Radar Point Cloud Accumulation for Vehicle Seat Occupancy Detection
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Solution Overview
Problem
Existing solutions for automatically detecting seat occupancy in vehicles require built-in sensors in seats, which are difficult to retrofit and cannot distinguish between different occupancy states beyond 'occupied' or 'unoccupied'.
Innovation Solution
A method using radar point clouds to detect seat occupancy, where measurement data from radar scans is accumulated to form a sequence of radar point clouds, and an evaluation model determines the seat occupancy state based on these accumulated data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If built-in pressure-sensitive sensors are integrated into seats at the factory, then seat occupancy detection can be achieved, but retrofitting becomes difficult or impossible and the system cannot detect occupancy states of seats not equipped with sensors
Solution Approach 1:
The patent replaces mechanical pressure-sensitive sensors integrated into seats with a radar-based detection system. The radar sensor emits electromagnetic signals that reflect off objects in the detection area, allowing occupancy detection without physical contact or integration into the seat structure. This substitution enables retrofitting of existing vehicles while maintaining reliable detection capability.
Solution Approach 2:
The radar-based system provides universal detection capability across all seats in the vehicle without requiring individual sensor integration. A single radar sensor can detect occupancy states of multiple seats simultaneously, making the system adaptable to different vehicle configurations and enabling retrofits in vehicles that originally lacked such detection capabilities.
2Reliability
If built-in sensors are used for seat occupancy detection, then occupancy state can be determined, but the system cannot distinguish between different seat occupancy states beyond 'occupied' or 'unoccupied'
Solution Approach 1:
The patent utilizes multiple radar signal parameters including amplitude, phase, frequency, and time-of-flight information to characterize detected objects. By analyzing these varying parameters, the system can distinguish between different occupancy states such as empty seat, occupied by adult, occupied by child, or occupied by animal, thereby preserving information that would be lost with simple binary sensor outputs.
Solution Approach 2:
The radar system introduces an intermediary evaluation model that processes raw radar signals and translates them into meaningful occupancy state classifications. This evaluation layer analyzes signal characteristics and patterns to differentiate between various types of occupants, providing detailed occupancy information without requiring complex sensor integration in each seat.
3Reliability
If radar scans are performed continuously to detect seat occupancy states, then detection reliability is improved, but energy consumption increases
Solution Approach 1:
The patent implements periodic radar scanning at optimized intervals rather than continuous scanning. The radar sensor performs detection cycles at specific frequencies, accumulating data over multiple measurement frames. This periodic approach maintains sufficient detection reliability for safety-critical applications while significantly reducing average power consumption compared to continuous operation.
Solution Approach 2:
The system performs preliminary rapid scans to detect potential occupancy changes, then activates more detailed evaluation only when changes are detected. This preliminary action allows the system to maintain low energy consumption during stable conditions while quickly responding to occupancy events, balancing reliability requirements with energy efficiency.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method allows for reliable detection of seat occupancy states, including distinguishing between different types of objects, and enables the activation or deactivation of vehicle functionalities such as seatbelt warnings and airbag control.
Implementation Method 1
Each radar point cloud of the sequence was or is obtained on the basis of a radar scan of a spatial region surrounding at least some sections of the seating arrangement
Data Source
AI summary
A method for the automated detection of a seat occupancy state, in particular related to each seat, of a seating arrangement having at least one seat comprises: receiving or generating measurement data, which represents in each case one assigned radar point cloud for each measurement frame of a sequence of a plurality of temporally consecutive measurement frames, so that the measurement data represent a sequence of radar point clouds corresponding to the sequence of measurement frames, wherein each radar point cloud of the sequence was or is obtained on the basis of a radar scan of a spatial region surrounding at least some sections of the seating arrangement, which takes place at a measurement time or during a measurement period assigned to the respective measurement frame; accumulating a plurality of the radar point clouds of the sequence in order to obtain an accumulated radar point cloud containing radar points from each of the individual radar point clouds combined as part of the accumulating process; determining a seat occupancy state of the seating arrangement on the basis of an evaluation model, which returns, as a function of the accumulated radar point cloud, one of a plurality of predefined possible seat occupancy states of the seating arrangement as an evaluation result; and outputting a piece of information defined according to the evaluation result.