Straddle-Type Vehicle Falling Phase Recognition via Instability Trend
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Solution Overview
Problem
Conventional vehicle information processors inaccurately recognize the falling phase in straddle-type vehicles due to significant changes in angular velocity, leading to increased erroneous recognition and delayed safety alerts, particularly in vehicles with lower occupant safety.
Innovation Solution
A straddle-type vehicle information processor that acquires roll rate and yaw rate data to derive a degree of instability over time, recognizing a falling phase when the change in instability shows an increasing tendency, thereby preventing erroneous recognition and enabling timely safety alerts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the limit value for angular velocity is set high to prevent erroneous recognition, then the frequency of erroneous recognition decreases, but the recognition of the falling phase delays
Solution Approach 1:
The patent transitions from a static threshold-based recognition system to a dynamic trend-based recognition system. Instead of using a fixed angular velocity limit value, the system dynamically evaluates whether angular velocity is exceeding a reference value and whether the degree of instability is increasing over time. This allows the system to adapt to changing vehicle states and distinguish between temporary fluctuations and actual falling phases, resolving the contradiction between avoiding false alarms and timely detection.
Solution Approach 2:
The patent introduces a feedback mechanism by continuously monitoring the degree of instability over time and comparing it against reference values. The falling phase recognition section receives feedback from the posture information acquisition section about current angular velocities and instability degrees, and uses this feedback to determine whether a falling phase is occurring. This feedback loop enables accurate recognition without delayed response.
2Loss of time
If the limit value is set low to enable timely recognition, then the recognition timing improves, but the frequency of erroneous recognition increases
Solution Approach 1:
The system uses dynamic evaluation of instability trends rather than a fixed low threshold. By assessing whether the degree of instability is increasing over time compared to reference values, the system can respond quickly to actual falling phases while filtering out temporary angular velocity spikes that would trigger false alarms with static thresholds.
Solution Approach 2:
The patent establishes reference values for angular velocity and degree of instability before the falling phase occurs. These reference values serve as preliminary criteria against which current states are compared. By having these references prepared in advance and using trend analysis, the system can recognize falling phases timely without being triggered by normal operational variations.
3Device complexity
If conventional threshold-based recognition is used, then the system complexity remains low, but the recognition accuracy deteriorates due to significant angular velocity changes in straddle-type vehicles
Solution Approach 1:
The patent changes the recognition parameters from simple angular velocity threshold comparison to a composite evaluation involving degree of instability calculation and temporal trend analysis. Instead of merely comparing angular velocity against a fixed limit, the system calculates instability degrees based on multiple sensors (accelerometers, gyroscopes) and evaluates whether this instability is increasing over time. This parameter transformation maintains reasonable system complexity while dramatically improving detection accuracy for straddle-type vehicles.
Solution Approach 2:
The recognition system is designed to handle multiple vehicle types and operating conditions through a universal instability-based approach. The same degree of instability calculation and trend evaluation methodology works for different straddle-type vehicles regardless of their specific angular velocity characteristics, providing accurate recognition without requiring vehicle-specific threshold tuning.
Data Source
AI summary
The invention obtains a straddle-type vehicle information processor and a straddle-type vehicle information processing method capable of recognizing that a traveling straddle-type vehicle enters a falling phase with a high degree of accuracy at appropriate timing and thereby contributes to improvement in occupant safety.A straddle-type vehicle information processor 10 includes: a posture information acquisition section 11 that at least acquires a roll rate Rr and a yaw rate Ry generated in a traveling straddle-type vehicle 1 as posture information; and a falling phase recognition section 12 that recognizes that the straddle-type vehicle 1 enters a falling phase in the case where a change in a degree of instability over time, which is derived at least on the basis of the roll rate Rr and the yaw rate Ry, shows an increasing tendency.