DoorDash. has been granted a patent for a remote vehicle control system that utilizes a vehicle-mounted sensor and video camera to transmit live video data. The system employs machine intelligence for frame synthesis, enhancing video quality and enabling real-time control instructions to be sent to the vehicle. GlobalData’s report on DoorDash 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 DoorDash, Supply chain management systems was a key innovation area identified from patents. DoorDash's grant share as of July 2024 was 75%. Grant share is based on the ratio of number of grants to total number of patents.
Remote control system for vehicles using video and ai
The patent US12050461B2 describes a remote vehicle control system that utilizes advanced video processing techniques to enhance vehicle operation and safety. Central to the system is a virtual control mechanism that processes video data from a vehicle-mounted sensor system, which includes a video camera. The system captures sequential image frames representing the vehicle's forward view, prioritizing these frames over those from secondary views. It employs a circular buffer to store these frames and generates an optical flow map from consecutive frames to predict pixel positions for a synthesized virtual image frame. This frame is created using a convolutional neural network (CNN) and is inserted into the video stream to produce a modified video representation of the vehicle's surroundings. The system can detect potential collisions based on the predicted positions and generate warnings accordingly.
Additionally, the patent outlines various methods and configurations for optimizing video data transmission and processing. It specifies that the video data can be received over cellular networks and may utilize techniques such as feed-forward correction and specific coding methods for data compression. The system can also interpolate or extrapolate frames to enhance the effective frame rate or replace missing frames. The control system processes user input to transmit control instructions back to the vehicle, ensuring real-time interaction. The claims further detail the use of advanced neural network architectures, including dilated convolutions and bottleneck modules, to improve processing efficiency and accuracy. Overall, this patent presents a comprehensive approach to remote vehicle control, integrating sophisticated video analysis and machine learning techniques to enhance operational safety and responsiveness.
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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.
