Vehicle Electric Device Driver Pattern Recognition
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Solution Overview
Problem
Current vehicle communication systems restrict drivers from using services like hands-free and navigation while driving due to safety concerns, as they are typically connected to passengers' mobile devices, and there is a need to seamlessly switch communication to the driver's device based on pattern recognition.
Innovation Solution
An electric device in a vehicle collects and compares pattern information, such as driving and manipulation patterns, to identify and establish communication with the driver's mobile device, using wireless technologies like Wi-Fi, Bluetooth, and NFC, and updates the pattern information in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the vehicle connects to a mobile device for communication services, then service availability is improved, but driver safety deteriorates when the connected device belongs to a passenger
Solution Approach 1:
The system continuously collects pattern information from multiple sensors (accelerometer, gyroscope, camera, microphone) and compares it with stored driver patterns to dynamically determine whether the current device user is the driver. This feedback mechanism allows the system to switch communication services based on real-time detection, ensuring services are provided only to the driver when appropriate, thus maintaining safety while preserving service availability.
Solution Approach 2:
The system automatically identifies whether the current mobile device user is the driver through pattern recognition and autonomously enables or disables communication services accordingly. This self-service approach eliminates the need for manual driver identification or passenger intervention, allowing the system to independently manage service allocation based on detected usage patterns, thereby maintaining both safety and service availability.
2Object-affected harmful factors
If the vehicle restricts communication services to ensure driver safety, then driver safety is improved, but driver convenience deteriorates
Solution Approach 1:
The system dynamically adjusts service accessibility based on real-time pattern recognition results. When the driver is identified through pattern matching, communication services are fully enabled; when a passenger is detected, services are restricted. This dynamic adaptation allows the system to provide maximum convenience to the driver when safe, while automatically reducing convenience when safety concerns arise, thus resolving the contradiction between safety and convenience.
Solution Approach 2:
The system changes the operational parameters of communication services based on detected pattern correlations. When driver patterns are recognized, service parameters are set to allow full access; when passenger patterns are detected, parameters are adjusted to restrict access. This parameter-based control enables flexible switching between safety-restricted and convenience-optimized states without manual intervention.
3Ease of operation
If the vehicle collects and compares pattern information to identify the driver's mobile device, then driver convenience is improved, but system complexity increases
Solution Approach 1:
The system performs preliminary actions by collecting and storing pattern information from multiple sensors during normal vehicle operation before driver identification is needed. Accelerometer, gyroscope, camera, and microphone data are continuously gathered and stored as baseline driver patterns. When a mobile device connects, the system simply compares incoming data against these pre-collected patterns, significantly reducing the computational complexity of real-time identification while maintaining high driver convenience.
Solution Approach 2:
The system merges multiple data sources (accelerometer, gyroscope, camera, microphone) into a unified pattern recognition framework. By combining these diverse sensor inputs into a single comprehensive pattern matching system, the complexity of handling multiple separate identification mechanisms is reduced. The merged approach allows the system to process all sensor data through a single comparison algorithm, simplifying the overall system architecture while improving identification accuracy and driver convenience.
Data Source
AI summary
A method for controlling an electric device in a vehicle includes: establishing communication with a first mobile device previously recognized by the vehicle; collecting first pattern information from the vehicle; comparing the first pattern information with second pattern information stored in the first mobile device; and discovering a second mobile device based on the comparison of the first pattern information with the second pattern information.