Vehicle Lane Deviation Prediction Using Margin Time on Curves
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Solution Overview
Problem
Existing vehicle control systems face delays and inaccuracies in determining lane deviation when a vehicle is traveling on a curve due to reliance on lateral deviation, which can lead to delayed control or notification.
Innovation Solution
A vehicle control system that calculates a predicted route based on the vehicle's traveling state, determines intersection points with road markings, and sets a threshold for margin time to accurately assess the likelihood of lane deviation, especially during turning movements, using a turning curve as the reference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If lateral deviation is used to determine lane deviation, then the system is simple to implement, but delays occur in control or notification when a vehicle is traveling on a curve
Solution Approach 1:
The patent changes the determination parameter from lateral deviation to margin time (time until the vehicle reaches the marking line). This parameter change allows the system to account for vehicle dynamics during turning movements, eliminating delays in control or notification while maintaining reasonable system complexity.
2Device complexity
If lateral deviation is used to determine lane deviation, then the calculation is simple, but accuracy decreases when a vehicle is traveling on a curve
Solution Approach 1:
The patent changes the determination parameter from lateral deviation to margin time, which accurately reflects the time available before the vehicle reaches the marking line. This parameter change significantly improves measurement precision during curve travel, as it directly measures the critical time factor rather than a spatial deviation that may be misleading on curves.
3Measurement precision
If margin time calculation is implemented, then deviation determination accuracy is improved, but processing load increases
Solution Approach 1:
The patent calculates the predicted route in advance using the turning curve based on current traveling state. This preliminary calculation of the predicted route and intersection points enables efficient margin time computation without excessive processing load, as the complex geometric calculations are performed once rather than continuously.
Data Source
AI summary
A vehicle control device includes a recognition part configured to recognize marking lines of a road on which a host vehicle is traveling, a prediction part configured to calculate a predicted route of the host vehicle on the basis of a traveling state of the host vehicle, an intersection determining part configured to determine whether each predetermined sections of the marking lines intersect with the predicted route, and a determining part configured to calculate a margin time until the host vehicle reaches an intersection point between the predicted route and the marking line when it is determined that the predicted route will intersect with the marking line of the predetermined section, and configured to determine that the host vehicle is highly likely to deviate from the marking line when the margin time is equal to or smaller than a threshold.