Vehicle Window Control via Predictive Environmental Actuation
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Solution Overview
Problem
Vehicles face challenges in predicting and adapting to environmental conditions such as water, dust, and pollution while traveling, which can affect the interior climate and comfort, as existing systems lack effective methods to anticipate and respond to these conditions in real-time.
Innovation Solution
A method and system that utilize sensors and predictive algorithms to determine environmental conditions and object proximity to vehicle windows, allowing the vehicle computer to actuate windows to a closed position when necessary, based on threshold distances and data from HD maps and weather data, preventing unwanted entry of environmental elements into the cabin.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If windows are kept closed to protect against environmental conditions, then interior climate and comfort are maintained, but passengers cannot benefit from open windows when conditions are favorable
Solution Approach 1:
The system performs preliminary action by predicting adverse environmental conditions before the vehicle reaches them using HD map data and weather data. Windows are closed in advance of the adverse conditions, rather than in direct response to them. This allows the system to maintain reliable interior climate protection while still allowing windows to remain open during favorable conditions, as the closure is triggered by predicted rather than current conditions.
2Object-affected harmful factors
If windows are closed proactively to prevent water, dust, and pollution entry, then interior cleanliness is improved, but energy consumption increases due to reduced natural ventilation
Solution Approach 1:
The system closes windows in advance of predicted adverse conditions (water, dust, pollution) rather than waiting for contaminants to be detected. This preliminary closure prevents contaminant entry more effectively than reactive systems, while the system only closes windows when necessary based on predictions, allowing natural ventilation to continue during favorable conditions and thus minimizing energy consumption.
Solution Approach 2:
The system uses sensor data including occluding material detection on sensors as feedback to verify predicted conditions and adjust window operation accordingly. This feedback mechanism ensures windows are closed only when actual conditions match predictions, optimizing the balance between contaminant prevention and energy-efficient ventilation.
3Ease of operation
If window actuation is automated based on environmental predictions, then operational convenience is improved, but system complexity increases
Solution Approach 1:
The system uses a multi-functional architecture where the vehicle computer leverages existing data sources (HD map data, weather data, sensor data including occluding material detection) for multiple purposes. The same predictive algorithms and sensor inputs used for other vehicle functions are also used for window control decisions, reducing the need for dedicated complex window control hardware while providing automated convenience.
4Measurement precision
If sensors are used to detect environmental conditions, then prediction accuracy is improved, but sensor reliability decreases when occluding materials are present
Solution Approach 1:
The system performs preliminary prediction of environmental conditions using HD map data and weather data before the vehicle reaches locations with potential adverse conditions. This allows the system to anticipate issues before sensors might be affected by occluding materials such as water or dust, maintaining reliable operation by not depending solely on real-time sensor feedback in harsh conditions.
Solution Approach 2:
The system uses occluding material detection on sensors as feedback to monitor sensor reliability. When occluding materials are detected, the system adjusts its operation to account for reduced sensor reliability, cross-referencing with predicted conditions from HD map and weather data to maintain accurate environmental condition assessment.
Data Source
AI summary
A method includes predicting an environmental condition at a location to which a vehicle is travelling, the environmental condition including at least one of water, dust, and pollution, determining that an object within the vehicle is at a distance greater than a threshold distance from an unobstructed window of the vehicle, and then actuating the unobstructed window to a closed position based on the environmental condition and the object being at the distance from the window greater than the threshold distance.