Cut-In Vehicle Detection for Camera-Radar Driver Assistance
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Solution Overview
Problem
Existing driver assistance systems struggle to effectively avoid collisions with surrounding objects, particularly those cutting into the travel lane at close ranges, due to limited field of view and sensing capabilities.
Innovation Solution
A driver assistance system equipped with a camera and radar sensors that acquire external image and sensing data to determine a nearby vehicle's cut-in area, velocity, and acceleration, allowing for control of the vehicle's braking and steering systems to prevent collisions by identifying potential lane intrusions and calculating necessary avoidance maneuvers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the field of view of sensors is increased to detect nearby vehicles cutting in at close ranges, then collision avoidance capability is improved, but device complexity and cost increase
Solution Approach 1:
The patent combines camera and radar sensors into an integrated sensing system that shares processing resources and data fusion algorithms. This merging approach enables comprehensive collision avoidance detection without proportionally increasing system complexity, as the combined system leverages complementary strengths of each sensor type.
Solution Approach 2:
The sensor system is designed to perform multiple functions: detecting vehicles in adjacent lanes, identifying cut-in maneuvers, measuring velocity and acceleration, and determining cut-in areas. This multi-functionality reduces the need for separate specialized sensors, thereby improving collision avoidance capability without linearly increasing device complexity.
2Measurement precision
If multiple sensors (camera and radar) are used to accurately determine nearby vehicle parameters, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent introduces a controller as an intermediary that fuses data from camera and radar sensors. This mediator processes and integrates information from both sensors to accurately determine nearby vehicle parameters including velocity, acceleration, and cut-in area, achieving high measurement precision while managing system complexity through centralized processing.
Solution Approach 2:
The sensing system uses a composite approach by combining different sensor types (camera for visual information, radar for range and velocity data) to create a more accurate and reliable detection system. This composite sensing strategy improves measurement precision by leveraging the complementary strengths of each sensor modality.
3Reliability
If the system processes detailed image data and radar data to calculate cut-in area and velocity, then collision avoidance reliability is improved, but processing time and computational load increase
Solution Approach 1:
The system performs preliminary processing of image and radar data to identify potential cut-in scenarios before full collision avoidance calculations are required. By pre-processing data to detect vehicles in adjacent lanes and calculate preliminary parameters like velocity and acceleration, the system reduces computational load during critical decision-making moments, maintaining high reliability while minimizing processing time.
Data Source
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AI summary
Disclosed are a driver assistance system for a vehicle, the driver assistance system comprising: a camera disposed on the vehicle to have a field of view of an outside of the vehicle, and configured to acquire external image data; a radar disposed on the vehicle to have a field of sensing of an outside of the vehicle, and configured to acquire radar data; and a controller including a processor configured to process the image data and the radar data, determine a cut-in area of a nearby vehicle on the basis of the image data acquired by the camera, determine a target vehicle on the basis of the determined cut-in area, and control at least one of a braking device or a steering device of the vehicle to avoid a collision with the target vehicle.