Adaptive Lane Biasing for Driver-Preferred Vehicle Positioning
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Solution Overview
Problem
Conventional lane keeping assistance systems position vehicles centrally within a lane, failing to account for individual driver preferences and comfort, which can lead to discomfort due to factors like proximity to other vehicles or road conditions.
Innovation Solution
A system that learns and adapts to a driver's lane biasing preferences by analyzing historical driving behaviors, physical characteristics, and environmental conditions to autonomously or semi-autonomously adjust the vehicle's position within a lane, allowing for personalized positioning based on learned habits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the vehicle is positioned centrally within the lane using conventional lane keeping assistance, then the lane keeping function is simple and reliable, but driver comfort deteriorates due to proximity to other vehicles or road conditions that do not account for individual driver preferences
Solution Approach 1:
The lane keeping system dynamically adjusts the vehicle's lateral position within the lane based on real-time sensor data and learned driver preferences. The system transitions from a static central positioning to a dynamic adaptive positioning that considers proximity to other vehicles, road conditions, and individual driver comfort preferences, resolving the contradiction between simplicity and comfort.
Solution Approach 2:
The system implements feedback loops where sensor data about surrounding vehicles and road conditions is continuously monitored, and driver responses to lane positioning are captured and used to refine future positioning decisions. This feedback mechanism enables the system to learn and adapt to driver preferences over time, improving comfort without requiring complex manual adjustments.
2Ease of operation
If the system autonomously adjusts vehicle position based on learned driver preferences, then driver comfort is improved, but the extent of automation increases system complexity
Solution Approach 1:
The lane keeping system performs self-learning by automatically capturing driver responses to different lane positions and using this information to adapt its positioning strategy. The system serves itself by continuously refining its understanding of driver preferences through observed behavior patterns, reducing the need for explicit programming while improving comfort through autonomous adaptation.
Solution Approach 2:
The system pre-learns driver preferences during periods when the driver is manually controlling the vehicle, building a profile of preferred lane positions before autonomous operation is needed. This preliminary learning phase allows the system to have automation-ready knowledge stored, enabling smooth transition to autonomous positioning without requiring complex real-time decision-making algorithms.
3Adaptability or versatility
If the system learns from historical driving behaviors and environmental conditions, then adaptability to driver preferences is improved, but the quantity of data processing and system complexity increases
Solution Approach 1:
The system focuses its data processing on locally relevant features such as lateral position preferences, proximity to adjacent vehicles, and specific road condition patterns rather than processing all possible driving data. By concentrating on the most impactful local factors that influence lane positioning, the system achieves high adaptability to driver preferences while keeping data processing complexity manageable.
Data Source
AI summary
Systems and methods are provided for lane biasing, e.g., positioning a vehicle within a current lane of travel. Lane biasing can be dependent on learned driver behaviors or other factors that may impact lane biasing, e.g., weather conditions, traffic conditions, and so on (which may also be learned). Lane biasing may result in a vehicle traveling, e.g., off the center-line of a current lane of travel, and is distinguished from conventional lane keep assist systems that merely position a vehicle in the center of a current lane of travel by default.