Yandex has been granted a patent for a method to predict the maneuvers of objects near a Self-Driving Car (SDC). The method involves analyzing road maps, generating predicted trajectories, and computing scores to determine future locations of objects, enabling the SDC to adjust its driving parameters accordingly. GlobalData’s report on Yandex 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 Yandex, Social media analytics was a key innovation area identified from patents. Yandex's grant share as of July 2024 was 47%. Grant share is based on the ratio of number of grants to total number of patents.
Predicting object maneuvers for self-driving car navigation
The granted patent US12024204B2 outlines a method for predicting the maneuvers of objects in the vicinity of a Self-Driving Car (SDC) using an electronic device. The method involves receiving a section of a road map that includes information about multiple road lanes. The electronic device generates predicted trajectories for the object, mapping potential future locations on the road map based on the road lane information. It computes scores for these locations, reflecting their association with the road lanes at a future time, and aggregates these scores to determine a predicted location for the object. This prediction informs the adjustment of the SDC's driving parameters, such as acceleration, speed, and direction, to enhance safety and navigation.
Additionally, the patent specifies that the method can utilize high-definition maps and may generate predicted trajectories without initially considering road lane information. The scoring system is designed to account for the likelihood of the object making rapid lane changes or zig-zagging behavior, with higher scores indicating stability in the object's movement. The electronic device can employ machine learning algorithms to refine the scoring process, ensuring that the SDC can effectively respond to the predicted behavior of nearby objects. This innovative approach aims to improve the operational efficiency and safety of self-driving vehicles in complex driving environments.
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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.
