Vehicle Device Control Profiles for Context-Aware Driving Experience
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Solution Overview
Problem
Existing vehicle control systems fail to dynamically adapt to the vehicle's state and environment, leading to monotonous driving experiences and potential loss of driver concentration during lengthy journeys.
Innovation Solution
A method for controlling vehicle devices based on real-time data analysis, including vehicle and environmental conditions, to dynamically update control profiles and create immersive multisensory experiences, using a computer to manage device actuation and synchronize instructions across multiple devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If predetermined control profiles are used for driving modes, then the driving experience can be adapted to different journey types, but the same set of commands is always executed making the use of these modes tedious in the long term
Solution Approach 1:
The patent transforms static predetermined control profiles into dynamic adaptive control profiles that automatically adjust based on real-time vehicle state and environmental data. The control profiles evolve during operation, changing parameters such as lighting intensity, audio characteristics, and climate control settings dynamically rather than following fixed predetermined sequences, thereby eliminating monotony while maintaining adaptability.
Solution Approach 2:
The system continuously receives feedback from sensors monitoring vehicle state (speed, acceleration, steering angle) and environmental conditions (ambient light, temperature, noise levels). This feedback loop enables the control system to automatically adjust the multisensory output parameters in real-time, creating a responsive adaptive experience that changes with driving conditions rather than following rigid predetermined profiles.
2Adaptability or versatility
If lighting in the passenger compartment is adapted on the basis of ambient brightness and external objects, then the driving experience for occupants is improved, but this approach is insufficient in situations of imminent danger where stronger warnings are needed
Solution Approach 1:
The system continuously monitors driving conditions through sensor feedback and can detect dangerous situations such as sudden braking, sharp steering inputs, or collision warnings. When such conditions are detected, the control system automatically adjusts the multisensory output parameters to provide stronger warnings, overriding the normal adaptive lighting behavior to ensure driver safety.
Solution Approach 2:
The patent employs multiple sensory parameters including lighting intensity, color temperature, audio volume and frequency, and climate control settings. In dangerous situations, the system can dramatically change these parameters - for example, increasing lighting intensity, adding alert sounds, or adjusting climate control - to create a noticeable warning effect that surpasses the limitations of lighting adaptation alone.
3Adaptability or versatility
If multiple sensors and devices are integrated to provide context-aware control, then driving engagement is enhanced through dynamic adaptation, but the system complexity increases
Solution Approach 1:
The patent integrates multiple existing vehicle sensors (accelerometers, gyroscopes, light sensors, microphones) and control devices (lighting systems, audio systems, climate control) into a unified multisensory control system. Rather than adding dedicated sensors for each function, the system repurposes existing components to serve multiple functions - for example, using the same sensors for both driver assistance features and adaptive multisensory control, thereby reducing overall system complexity.
Solution Approach 2:
The control system merges the functionality of multiple independent control systems (lighting control, audio control, climate control) into a single integrated multisensory control architecture. This unified system manages all sensory output parameters through a common control algorithm that processes vehicle state and environmental data, simplifying the control structure compared to managing each system separately while maintaining full adaptability across all devices.
Data Source
AI summary
A method for controlling a device of a motor vehicle includes, in a first time step, receiving data characterizing a state of the vehicle and the environment, determining an initial vector on the basis of the data, selecting a first control profile on the basis of the initial vector, transmitting the first profile so as to control the device, and then, in a second time step, updating the data, determining an updated vector, selecting a second control profile on the basis of the updated vector, and if the second profile is different from the first profile, transmitting the second profile so as to update the control of the device of the vehicle.