Navigation-Based EV Driving Sound Personalization Control
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Solution Overview
Problem
Electric vehicles lack a natural driving sound and vibration, making it difficult for drivers to customize their driving experience, as the artificially generated sound is predetermined by the manufacturer.
Innovation Solution
A vehicle system that includes a database of sound sources classified by emotions or terrains, a controller that uses navigation system data to select and synthesize driving sounds based on landmarks or map images, and a speaker to output these sounds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a fixed manufacturer-designed driving sound is used, then the system is simple and reliable, but the adaptability to different driving conditions and user preferences is poor
Solution Approach 1:
The patent implements dynamic sound selection by allowing the driving sound to change based on navigation information (landmarks, terrain) and driver emotion states. The controller dynamically switches between different sound sources stored in the database, making the sound system adaptive rather than static. This resolves the contradiction by enabling versatility through dynamic adjustment while maintaining a relatively simple overall structure.
Solution Approach 2:
The system changes the parameter of sound characteristics by selecting from multiple pre-stored sound sources with different emotional classifications (happy, sad, angry, etc.). By changing the emotional parameter of the output sound based on detected driver state and navigation context, the system achieves adaptability without requiring complex real-time sound generation, thus managing device complexity.
2Adaptability or versatility
If multiple sound sources and emotion recognition are added, then the adaptability and personalization improve, but the device complexity increases
Solution Approach 1:
The system performs preliminary action by pre-classifying and storing multiple sound sources in the database according to different emotional categories before actual use. When the driver needs personalized sound, the controller simply retrieves and switches between pre-prepared sound sources based on detected emotions and navigation context, rather than generating sounds in real-time. This reduces the complexity of the control system while achieving personalization.
Solution Approach 2:
The patent uses copying by storing multiple copies of driving sounds with different emotional characteristics in the database. Instead of creating complex real-time sound synthesis, the system copies appropriate pre-recorded sounds matching the current driver state and navigation situation. This approach achieves personalization through simple retrieval and playback of copied sound sources, minimizing control system complexity.
3Productivity
If AI-based emotion recognition and landmark analysis are implemented, then the driving experience becomes more engaging, but the computational requirements and processing time increase
Solution Approach 1:
The system applies preliminary action by pre-classifying sound sources into different emotional categories during system setup. When processing driver emotions and navigation information in real-time, the controller only needs to match the current state against pre-classified categories and retrieve corresponding sounds, rather than performing complex AI analysis during sound generation. This reduces processing time while maintaining driver engagement through personalized sound selection.
Data Source
AI summary
A vehicle selects various sound sources and outputs driving sound based on information received from the navigation system. A database stores sound sources classified as first and second emotions. A controller outputs a landmark name based on a route guidance text and outputs a ratio of the first and second emotions corresponding to the landmark name. The controller selects a first sound source from the sound sources classified as the first emotion based on the first emotion ratio, selects a second sound source from the sound sources classified as the second emotion based on the second emotion ratio and determines first and second playback periods based on the ratios of the first and second emotions. The controller outputs a first sound generated based on the first sound source during the first playback period and a second sound generated based on the second sound source during the second playback period.