Vehicle Collision Avoidance Using Camera-Based Lane and Vehicle Tracking
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Solution Overview
Problem
Conventional methods for preventing vehicle collisions on adjacent carriageways are ineffective due to reliance on numerous sensors and complex mathematical functions, leading to increased signal processing time and error probability, particularly when determining collision possibilities on straight and curved lanes and distinguishing between passing and running vehicles.
Innovation Solution
An apparatus and method utilizing image data acquisition and recognition to calculate spacing distances and predict relative moving directions between a user's vehicle and adjacent vehicles, generating control signals to prevent collisions, and incorporating driver state analysis to initiate cruise driving when necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If numerous sensors are used to detect vehicle position and movement direction, then measurement precision is improved, but device complexity and signal processing time increase
Solution Approach 1:
The patent combines multiple detection functions (vehicle position, movement direction, lane identification) into a single camera-based vision system. Instead of using separate sensors for each function, the system processes visual information from one or more cameras to extract all necessary parameters, thereby reducing device complexity while maintaining measurement precision.
Solution Approach 2:
The patent replaces traditional mechanical sensors (radar, ultrasonic sensors, inertial measurement units) with an optical vision-based system. By using image processing and computer vision algorithms, the system achieves the same measurement objectives without the complexity of multiple electronic sensors and their associated signal processing circuits.
2Measurement precision
If complex mathematical functions are used to extract curved lanes and predict movement, then measurement precision is improved, but signal processing time increases
Solution Approach 1:
The system performs preliminary processing of image data by pre-segmenting the road surface and identifying lane markings before vehicle movement analysis. By preparing the road model in advance and updating it incrementally as the vehicle moves, the system avoids complex real-time calculations while maintaining accurate curved lane extraction.
Solution Approach 2:
The patent uses a dynamic approach where the road model is continuously updated based on sequential image frames and vehicle movement. Instead of performing complex calculations on each frame independently, the system leverages temporal coherence to track lane curvature dynamically, reducing computational burden while maintaining precision.
3Measurement precision
If radar-based relative distance measurement is used, then measurement precision is improved, but adaptability to different driving scenarios decreases
Solution Approach 1:
The vision-based system is designed to be universally applicable to various driving scenarios including straight roads, curved roads, lane changes, and intersections. By using visual features that are invariant to road geometry and implementing adaptive algorithms, the system maintains measurement precision across different scenarios without requiring scenario-specific sensor configurations.
Data Source
AI summary
The present invention provides an apparatus and method for predicting a moving direction of another vehicle running on a carriageway adjacent to a user's vehicle using periodically acquired image information around the user's vehicle, and performing a control process of preventing collision of the user's vehicle when a moving direction of the user's vehicle crosses the moving direction of the other vehicle.