Mobility Vehicle Vibration Analysis for Sidewalk Detection
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Solution Overview
Problem
Transportation services face challenges in detecting when personal mobility vehicles are driven on sidewalks, leading to penalties and safety hazards, as existing systems lack efficient and accurate sidewalk-detection capabilities.
Innovation Solution
Systems and methods analyze vibrations introduced into personal mobility vehicles to identify sidewalk-specific vibrations using machine learning algorithms, determining the vehicle's surface type based on frequency patterns, speed, and vertical acceleration, enabling real-time detection and corrective actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If personal mobility vehicles are driven on sidewalks, then user convenience is improved, but safety and compliance deteriorate due to penalties and hazards to pedestrians
Solution Approach 1:
The system continuously monitors vibration signals from the vehicle and provides real-time feedback to the user through notifications when sidewalk usage is detected. This feedback loop enables users to adjust their behavior to avoid penalties and safety hazards while maintaining operational convenience.
Solution Approach 2:
The patent replaces manual monitoring and judgment of surface types with an automated sensor-based system that uses vibration analysis and machine learning algorithms to detect sidewalk versus road surfaces, eliminating the need for users to manually determine appropriate driving surfaces.
2Measurement precision
If vibration analysis with machine learning is implemented for sidewalk detection, then detection accuracy is improved, but device complexity increases
Solution Approach 1:
The system uses the vehicle's existing vibration sensors and onboard processing capabilities to perform sidewalk detection independently, without requiring external infrastructure or complex additional hardware. The machine learning model is trained offline and deployed as a lightweight algorithm that leverages the vehicle's own sensor data.
Solution Approach 2:
The patent transforms the complex problem of sidewalk detection into analysis of vibration signal parameters (frequency, amplitude, patterns) that can be processed by relatively simple algorithms. By changing the detection approach from visual or GPS-based methods to vibration parameter analysis, the system achieves high accuracy with reduced computational complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances user safety and compliance by accurately detecting sidewalk usage, reducing penalties and improving the functioning of transportation services through real-time feedback and operational adjustments.
Implementation Method 1
A personal mobility vehicle may introduce vibrations within the personal mobility vehicle when the personal mobility vehicle moves over a seam of the sidewalk
Data Source
AI summary
In one embodiment, a method includes determining vibration signals detected by a personal mobility vehicle, determining that the vibration signals correspond to an unexpected event occurred to the personal mobility vehicle, generating a feedback signal corresponding to the unexpected event, and transmitting the feedback signal corresponding to the unexpected event.