Adaptive Driving System for Overtaking Comfort
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Autonomous or semi-autonomous vehicle control systems often choose a straight path that may not align with human drivers' comfort during overtaking conditions, such as passing other vehicles, leading to uncomfortable experiences due to fixed lateral spacing and speed.
Innovation Solution
A vehicle system that learns a driver's preferred lateral spacing and speed relative to adjacent vehicles by using a control module, sensors, and a display device to determine planned and actual overtaking policies, allowing for adaptive control based on driver input and preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the vehicle control system chooses a straight path with fixed lateral spacing, then the vehicle maintains stable and predictable autonomous control, but the driver experience becomes uncomfortable during overtaking conditions
Solution Approach 1:
The system dynamically adjusts lateral spacing and path deviation based on detected driving conditions and learned driver preferences. Instead of maintaining fixed lateral spacing, the vehicle adaptively modifies its position within the lane during overtaking maneuvers, transitioning from a static control approach to a dynamic one that responds to real-time contextual factors.
Solution Approach 2:
The system incorporates feedback loops where sensor data about adjacent vehicles and road conditions is continuously processed, and the control adjustments are made based on this feedback. The learned driver preferences are integrated into the feedback mechanism, allowing the system to refine its overtaking behavior based on observed driver responses to previous maneuvers.
2Adaptability or versatility
If the vehicle uses a fixed straight path, then the control algorithm is simple and easy to implement, but it cannot adapt to individual driver preferences and comfort levels
Solution Approach 1:
The system performs preliminary learning of driver preferences during normal operation before actual overtaking maneuvers. By continuously monitoring and learning from driver behavior patterns in various driving conditions, the system prepares adaptive parameters in advance, so that when overtaking is needed, the vehicle can immediately apply personalized control strategies without complex real-time decision-making.
Solution Approach 2:
The system changes control parameters such as lateral spacing, path deviation, and acceleration profiles based on learned driver preferences. Instead of using a single fixed control algorithm, the system modifies key parameters dynamically according to the specific driver's comfort levels and overtaking preferences, allowing adaptability through parameter variation rather than algorithmic complexity.
3Ease of operation
If the vehicle maintains equidistant positioning from adjacent vehicles, then the control system is straightforward, but the driver finds the path uncomfortable during passing conditions
Solution Approach 1:
The system applies different lateral spacing strategies for different local conditions and different phases of the overtaking maneuver. Instead of maintaining uniform equidistant positioning throughout, the vehicle adjusts lateral spacing locally based on the specific situation - closer to the center line when safe and comfortable, and maintaining greater distance when safety concerns arise, creating spatially varying control behavior.
Solution Approach 2:
The system dynamically adjusts lateral spacing during the overtaking maneuver rather than maintaining a fixed equidistant position. The lateral spacing evolves through different phases of the pass, transitioning from normal lane positioning to overtaking positioning and back, with continuous monitoring of safety margins to ensure reliable operation throughout the dynamic process.
Data Source
AI summary
A vehicle system for a vehicle can include sensors and a controller. The sensors can detect a position and speed of the vehicle and a position and speed of an object adjacent to the vehicle's lane. The controller can determine an operational state based on input from the sensors. The controller can operate the vehicle in an autonomous mode, wherein the controller controls the speed of the vehicle and a spacing between the vehicle and the object. The controller can switch from the autonomous mode to a learning mode in response to a driver taking control of the vehicle's speed or steering. In the learning mode, the controller can learn a preferred spacing between the vehicle and the object and a preferred speed relative to the object. The controller can control the vehicle in the autonomous mode based on the preferred spacing and speed during similar operational states.