V2V Sensor Data Sharing for Blind Spot Detection
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Solution Overview
Problem
Conventional vehicle-implemented object detection systems rely solely on local sensor data and do not utilize information from other vehicles, limiting their field of view and accuracy, while V2V communications typically transmit textual data rather than raw sensor data, which restricts the sharing of detailed object information.
Innovation Solution
The system utilizes vehicle-to-vehicle (V2V) communications to share sensor data between vehicles, enabling the determination of object positions and types, and generates images of detected objects, which are then displayed to the operator, thereby enhancing situational awareness beyond the limitations of individual vehicle sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If V2V communications transmit textual data only, then communication simplicity is maintained, but object information sharing is restricted
Solution Approach 1:
The patent merges sensor data acquisition, processing, and communication functions into an integrated system. Multiple sensors (cameras, radar, LIDAR) are combined to capture comprehensive object information, which is then processed and shared via V2V communications, resolving the contradiction between information completeness and system complexity
Solution Approach 2:
The patent introduces a communication manager as an intermediary component that handles the complex task of selecting and transmitting relevant object information. This mediator processes raw sensor data, identifies critical objects, and transmits only necessary information, reducing communication complexity while maintaining information quality
2Loss of information
If camera systems are limited by field of view, then device complexity is reduced, but situational awareness is restricted
Solution Approach 1:
The patent combines multiple sensor types (cameras with limited FOV, radar sensors, LIDAR) into an integrated sensing system. Each sensor type compensates for the limitations of others, providing comprehensive situational awareness while maintaining reasonable device complexity through shared processing infrastructure
Solution Approach 2:
The patent adds spatial dimensionality to situational awareness by integrating data from vehicles at different positions and orientations. By combining sensor data from multiple vehicles surrounding the target area, the system achieves 360-degree awareness without requiring a single complex omnidirectional sensor system
3Measurement precision
If local sensor data only is used, then system complexity is minimized, but detection accuracy is limited
Solution Approach 1:
The patent merges sensor data from multiple vehicles to improve detection accuracy. By combining observations from different vantage points, the system achieves more precise object detection and tracking than any single vehicle could accomplish alone, while sharing processing loads across the network
Solution Approach 2:
The patent implements selective data sharing where only relevant object information is transmitted between vehicles. The communication manager filters and prioritizes data based on object importance, distance, and motion characteristics, reducing processing complexity while maintaining detection accuracy through targeted information exchange
Data Source
AI summary
Methods, systems, and storage media are described for assisting the operation of a first vehicle. In embodiments, a computing device of the first vehicle may obtain first sensor data from a first sensor of the first vehicle. The first sensor data may be representative of a second vehicle proximate to the first vehicle. The computing device may determine a first position of the second vehicle relative to the first vehicle; initiate a vehicle-to-vehicle (V2V) communications session with the second vehicle; receive second sensor data from the second vehicle during the V2V communications session; and determine a second position based on the second sensor data. The second position may be a position of the second vehicle relative to a third vehicle. The computing device may display an image of the third vehicle on a display device. Other embodiments may be described and/or claimed.