Vehicle Collision Warning System Using Color-Coded Video Highlighting
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Solution Overview
Problem
Current vehicle collision warning systems lack effectiveness in intuitively alerting drivers of impending collisions, particularly in conveying relevant information in a manner that is easily understandable and applicable across various driving conditions.
Innovation Solution
A collision warning system that utilizes a vision system to provide enhanced video of an upcoming road segment, highlighting in-path objects based on collision data, such as time-to-collision information, to be displayed to the driver through a visual interface like a heads-up display, instrument panel, or center console.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If collision warning systems provide basic audible or visual warnings, then drivers are alerted of impending collisions, but the warnings lack intuitiveness and fail to convey additional relevant information effectively
Solution Approach 1:
The system overlays colored highlights on detected objects in the video feed, using different colors to indicate different collision risks or object types. This visual enhancement conveys multiple pieces of information simultaneously while maintaining intuitive understanding through color-coded alerts.
Solution Approach 2:
The system transitions from basic 2D video display to enhanced video with overlay elements that add a third visual dimension through color-coded annotations. This dimensional enhancement provides additional information layers without complicating the basic visual interface.
2Loss of information
If the system highlights all detected objects, then comprehensive information is provided, but the visual display becomes complex and difficult to interpret
Solution Approach 1:
The system applies different visual qualities (highlighting vs. no highlighting) to different regions of the display based on collision risk assessment. Only objects posing potential collision threats are highlighted with enhanced visual properties, while other objects remain unhighlighted, creating local differentiation that reduces overall visual complexity.
Solution Approach 2:
The visual display is segmented into highlighted regions (objects with collision risk) and non-highlighted regions (objects without immediate risk). This segmentation allows the system to present comprehensive information while maintaining visual simplicity by clearly distinguishing between different priority levels.
3Reliability
If the system processes and displays enhanced video with highlights, then situational awareness is improved, but processing time and computational resources increase
Solution Approach 1:
The system performs object detection and collision risk assessment in advance, before video display is needed. By pre-processing the video feed to identify and flag potential collision objects, the system reduces real-time processing requirements and enables rapid display of enhanced video when needed.
Solution Approach 2:
The system replaces complex real-time video processing with pre-computed collision data overlays. Instead of processing entire video frames in real-time, the system uses predetermined collision algorithms to generate highlight masks that are applied to the video feed, reducing computational burden during critical display moments.
Data Source
AI summary
A vehicle collision warning system and method that alerts a driver of an impending collision by displaying enhanced video of an upcoming road segment, where the enhanced video includes an in-path object that is highlighted so that it stands apart. In one exemplary embodiment, the system and method receive video of an upcoming road segment from a forward-looking vision system, obtain certain collision data for an in-path object, and then use the video and the collision data to provide enhanced video to a visual display that is seen by the driver. The enhanced video may include an in-path object that is highlighted according to the collision data (e.g., highlighted with a color-coded scheme where the in-path object changes color based on time-to-collision data) so that it stands apart from the rest of the upcoming road segment.