Adaptive Vehicle Control System Operator Alertness
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Solution Overview
Problem
Existing vehicle control systems that automatically manage movement to reduce fuel consumption and emissions can lead to decreased operator alertness and skill, with current alertness maintenance methods being intrusive and ineffective in preventing skill degradation.
Innovation Solution
A system that determines permissible regions for automatic or manual control based on route parameters and operator alertness, using an alertness detection system to monitor operator conditions and switch control modes accordingly, ensuring operator alertness and skill without excessive fuel consumption or emissions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If automatic control is used to reduce fuel consumption and emissions, then energy efficiency is improved, but operator alertness and skill deteriorate
Solution Approach 1:
The system dynamically switches between automatic and manual control modes based on real-time operator alertness detection. When the operator is detected to be alert, manual control is permitted to maintain skill; when drowsiness is detected, automatic control engages to ensure safety. This dynamic adaptation resolves the contradiction by allowing both automatic control for efficiency and manual control for skill maintenance.
Solution Approach 2:
The system implements continuous feedback through operator monitoring (e.g., eye-tracking, response time measurement) to detect alertness levels. This feedback loop enables the system to adjust control mode accordingly, maintaining operator alertness while utilizing automatic control for fuel efficiency when appropriate.
2Reliability
If audio or visual prompts are used to maintain operator alertness, then operator alertness is improved, but ease of operation deteriorates due to intrusiveness and distraction
Solution Approach 1:
The system uses passive monitoring methods (e.g., eye-tracking cameras, steering wheel sensor analysis) that automatically detect operator alertness without requiring active operator response. This eliminates the need for intrusive prompts while still maintaining alertness through automatic control engagement when needed.
Solution Approach 2:
The system replaces mechanical alertness maintenance methods (audio/visual prompts requiring operator response) with electronic sensing and automated control systems that passively monitor and automatically adjust control modes based on detected operator state.
3Reliability
If manual control is used to maintain operator skill and alertness, then operator alertness is improved, but energy efficiency deteriorates due to increased fuel consumption
Solution Approach 1:
The system dynamically adjusts control mode based on operator state, permitting manual control when operators are alert to maintain skill, and switching to automatic control when drowsiness is detected to ensure safety. This resolves the contradiction by allowing manual control for skill maintenance during alert periods while utilizing automatic control for energy efficiency during non-critical periods.
Solution Approach 2:
The system changes the operational parameter of control mode (manual vs. automatic) based on detected operator alertness levels, enabling optimal balance between skill maintenance and energy efficiency at different times during operation.
4Use of energy by moving object
If automatic control is used for extended periods, then fuel consumption is reduced, but operator skill deteriorates
Solution Approach 1:
The system implements periodic switching between automatic and manual control modes based on monitored operator alertness. This periodic engagement of manual control maintains operator skill while allowing automatic control to dominate during periods when manual intervention is not needed, thus reducing overall fuel consumption.
Solution Approach 2:
Continuous feedback from operator monitoring enables the system to detect when manual control should be permitted to maintain skill, balancing skill development with fuel efficiency over extended operational periods.
Data Source
AI summary
A vehicle system having processors configured to determine permissible regions of a trip where the vehicle system is permitted for automatic control. The permissible regions of the trip are determined based on one or more of parameters of a route, a trend of operating parameters of the vehicle system, or a trip plan that designates one or more operational settings of the vehicle system at different locations, different times, or different distances along a route. The processors also are configured to control transition of the vehicle system between manual control and the automatic control in the permissible regions by alerting an operator of the vehicle system, automatically switching between the manual control and the automatic control, or modifying conditions on which the transition occur.