Multi-Layer Driver Activity Fusion Architecture
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Solution Overview
Problem
Current systems for detecting driver activities in vehicles are inefficient in combining data from multiple sensors to determine complex activities, leading to potential inaccuracies and increased storage and processing requirements.
Innovation Solution
A multi-layer software and hardware architecture that uses activity fusion modules to combine data from various sensors in a common format, allowing for flexible detection of complex activities and efficient communication between layers, with each layer focusing on specific aspects of driver activity recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensors are used to detect driver activities, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system is divided into multiple layers (first layer with activity recognition modules, second layer with fusion modules) that process different aspects of driver activity independently. Each layer handles specific sensor data types and combines them systematically, reducing overall system complexity while maintaining comprehensive detection capabilities across multiple sensors
Solution Approach 2:
Activity fusion modules serve as intermediary components between individual activity recognition modules and the final detection output. These fusion modules aggregate data from multiple sensors and recognition modules, standardizing complex multi-sensor inputs into unified activity determinations, thereby managing system complexity while preserving measurement precision
2Measurement precision
If comprehensive sensor data is processed, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The processing pipeline is segmented into parallel layers where the first layer performs initial activity recognition from sensor data and the second layer performs fusion and combination. This segmentation enables concurrent processing of different data streams, reducing overall processing time while maintaining comprehensive analysis of all sensor inputs for accurate driver activity detection
Solution Approach 2:
The first layer performs preliminary activity recognition and filtering of sensor data before passing processed information to the second layer. By pre-processing and organizing data in advance, the system reduces the computational burden on subsequent fusion operations, thereby decreasing total processing time while preserving measurement precision
3Measurement precision
If activity fusion modules combine data from multiple sources, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The software architecture is segmented into distinct layers with clear responsibilities: the first layer handles activity recognition from individual sensors, while the second layer handles fusion and combination. This segmentation organizes complexity into manageable modules, making the system easier to implement and maintain while achieving high measurement precision through comprehensive data integration
Solution Approach 2:
The activity fusion modules are designed as universal components that can handle multiple types of sensor data and activity recognition outputs through standardized interfaces. This multi-functionality allows the same fusion module architecture to process diverse data sources without increasing complexity, enabling comprehensive data combination while maintaining software architecture simplicity
Data Source
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AI summary
It is described a method for detecting one or more activities of a driver of a vehicle, the method comprising: receiving, by a first activity fusion module of a first layer, one or more activities of a body part of a driver from each activity recognition module of a plurality of activity recognition modules of the first layer using a common data format; determining, by a first activity fusion module of the first layer, one or more combined activities from the one or more received activities; sending, by the first activity fusion module of the first layer, the one or more combined activities to a second activity fusion module of a second layer using the common data format; receiving, by the second activity fusion module of the second layer, one or more activities of a control of a vehicle from each activity recognition module of a plurality of activity recognition modules of the second layer using the common data format; receiving, by the second activity fusion module of the second layer, the one or more combined activities from the activity fusion module of the first layer using the common data format; and determining, by the second activity fusion module of the second layer, one or more combined activities of the one or more received activities of each of the activity recognition modules of the second layer and the one or more received combined activities of the first activity fusion module of the first layer.