Vehicle Behavior Model Matching Using Time-Waveform Simulation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for customizing vehicle settings based on user preferences involve significant human effort and burden, such as trial and error, which is inefficient and labor-intensive.
Innovation Solution
A data processing apparatus and method that uses multiple vehicle models with different parameter settings to simulate vehicle behaviors, identifying the most similar model to a target behavior based on driving operation data, using similarity evaluation of time waveforms to determine optimal settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual trial and error methods are used to customize vehicle settings, then user preference matching can be achieved, but the process becomes labor-intensive and time-consuming
Solution Approach 1:
The patent creates virtual copies (digital twins) of the vehicle that replicate real-world vehicle behavior. These digital twins are used to simulate and evaluate different vehicle settings without requiring physical trial and error, thereby reducing time consumption while maintaining accurate behavior matching.
Solution Approach 2:
The system performs preliminary simulations using digital twins to predict vehicle behavior under different settings before actual implementation. This preliminary evaluation allows optimization of vehicle settings in advance, avoiding repeated manual adjustments and reducing overall setting time.
2Measurement precision
If multiple vehicle models with different parameter settings are simulated, then accurate identification of optimal settings is achieved, but computational complexity increases
Solution Approach 1:
The patent extracts only the essential parameters and characteristics needed for vehicle behavior simulation into simplified digital twin models. By focusing on key parameters rather than complete vehicle complexity, the system achieves accurate model identification while reducing computational burden.
Solution Approach 2:
The system varies specific parameters in vehicle models to explore different behavior characteristics. By systematically changing key parameters and evaluating their impact through similarity metrics, the system identifies optimal settings without requiring exhaustive simulation of all possible configurations.
3Measurement precision
If time waveform-based similarity evaluation is used, then vehicle behavior matching precision is improved, but processing requirements increase
Solution Approach 1:
The patent uses continuous time waveform data from digital twin simulations to evaluate vehicle behavior similarity. By analyzing the temporal continuity of behavior patterns rather than discrete snapshots, the system achieves precise matching while utilizing efficiently the simulation data already generated.
Data Source
AI summary
A data processing apparatus includes one or more processors, and one or more recording media including a program to be executed by the one or more processors stored therein. The program includes one or more commands that cause the one or more processors to execute: a simulation process of performing, based on driving operation data of a vehicle, a simulation of a vehicle behavior of the vehicle using vehicle models having different parameter settings; and a model identifying process of identifying one or more of the vehicle models that satisfy a predetermined similarity condition by evaluating a similarity of a vehicle behavior of each of the vehicle models to be obtained in the simulation process with a target vehicle behavior. Evaluating the similarity in the model identifying process is based on respective time waveforms of the vehicle behavior obtained in the simulation process and the target vehicle behavior.