Mixed-mode driving system for vehicle mode transitions
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Solution Overview
Problem
Current vehicle systems lack the ability to efficiently transition between autonomous and manual driving modes based on real-time information about vehicle occupants, their preferences, and environmental conditions, potentially compromising safety and efficiency.
Innovation Solution
A mixed-mode driving system that automatically adjusts the driving mode of a vehicle between autonomous, manual, paused, or disabled modes in response to updated information about occupants, their preferences, and environmental conditions, using sensors and data sources to determine the optimal mode for safety and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the vehicle operates in autonomous driving mode to maximize efficiency, then productivity is improved, but reliability deteriorates when occupants require manual control or emergency intervention
Solution Approach 1:
The system dynamically transitions between autonomous and manual driving modes based on real-time monitoring of occupant conditions, preferences, and environmental factors. The driving mode is not fixed but adapts continuously to changing conditions, allowing the vehicle to maximize autonomous operation for efficiency while ensuring manual control availability for safety-critical situations
Solution Approach 2:
The system continuously monitors multiple data sources including sensor information about occupant physical conditions, stored occupant preferences, and environmental data to determine the appropriate driving mode. This feedback loop ensures that the vehicle responds to changing conditions and maintains the optimal balance between autonomous efficiency and manual safety control
2Reliability
If the system continuously monitors occupant conditions and environmental factors to determine optimal driving mode, then reliability is improved, but device complexity increases
Solution Approach 1:
The mixed-mode driving system performs multiple functions through a unified architecture: it monitors occupant conditions, processes environmental data, retrieves stored preferences, determines optimal driving modes, and executes mode transitions. This multi-functional approach consolidates what could be separate complex systems into a single integrated solution, managing complexity while maintaining comprehensive safety monitoring
Solution Approach 2:
The system automatically determines and executes driving mode transitions based on its own monitoring of conditions and stored preferences, without requiring external intervention for each decision. The vehicle self-manages the complexity of mode selection by using its own sensors, stored data, and decision-making algorithms
3Adaptability or versatility
If the vehicle transitions between driving modes based on real-time information, then adaptability is improved, but loss of time occurs during mode switching
Solution Approach 1:
The system continuously monitors and evaluates conditions in advance, maintaining readiness to transition between modes. By keeping the system in a state of preparedness and pre-processing potential transitions, the actual mode switching can occur more quickly when needed, reducing the perceived transition time while maintaining high adaptability
Data Source
AI summary
Among other things, a vehicle having autonomous driving capabilities is operated in a mixed driving mode.