Vehicle Wind Estimation Control for Stability in Crosswinds
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Solution Overview
Problem
Autonomous vehicles face challenges in navigating windy conditions due to the difficulty in accurately estimating ambient ground relative wind speed, which can impact roll stability and off-tracking, especially for large vehicles like semi-trucks, as robotic systems struggle to replicate human driver adjustments based on mixed and nonlinear wind signals.
Innovation Solution
Implementing onboard wind sensors to provide real-time ambient ground relative wind speed measurements, which are combined with vehicle trajectory data to estimate the ambient wind speed relative to the ground, allowing vehicles to adjust behavior through predefined behavior threshold curves to mitigate wind impacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If onboard wind sensors are implemented to measure ambient ground relative wind speed, then vehicle stability and safety in windy conditions are improved, but device complexity and cost increase
Solution Approach 1:
The patent uses an intermediary computational model that processes data from existing sensors (anemometer, GPS, motion sensors) to estimate ambient ground relative wind speed. This intermediary layer translates raw sensor data into meaningful wind speed estimates without requiring direct complex wind measurement hardware, thereby improving reliability while minimizing additional device complexity.
Solution Approach 2:
The patent replaces direct mechanical wind measurement systems with a computational approach that uses data from existing vehicle sensors. Instead of installing complex dedicated wind measurement hardware, the system substitutes a software-based estimation model that processes signals from standard vehicle anemometers and motion sensors, reducing device complexity while maintaining stability improvements.
2Reliability
If real-time wind speed estimation and behavior adjustment systems are implemented, then navigation safety in windy conditions is improved, but computing resources and processing time are consumed
Solution Approach 1:
The patent applies partial action by implementing behavior adjustments only when estimated wind speeds exceed predefined thresholds. The system continuously monitors wind conditions but activates energy-consuming behavior modifications (such as route changes or speed adjustments) only when necessary, thereby improving navigation safety while minimizing unnecessary computing energy consumption during calm conditions.
3Reliability
If behavior adjustments are made based on ambient ground relative wind speed estimates, then the impact of windy conditions is minimized, but vehicle productivity and travel time may be reduced
Solution Approach 1:
The patent implements dynamic behavior adjustments that adapt to real-time wind conditions. The system continuously estimates ambient ground relative wind speed and adjusts vehicle behavior dynamically based on current conditions rather than applying static restrictions. This allows the vehicle to maintain optimal speed and route when wind conditions are favorable while only making adjustments when necessary, thereby improving stability without excessively compromising productivity.
Data Source
AI summary
Example embodiments relate to techniques for adjusting vehicle behavior based on ambient ground relative wind estimations. An onboard computing system may receive wind data from one or multiple wind sensors positioned onboard a vehicle. The wind data can indicate a direction and a speed of wind propagating in the vehicle's environment. The computing system can also receive navigation data that represents a direction and a speed of the vehicle and then estimate an ambient ground relative wind speed based on the navigation data and the wind data. The computing system can adjust the behavior of the vehicle based on the ambient ground relative wind speed. For instance, the computing system may compare the speed of the ambient ground relative wind to a predefined behavior threshold curve and adjust the behavior of the vehicle based on the comparison.