Blind Zone Assist Using Radar and Steering Torque Overlay
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Solution Overview
Problem
Existing vehicle blind zone assist systems rely on image-capturing devices that are ineffective in adverse environmental conditions and may not be present in all vehicles, leading to reduced efficacy in avoiding collisions during lane changes.
Innovation Solution
A method and system for active blind zone assist that uses radar sensors and a processor to estimate the position and heading angle of a target vehicle without an image-capturing device, applying a torque overlay to the steering system to avoid collisions by predicting time to collision and using transformation functions and linear regression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image-capturing devices (cameras) are used for blind zone assist, then lane indicator detection and target vehicle position determination are improved, but system reliability deteriorates in adverse environmental conditions
Solution Approach 1:
The patent replaces optical image-capturing devices with radar sensors that use electromagnetic wave reflection. Radar sensors transmit electromagnetic waves and detect reflected waves from target vehicles, enabling blind zone monitoring without relying on visual lane indicators. This substitution maintains target vehicle detection capability while eliminating susceptibility to adverse environmental conditions such as fog, rain, or poor lighting that affect camera-based systems.
2Measurement precision
If camera-based systems are used for blind zone assist, then visual lane detection is improved, but system versatility deteriorates due to absence of image-capturing devices in some vehicles
Solution Approach 1:
The patent substitutes camera-based visual detection with radar sensor-based electromagnetic wave detection. Radar sensors are more universally installed in modern vehicles and do not require external visual conditions or additional image-capturing hardware. This enables the blind zone assist system to function across diverse vehicle types and configurations without dependency on optional camera equipment.
3Reliability
If radar sensors are used instead of cameras, then system reliability in adverse conditions is improved, but lane indicator detection capability deteriorates
Solution Approach 1:
The patent extracts the lane indicator detection function from the radar sensor's primary role and replaces it with host vehicle positioning logic. Instead of detecting lane indicators directly, the system uses the host vehicle's own position, steering angle, and speed data to calculate which lane the vehicle is in or will enter. This extraction allows radar to focus on target vehicle detection while lane determination is achieved through computational methods.
Solution Approach 2:
The patent introduces host vehicle state data (position, steering angle, speed) as an intermediary to bridge the gap between radar detection and lane determination. These intermediary parameters enable the system to infer lane information without direct visual detection, combining radar target detection with vehicle dynamics data to achieve both reliability and lane awareness.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables effective collision avoidance in various environmental conditions and without the need for image-capturing devices, improving the reliability of blind zone assist systems by using sensor data to direct the vehicle away from potential hazards.
Implementation Method 1
at least one radio detection and ranging sensor disposed proximate a rear portion of a host vehicle
Data Source
AI summary
A method includes receiving, before a first time, a plurality of sensor values and identifying, based on the plurality of sensor values, a target vehicle in a blind zone of a host vehicle. The method also includes determining, at the first time, that the host vehicle is initiating a steering maneuver and identifying a plurality of time segments between the first time and a second time. The method also includes updating the plurality of sensor values and determining a heading angle of the target vehicle relative to the host vehicle. The method also includes estimating a position of the target vehicle at each time segment of the plurality of time segments and estimating, using each position of the target vehicle at each corresponding time segment of the plurality of time segments, a position of the target vehicle at the second time.


