TuSimple. has filed a patent for a sensor network providing full and redundant coverage for autonomous vehicles. The system includes multiple cameras with overlapping fields of view and directional sensors to ensure comprehensive environmental awareness for safe autonomous driving. GlobalData’s report on TuSimple 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 TuSimple, Autonomous freight management was a key innovation area identified from patents. TuSimple's grant share as of January 2024 was 35%. Grant share is based on the ratio of number of grants to total number of patents.
Redundant sensor coverage for autonomous vehicle
A sensor network for an autonomous vehicle has been claimed in a filed patent (Publication Number: US20240040269A1). The network includes a plurality of first cameras with a first field-of-view (FOV) and a first horizontal aspect, along with a plurality of second cameras with a second FOV and a second horizontal aspect. These cameras are strategically located at different angular positions on the vehicle, ensuring that the horizontal aspects of the fields-of-view overlap by a predetermined number of degrees. The system also involves operating the cameras at corresponding frame rates, synchronizing them with a sensor frequency of a light detection and ranging sensor on the vehicle, and considering the expected speed of external objects in motion relative to the vehicle.
Furthermore, the sensor network includes additional features such as symmetrical placement of cameras along the vehicle's central axis, stereovision-based detection capabilities with specific camera separations, and vertical aspect overlaps between different sets of cameras. The system aims to continuously cover a 360-degree span around the vehicle, enabling comprehensive monitoring and object detection. A system for operating the autonomous vehicle is also described, involving a processor receiving image data from the camera network to detect objects, determine trajectories, and guide the vehicle accordingly. Additionally, a method for operating the autonomous vehicle based on the sensor network data is outlined, including object detection, trajectory determination, and vehicle movement based on the detected objects' movements within the cameras' fields-of-view.
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