Virtual Lane Generation via Wheel Trajectory Analysis
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Solution Overview
Problem
Conventional lane departure prevention systems for autonomous vehicles fail when lane information is insufficient, leading to potential lane departure and vehicle misalignment due to blurred, zigzag, or unclear lanes, which limits their ability to maintain the driving lane.
Innovation Solution
A driving lane keeping control system that uses a tire pressure monitoring system (TPMS) to transmit wheel position information to a server, which calculates a moving trajectory and generates virtual lane information to prevent lane departure and correct the vehicle's position, leveraging GPS and detailed maps to optimize the vehicle's path.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional lane departure prevention systems (LDW, LKA, HAD) are used, then lane departure can be prevented when lane information is sufficient, but the system fails when lane information is insufficient (blurred, zigzag, or unclear lanes)
Solution Approach 1:
The patent introduces virtual lane information as an intermediary element that mediates between insufficient physical lane markings and the vehicle's lane keeping system. When camera and radar detection fails due to blurred or unclear lanes, the server generates virtual lane information based on wheel position data and detailed map information, providing a reliable reference for lane keeping control without requiring clear visual lane markings
Solution Approach 2:
The patent replaces the optical detection system (camera) and electromagnetic detection system (radar) with a positioning-based system using wheel position markers and GPS. Instead of relying on optical or electromagnetic waves to detect lane markings, the system uses mechanical wheel position data combined with digital map information to determine vehicle position and generate virtual lane guidance, substituting sensor-based detection with positioning-based determination
2Measurement precision
If camera and radar are used for lane detection, then lane information can be obtained when lanes are clear, but the vehicle cannot maintain proper alignment when lane information is insufficient
Solution Approach 1:
The system performs preliminary actions by continuously collecting and storing wheel position information from multiple vehicles, and pre-generating virtual lane information based on detailed map data before it is needed. When lane detection fails, the pre-collected positioning data and pre-generated virtual lane information are immediately available to maintain vehicle alignment, avoiding the need for real-time lane marking interpretation
3Adaptability or versatility
If virtual lane information is generated using wheel position markers and detailed maps, then lane keeping can be maintained under all conditions, but system complexity increases
Solution Approach 1:
The patent makes existing components serve multiple functions: wheel position markers originally designed for tire pressure monitoring now also serve as positioning references for lane keeping; the server originally used for map data now also generates virtual lane information; communication infrastructure originally for other purposes now transmits positioning and lane guidance data. This multi-functionality reduces the need for dedicated components while achieving universal lane keeping capability
Solution Approach 2:
The system uses the vehicle's own wheel position data and the publicly available detailed map information to self-generate virtual lane guidance without requiring additional sensors or external infrastructure. The server utilizes existing communication networks and open-source map data, making the system self-sufficient and reducing complexity by leveraging already-available resources
Data Source
AI summary
A driving lane keeping control system includes a number of vehicles and a server. Each vehicle is configured to transmit wheel position information to the server. The server is configured to receive the wheel position information from each vehicle, to match the wheel position information with a detailed map to generate a moving trajectory of each vehicle, to analyze the generated moving trajectory of each vehicle to select an optimum moving trajectory, to generate virtual lane information based on the selected optimum moving trajectory, and to transmit the generated virtual lane information to at least one of the vehicles to enable the at least one vehicle to correct a driving position based on the virtual lane information.