Motorcycle Helmet Visor Display for Autonomous Vehicle Detection
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Solution Overview
Problem
Existing systems fail to distinguish between autonomous and non-autonomous vehicles in a motorcycle rider's field of view, limiting the rider's ability to take appropriate precautions.
Innovation Solution
A system comprising a smart helmet with an advanced driver assistance camera, radar module, gyroscope, GPS sensor, acceleration sensor, and Vehicle-to-Everything (V2X) communication, which processes video streams and sensor data to detect and display autonomous vehicles in the rider's field of view, using image segmentation, simultaneous localization and mapping, and V2X communication to identify and mark autonomous vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If existing camera and sensor systems are used to detect vehicles, then the system can identify vehicles in the field of view, but it cannot distinguish which vehicles are autonomous and which are not
Solution Approach 1:
The patent introduces V2X communication as an intermediary mechanism that enables the motorcycle system to receive and process identification information about autonomous vehicles from external communication infrastructure, allowing distinction between autonomous and non-autonomous vehicles without significantly increasing on-board processing complexity
Solution Approach 2:
The system integrates multiple functions into existing components: the camera system serves both general vehicle detection and autonomous vehicle identification purposes, while the processing unit handles both standard traffic monitoring and specialized autonomous vehicle classification, reducing overall system complexity
2Reliability
If multiple sensors and processing units are integrated into the motorcycle system, then autonomous vehicle detection capability is improved, but the device complexity increases
Solution Approach 1:
The patent combines multiple sensor functions into integrated modules: the camera system is merged with processing capabilities to simultaneously perform vehicle detection and autonomous vehicle identification, while V2X communication is integrated with the existing motorcycle electronics system, reducing the number of separate components needed
Solution Approach 2:
The system uses the motorcycle's existing communication and processing capabilities to serve the additional function of autonomous vehicle detection, rather than requiring completely separate dedicated systems, thereby reducing overall device complexity while maintaining reliability
3Measurement precision
If the system processes video streams and sensor data in real-time, then the detection accuracy is improved, but the computational requirements and system complexity increase
Solution Approach 1:
The system performs preliminary processing of video streams and sensor data to create a foundational understanding of the traffic environment before applying specialized algorithms to identify autonomous vehicles, reducing the computational burden on the main processing unit while maintaining high detection accuracy
Solution Approach 2:
The processing pipeline is segmented into distinct stages: general vehicle detection, autonomous vehicle identification through V2X communication, and integrated analysis, allowing each stage to operate independently and reduce overall computational requirements while maintaining precision
Data Source
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AI summary
This patent relates to ego motorcycle on-board awareness raising system placed in an ensemble consisting in an ego motorcycle and an ego motorcycle rider smart helmet, provided with advanced driver assistance systems camera acquiring video streams and further comprising: a radar module; a gyroscope, a GPS sensor; an acceleration sensor; a speedometer, an ego motorcycle on-board unit communicating with other vehicles via the Vehicle-to-Everything communication channel and reading autonomous vehicle identifier; an on-board detection processing unit and a bus system for connecting components. The method for detecting and displaying presence of autonomous vehicle comprises receiving data regarding other vehicles driving in motorcycle rider's field of view and regarding the ego motorcycle rider, performing processing of video stream, creating of a fused environment road model, applying simultaneous localization and mapping algorithm for localizing the ego motorcycle in the fused road environment, detecting and marking in said processed video stream the presence of autonomous vehicles, applying correction to the marking and sending the result of detected autonomous vehicles to the smart helmet visor in an understandable manner by the motorcycle rider. The computer program when executed on the ego motorcycle on-board detection processing unit causes the execution of the steps related to the detection of the autonomous vehicles driving in motorcycle rider's field of view.