INRIX. has been granted a patent for a method that detects vehicle slowdowns by analyzing location data from vehicles. The process involves generating a space-time diagram and using a convolutional neural network to assess the likelihood of a slowdown, subsequently notifying affected vehicles. GlobalData’s report on INRIX 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 INRIX, AV navigation planning was a key innovation area identified from patents. INRIX's grant share as of July 2024 was 49%. Grant share is based on the ratio of number of grants to total number of patents.
Vehicle slowdown detection using location data and neural networks
The patent US12033500B2 outlines a method and system for detecting vehicle slowdowns on road segments using a computing device equipped with a processor. The method involves evaluating location data from vehicles to identify specific road segments and generating a space-time diagram that represents vehicle movement over time and distance. This diagram is processed through a neural network designed for image recognition, which detects slowdowns by constructing a time series of transition points based on features extracted from the diagram. Additional operations include notifying drivers of identified slowdowns, predicting the duration of these slowdowns, and providing information about transition points between free-flowing and congested traffic.
Further enhancements to the method include the use of Kalman and Hampel filters to refine the detection of slowdowns by clustering vehicle speeds and identifying significant differences between free-flowing and slowed traffic. The system can also incorporate historical data on traffic patterns, as well as current road and weather conditions, to improve accuracy in detecting slowdowns. Notifications can be sent to vehicles within a certain distance of the slowdown, ensuring timely information is provided to drivers. The patent emphasizes the integration of advanced data processing techniques and machine learning to enhance traffic management and driver awareness on the road.
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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.
