their locations, which are then clustered to determine scenarios associated with the environment. The method involves labeling the encodings based on similarity, determining new scenarios, identifying maneuvers, and utilizing machine learning models for scenario classification.

The computer-implemented method involves clustering parameter-based encodings, assigning labels based on similarity, determining new scenarios or scenario families, associating scenarios with interactions between vehicles and agents, and classifying scenarios based on machine learning models. The system includes processors and memory for performing operations such as clustering, labeling, determining maneuvers, and utilizing machine learning models. The non-transitory computer-readable storage medium contains instructions for clustering encodings, determining scenarios, labeling new scenarios, associating scenarios with vehicle-agent interactions, and utilizing machine learning models for scenario classification. Overall, the patent focuses on efficiently analyzing sensor data from vehicles to identify and classify scenarios in an environment.

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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.