Lane Keeping Assistance Using Preceding Vehicle Heading Angle
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Solution Overview
Problem
Lane keeping assistance systems fail to reliably recognize lanes on congested roads, especially when preceding vehicles block the view of lane markings, leading to potential misrecognition or non-recognition of lanes.
Innovation Solution
A system that uses a camera to detect lane markings, a radar to determine the position of preceding vehicles, and a controller to create a lane model by applying a preceding vehicle heading angle to the lane heading angle when the vehicle is traveling at low speeds and close to the preceding vehicle, ensuring reliable lane recognition even in congested conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the lane keeping assistance system uses camera-based lane marking detection, then it can recognize lanes under normal conditions, but it fails to reliably recognize lanes when preceding vehicles block the view on congested roads
Solution Approach 1:
The patent introduces an intermediary inference mechanism that uses detectable parameters (vehicle position, lane width, heading angle) as mediators to estimate lane information when direct observation is blocked. The system calculates lane parameters based on the preceding vehicle's position and orientation, using these as intermediary data points to reconstruct lane geometry without direct camera contact with lane markings.
Solution Approach 2:
The patent replaces the mechanical/optical detection system (camera directly viewing lane markings) with a computational inference system. Instead of relying on direct optical detection of lane markings, the system substitutes camera-based geometric inference using detected vehicle parameters, mathematical models, and calculation algorithms to derive lane information indirectly.
2Measurement precision
If the system relies solely on camera detection of lane markings, then the device complexity remains low, but the measurement precision deteriorates when lane markings are obscured
Solution Approach 1:
The patent makes the detection system universal by enabling it to function through multiple pathways: direct lane marking detection when visible, and indirect inference through vehicle parameter analysis when blocked. The same system architecture handles both normal and congested conditions, making the lane recognition capability multi-functional and adaptable to different environmental conditions without requiring separate systems.
Solution Approach 2:
The patent changes the detected parameters from direct lane marking coordinates to vehicle-centric parameters (position, lane width, heading angle). By transforming the detection task from identifying static lane markings to measuring dynamic vehicle-relative parameters, the system maintains measurement precision under obstruction while using standard sensor capabilities.
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 reliable lane recognition on congested roads and when lane markings are obstructed by preceding vehicles, reducing the risk of accidental lane deviation.
Implementation Method 1
a camera that obtains an image of the road; an image analyzing unit that detects lane markings by analyzing the image
Implementation Method 2
a radar that detects the position of the preceding vehicle
Data Source
AI summary
Disclosed is a system that creates a lane model using a lane offset value and a lane heading angle and assists a vehicle in keeping its lane by using the lane model. More specifically, the system may include: a camera that obtains an image of the road; an image analyzing unit that detects lane markings by analyzing the image and calculates and stores the lane offset value from the detected lane markings; a radar that detects the position of the preceding vehicle; a preceding vehicle analyzing unit that calculates a preceding vehicle heading angle between the vehicle and the preceding vehicle; and a controller that, if the lane markings are blocked, applies the preceding vehicle heading angle to the lane heading angle to thereby create the lane model.