Automatic Mirror Adjustment Using In-Car Camera System
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Solution Overview
Problem
Blind zones in vehicle mirrors due to incorrect alignment lead to accidents, as many drivers are unaware of how to correctly align mirrors, and manual adjustments are often cumbersome, especially in unfamiliar vehicles.
Innovation Solution
An automatic mirror adjustment system using an in-car camera system that determines the driver's field of view, adjusts mirrors based on driver and vehicle characteristics, and provides manual fine-tuning options, utilizing existing cameras to reduce blind zones and alert users of misalignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual mirror adjustment is used, then drivers can adjust mirrors according to their preferences, but the process is too bothersome for single trips and many drivers do not know how to align mirrors correctly
Solution Approach 1:
The system automatically performs mirror adjustment without requiring driver intervention. The camera system detects driver position and automatically adjusts mirrors to optimal angles, eliminating the manual adjustment process while ensuring correct alignment through algorithmic calculation of optimal mirror positions based on driver characteristics.
Solution Approach 2:
The system pre-calculates and stores optimal mirror adjustment positions for different driver types and seating positions. When a driver enters the vehicle, the system retrieves the appropriate pre-calculated positions and applies them automatically, eliminating the need for real-time manual adjustment or complex real-time calculations.
2Reliability
If automatic mirror adjustment using camera system is implemented, then blind zones are reduced and driver safety is improved, but device complexity increases
Solution Approach 1:
The system uses the existing in-car camera that serves multiple functions (driver monitoring, attentiveness detection, drowsiness detection) for the additional purpose of mirror adjustment. By reusing the existing camera hardware and processing capabilities, the system avoids adding dedicated sensors or complex hardware while achieving multiple safety functions simultaneously.
Solution Approach 2:
The system uses image processing algorithms as an intermediary to translate camera footage into driver position information and mirror adjustment commands. Rather than requiring direct mechanical linkages or complex sensor arrays, the software-based intermediary processes visual data to determine optimal mirror positions, simplifying the physical system architecture.
3Area of stationary object
If mirrors are adjusted based on driver characteristics, then visibility is improved and blind zones are reduced, but the system requires complex processing to determine field of view and driver position
Solution Approach 1:
The system replaces complex mechanical measurement devices with optical-based camera systems and image processing. Instead of using mechanical sensors to directly measure driver position, the system uses visual field analysis through camera footage, substituting mechanical measurement with optical detection and computational analysis.
Solution Approach 2:
The system creates a digital representation (copy) of the driver's field of view by analyzing camera images. By generating a computational model of where the driver is looking and what areas are visible, the system can determine optimal mirror positions without requiring physical measurement devices, using instead a virtual copy of the visual environment.
Data Source
AI summary
An apparatus comprising a sensor, an interface and a processor. The sensor may be configured to generate a video signal based on a targeted view of a driver. The interface may be configured to receive status information about one or more components of a vehicle. The processor may be configured to generate a control signal in response to a determined field of view of the driver. The control signal may be used to adjust one or more mirrors of the vehicle. The field of view may be determined based on (i) the video signal and (ii) the status information.