Stereo Camera Hazard Mapping for Cyclist Rear Awareness
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Solution Overview
Problem
Cyclists face challenges in maintaining situational awareness due to difficulties in perceiving objects and events behind them, with existing solutions like bicycle radar devices failing to discriminate between various types of objects and providing inaccurate distance and speed assessments, especially in urban environments.
Innovation Solution
A computer-implemented method using stereo image data from multiple cameras to determine relative position information of objects, including distance and azimuth, and generate hazard maps for improved situational awareness, integrated with a processor to provide visual and auditory alerts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a cyclist looks over their shoulder to see what is behind them, then they can detect objects behind them, but they cannot see what is ahead of them and they risk losing stability or inadvertently changing their bicycle's course
Solution Approach 1:
The patent uses cameras and sensors as intermediary devices mounted on the bicycle to detect objects behind and around the cyclist. These devices capture visual and environmental data, which is then processed by a computing device to provide situational awareness information to the cyclist through displays or audio outputs, eliminating the need for the cyclist to physically turn their head.
Solution Approach 2:
The patent replaces the mechanical action of the cyclist turning their head with an automated optical and computational system. Cameras, sensors, and image processing algorithms substitute for human physical movement, providing continuous monitoring of the environment without requiring the cyclist to break their forward focus or compromise their balance.
2Loss of information
If a cyclist turns their head far enough to see what is directly behind them, then they can detect objects behind them, but they cannot see what is ahead of them and they risk losing stability
Solution Approach 1:
The patent employs cameras and sensors as intermediary devices that continuously monitor the environment behind and around the cyclist. The computing device processes this data and presents it to the cyclist in an easily consumable format, such as graphical overlays or audio warnings, allowing the cyclist to maintain their balance while staying informed about rearward traffic conditions.
Solution Approach 2:
The patent substitutes the mechanical action of head turning with an automated detection and information presentation system. Sensors and cameras continuously capture data, and the computing device automatically processes and displays relevant information, freeing the cyclist from the need to physically reposition their head while maintaining awareness of their surroundings.
3Measurement precision
If existing radar devices are used to detect objects behind cyclists, then they can provide distance information, but they cannot discriminate between various types of objects or determine relative priority of threats
Solution Approach 1:
The patent combines multiple detection technologies including cameras, sensors, and radar into an integrated system. The camera captures visual information for object identification and classification, while sensors provide additional environmental data. This multi-modal approach merges distance measurement with visual recognition capabilities, allowing the system to both measure distance precisely and identify what type of object is present.
Solution Approach 2:
The patent creates a multi-functional system where the same hardware platform performs multiple functions: distance measurement, object detection, object classification, and threat assessment. The computing device processes data from multiple sources to provide comprehensive situational awareness, making the system universal in its ability to handle various object types and scenarios rather than being limited to simple distance detection.
4Loss of information
If monocular camera-based solutions are used to identify multiple target threats, then they can detect object locations, but they provide poor accuracy when assessing relative distance and speed of threats
Solution Approach 1:
The patent transitions from monocular (single-eye) 2D imaging to stereo (dual-eye) 3D imaging by using two cameras positioned at different locations on the bicycle. This dimensional change from 2D to 3D space enables the system to calculate depth, distance, and speed with much greater accuracy by analyzing the parallax between the two camera views, while still maintaining the ability to detect multiple target locations simultaneously.
Data Source
AI summary
A system for providing situational awareness to a cyclist or other user of a micromobility vehicle comprises a stereo camera assembly and processing logic configured to determine, based on images acquired by the stereo camera assembly, a distance between the cyclist and an object of interest (e.g., a vehicle). The system is configured to determine a threat level of the object based one or more factors such as, e.g., a speed of the object and/or a category of the object. In some examples, the system includes a display and/or an audio indicator to convey information to the cyclist about detected threats. In some examples, the system is configured to produce an audio indication in response to a threat exceeding a threshold threat level. A software platform may be configured to store and/or process micromobility data gathered from one or more users.