Self-balancing vehicle adaptive speed control
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Solution Overview
Problem
Existing smart self-balancing vehicles lack a unified and adaptive safety mechanism to accommodate varying rider experiences and proficiency levels, as they rely on fixed speed limits and user-defined settings, which do not dynamically adjust to individual rider performance.
Innovation Solution
A method and device that determine a user level based on riding data such as time, distance, shaking frequency, and shaking arc magnitude, allowing for real-time adjustment of startup acceleration to ensure safe riding by limiting or unlocking speed according to the user's proficiency level.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If fixed speed limits are implemented for safety, then safety is improved, but adaptability to different rider skill levels deteriorates
Solution Approach 1:
The patent implements dynamic speed limits that automatically adjust based on real-time riding data analysis. The system transitions from static, fixed speed limits to dynamic, adaptive speed limits that change according to the rider's demonstrated skill level, thereby resolving the contradiction between safety and adaptability.
Solution Approach 2:
The system continuously collects riding data (shaking frequency, arc magnitude, riding time) and uses this feedback to automatically evaluate and adjust the rider's skill level. This closed-loop feedback mechanism enables the speed limit to adapt to the rider's improving skills, maintaining safety while increasing adaptability.
2Adaptability or versatility
If user-defined settings are used, then adaptability is improved, but ease of operation deteriorates
Solution Approach 1:
The system performs automatic skill level evaluation and speed limit adjustment without requiring user intervention. The rider simply operates the vehicle normally while the system autonomously collects data, evaluates performance, and configures appropriate speed limits, eliminating the need for manual settings while maintaining adaptability.
Solution Approach 2:
The system proactively evaluates riding data and adjusts speed limits before safety issues arise. By continuously monitoring and preemptively adapting the speed limit based on skill level, the system eliminates the need for users to manually configure settings, thereby improving ease of operation while maintaining adaptability.
3Reliability
If startup acceleration is limited for safety, then safety is improved, but productivity deteriorates
Solution Approach 1:
The patent implements dynamic startup acceleration limits that adjust based on the rider's skill level. Beginner riders experience limited startup acceleration for safety, while experienced riders automatically gain higher acceleration performance through automatic skill-based adjustment, resolving the contradiction between safety and productivity.
Solution Approach 2:
The system changes the startup acceleration parameter dynamically based on evaluated skill level. By adjusting this critical performance parameter according to rider competency, the system maintains safety for beginners while enabling high performance for experienced riders, eliminating the trade-off between safety and productivity.
Data Source
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AI summary
The present invention relates to a method and a device for safety driving. The method includes: acquiring (S101) riding data of a current user of a self-balancing vehicle; comparing (S 102) the riding data with riding data corresponding to a preset user level; and determining (S103) a user level of the current user of the self-balancing vehicle according to a result of the comparing.