Vehicle Proximity Audio Response for Entity Risk Classification
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Solution Overview
Problem
Existing vehicle systems lack effective methods for detecting and interacting with entities within a specified distance, particularly in classifying and responding to entities based on their characteristics and risk levels, which can lead to inadequate vehicle component activation.
Innovation Solution
A vehicle computer system that utilizes sensors to detect entities within a specified distance, classifies them based on collected data, and activates vehicle features accordingly, including outputting audio and adjusting vehicle components based on risk scores and language detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the vehicle outputs audio and activates features for all detected entities, then interaction coverage is improved, but energy consumption and false positive responses increase
Solution Approach 1:
The patent applies local quality by differentiating the response strategy based on entity classification. Threatening entities receive audio warnings and feature deactivation, while non-threatening entities receive normal interaction. This selective approach ensures energy is consumed only when necessary for safety-critical responses, rather than uniformly for all detected entities.
Solution Approach 2:
The system changes the parameter of interaction intensity based on the threat classification parameter. For threatening entities, the system activates safety features and outputs audio warnings. For non-threatening entities, the system maintains normal operation without additional energy-consuming responses. This dynamic parameter adjustment resolves the contradiction between comprehensive interaction and energy efficiency.
2Measurement precision
If the vehicle classifies entities using multiple data sources and analysis methods, then classification accuracy is improved, but computational complexity and processing time increase
Solution Approach 1:
The patent segments the classification process into distinct modules: sensor data acquisition, image processing, audio analysis, and integration/decision-making. Each module handles a specific aspect of entity characterization independently. This segmentation allows the system to achieve high classification accuracy through multiple data sources while managing computational complexity through modular architecture, where each segment can be optimized separately.
Solution Approach 2:
The system employs multi-functional sensors and processing units that serve multiple purposes. For example, sensors detect both presence and characteristics of entities, and the processing system performs both classification and risk assessment. This universality reduces overall system complexity compared to having separate dedicated systems for each function, while maintaining high classification accuracy through comprehensive data analysis.
3Speed
If the vehicle responds immediately to all detected entities, then response time is improved, but false positive reactions and unnecessary feature activation increase
Solution Approach 1:
The patent implements preliminary action by performing entity classification and threat assessment before activating safety features or outputting audio warnings. The system pre-processes sensor data, analyzes entity characteristics, and determines threat level in advance of the actual response. This preliminary classification ensures that immediate responses are triggered only by genuinely threatening entities, reducing false positives while maintaining fast response times for confirmed threats.
Solution Approach 2:
The system incorporates feedback mechanisms where the classification results and risk scores feed back into the decision-making process. The audio output and feature activation are conditioned on the feedback from entity classification. This feedback loop allows the system to adjust its response based on the analyzed data, ensuring that immediate responses are proportional to the actual threat level and reducing unnecessary activations while maintaining rapid response capability.
Data Source
AI summary
A vehicle may detect an entity within a specified distance of a vehicle, output a first audio outside of the vehicle in response to detecting the entity, classify the entity based on data collected about the entity after outputting the first audio, and output a second audio based on classifying the entity.