Vehicle HMI Wake-Up Control Using Occupant and Destination Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing vehicle systems lack the ability to efficiently determine optimal wake-up times for occupants based on destination, object presence, and user preferences, leading to inefficient or inappropriate vehicle component actuation.
Innovation Solution
A vehicle computer system that determines a wake-up time for occupants by analyzing destination data, object classification, user input, and various factors such as sleep state, traffic conditions, and historical data to actuate vehicle components like displays and audio devices at appropriate times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the vehicle system actuates components based on simple fixed schedules, then the system complexity is low, but the user experience and timing accuracy are poor
Solution Approach 1:
The system performs preliminary detection of occupant presence and classification before determining the wake-up time. Sensors detect objects in the vehicle interior and classify them as occupants or non-occupants, then use this information along with destination data to calculate an optimal wake-up time that accounts for travel duration and preparation needs.
Solution Approach 2:
The system continuously monitors vehicle state, sensor data, and navigation information to dynamically adjust wake-up time predictions. It uses feedback from object detection sensors, destination updates, and travel condition changes to refine the wake-up time calculation and ensure accurate timing.
2Adaptability or versatility
If the system considers multiple factors (destination, objects, user preferences) to determine wake-up time, then the user experience is improved, but the computational complexity increases
Solution Approach 1:
The system segments the wake-up time determination process into distinct functional modules: object detection sensors identify occupants, a classifier distinguishes occupants from non-occupants based on object characteristics, a navigation system provides destination data, and a calculator integrates these inputs with user preferences to compute the optimal wake-up time. This modular segmentation reduces processing complexity while maintaining comprehensive personalization.
3Measurement precision
If the system uses sensor detection to identify objects and classify them, then the accuracy of occupant identification is improved, but the time required for processing increases
Solution Approach 1:
The classifier performs partial classification by focusing on key distinguishing features of occupants versus non-occupants rather than analyzing all possible object characteristics. It uses sensor data to identify critical attributes (such as object position, size, and type) that sufficiently distinguish occupants from other objects, achieving accurate identification without exhaustive processing of all object properties.
Data Source
AI summary
A system comprises a computer having a processor and a memory. The memory stores instructions executable by the processor to determine a wakeup time for an occupant of a vehicle based on a destination and an object in an interior of the vehicle, and actuate a vehicle component to awaken the occupant.