Leaning Vehicle Corner Segmentation for Accurate Riding-State Output
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Solution Overview
Problem
Existing leaning vehicle data output systems face challenges in increasing the accuracy of vehicle-traveling-state data while turning on corners without increasing the hardware resource load, as they struggle to effectively evaluate driving skills during cornering maneuvers.
Innovation Solution
The system divides the corner into multiple sections (deceleration, entry, turning, and rising) and generates vehicle-traveling-state data for each section, allowing for more accurate evaluation of driving skills without increasing data resolution, thereby reducing the computational load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data resolution is increased to enhance accuracy of vehicle-traveling-state data, then measurement precision is improved, but hardware resource load increases
Solution Approach 1:
The corner is divided into multiple sections (deceleration section, entry section, turning section, and rising section) based on vehicle behavior characteristics. By segmenting the corner into these functional sections, the system can evaluate driving skills in each specific section rather than treating the entire corner as one unit. This segmentation enables accurate evaluation of different driving phases without requiring increased data resolution, thus improving measurement precision while avoiding increased hardware resource load.
2Device complexity
If the entire corner is evaluated as one unit, then device complexity is reduced, but measurement precision of driving skill evaluation decreases
Solution Approach 1:
The corner is divided into multiple sections (deceleration section, entry section, turning section, and rising section) based on vehicle behavior characteristics. By segmenting the corner into these functional sections, the system can evaluate driving skills in each specific section rather than treating the entire corner as one unit. This segmentation enables accurate evaluation of different driving phases without requiring increased data resolution, thus improving measurement precision while avoiding increased hardware resource load.
Solution Approach 2:
Different evaluation criteria and data processing methods are applied to different sections of the corner based on their specific characteristics. For example, the deceleration section focuses on braking performance, the entry section on lean angle control, the turning section on steady-state handling, and the rising section on exit acceleration. This local quality approach allows each section to be evaluated with appropriate precision while keeping the overall system relatively simple.
Data Source
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AI summary
A leaning-vehicle-data-output apparatus is provided which is capable of increasing accuracy of output data including vehicle-traveling-state data of a leaning vehicle while suppressing an increase in load of a hardware resource. A leaning-vehicle-traveling-state-data-output device 20a includes a physical-quantity-data acquirer 21 configured to acquire physical quantity data concerning a behavior of a leaning vehicle 1, a vehicle-traveling-state-data generator 24 configured to generate vehicle-traveling-state data based on the physical quantity data and a vehicle-traveling-state-data-output controller 25 configured to output the vehicle-traveling-state data. The vehicle-traveling-state-data generator 24 generates vehicle-traveling-state data of the leaning vehicle 1 in each of sections based on physical quantity data, the sections being obtained by dividing, into a plurality of sections, a single corner on which the leaning vehicle 1 turns while leaning to perform yaw motion continuously in an identical direction, the physical quantity data being acquired by the physical-quantity-data acquirer and concerning a behavior of the leaning vehicle 1 while the leaning vehicle 1 turns left on the corner while leaning leftward or turns right on the corner while leaning rightward.