Vehicle Occupancy Detection for Automatic Cabin Setting Adjustment
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Solution Overview
Problem
Vehicles often experience changes in occupancy states over time, leading to inconsistent settings for audio, entertainment, and climate-control systems, which can be inconvenient for occupants.
Innovation Solution
Implementing sensors and a probabilistic model within vehicles to determine occupancy states and adjust settings accordingly, such as volume, entertainment system usage, and climate control, based on detected changes in occupancy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If vehicle settings are manually adjusted for each occupancy state, then occupant comfort and convenience are improved, but the complexity of operation and time required increase
Solution Approach 1:
The vehicle system automatically detects occupancy state changes using sensors and probabilistic models, then autonomously adjusts audio, entertainment, and climate-control settings without requiring manual intervention from occupants. This self-service approach eliminates the time and effort previously needed for manual adjustments while maintaining optimal comfort settings for each occupancy scenario.
Solution Approach 2:
The system pre-configures multiple occupancy state profiles with optimized settings for different scenarios (e.g., single occupant, multiple occupants, driver only). When an occupancy state change is detected, the system quickly applies the pre-prepared settings from the matching profile, avoiding the need for real-time manual adjustment and reducing the time lag between occupancy change and optimal setting application.
2Extent of automation
If automated sensors and probabilistic models are implemented to detect occupancy states, then setting adjustments become automatic and convenient, but device complexity increases
Solution Approach 1:
The patent leverages existing multi-functional vehicle components, particularly the camera system originally designed for driver monitoring and safety features. By repurposing these existing sensors to also detect passenger occupancy states, the system achieves automated occupancy detection without adding dedicated specialized sensors, thereby reducing overall system complexity while maintaining high automation capability.
Solution Approach 2:
The system introduces a probabilistic model as an intermediary layer that processes sensor data and determines occupancy states. This probabilistic approach handles the complexity of interpreting ambiguous sensor readings (e.g., distinguishing between a sleeping passenger and an empty seat) without requiring complex hardware, allowing the system to achieve accurate automated detection while keeping the physical device complexity manageable.
Data Source
AI summary
This disclosure is directed to, in part, techniques for determining occupancy states of a vehicle over time and adjusting settings associated with the vehicle based at least in part on these occupancy states. For instance, an example vehicle may include an array of sensors that may generate sensor data for identifying an occupancy state of a vehicle. These sensors may include cameras, microphones, in-seat weight sensors, seatbelt sensors, door-latch sensors, and the like, which may be used to generate sensor data indicative of a current occupancy state of a vehicle. An occupancy state may include a number of occupants of the vehicle, the location of these occupants within the vehicle, the identity of these occupants, and/or the like.