Driver Intervention Notifications for Assisted Automated Driving
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Solution Overview
Problem
Autonomous driving systems face challenges in effectively notifying vehicle operators of the need for driver intervention, leading to potential system disengagement and human-machine misalignment, especially in level 2 and level 3 autonomous vehicles.
Innovation Solution
A system and process that utilize a computer with a processor and memory programmed to generate notifications for driver intervention, providing information on finite driving options through visual, verbal, or haptic means, displayed in various notification regions within the vehicle, to assist operators in reconciling human-machine disagreements and minimizing system disengagement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the autonomous driving system provides comprehensive notifications to drivers about intervention requirements, then driver awareness and system reliability improve, but notification complexity and information processing burden increase
Solution Approach 1:
The notification system divides intervention information into discrete, manageable segments including situation description, available options, and selected action. This segmentation allows drivers to process information in structured steps rather than overwhelming them with undifferentiated complexity, thereby maintaining high reliability while managing notification complexity.
Solution Approach 2:
The system implements feedback loops where notifications are provided to drivers about system intentions and driver responses are acknowledged. This feedback mechanism enhances reliability by ensuring driver awareness and understanding, while the structured feedback format prevents information overload through clear, concise communication protocols.
2Ease of operation
If the system presents detailed driving options to the driver, then driver understanding and appropriate intervention improve, but information processing time and driver cognitive load increase
Solution Approach 1:
The system prepares and presents driving options to the driver in advance of when intervention is actually needed. By preliminarily displaying available actions and their consequences, drivers have time to process information without experiencing cognitive overload during critical moments, thus improving ease of operation while managing time loss through proactive information delivery.
Solution Approach 2:
The notification system provides sufficient but not excessive information - presenting the essential driving options needed for driver understanding without overwhelming detail. This partial action approach focuses on critical information only, balancing comprehensive understanding with efficient processing time by excluding redundant data while maintaining adequate driver awareness.
3Reliability
If the autonomous driving system requires driver intervention, then safety and control improve, but system disengagement and human-machine misalignment increase
Solution Approach 1:
The notification system acts as an intermediary between the autonomous driving system and the driver, translating system intentions into driver-friendly language and presenting intervention options in an accessible format. This intermediary role maintains safety by ensuring clear communication of risks and options, while reducing disengagement by making the automation system feel more transparent and controllable rather than abrupt or mysterious.
Solution Approach 2:
The system implements feedback mechanisms that acknowledge driver responses and confirm intervention execution. This feedback loop reduces human-machine misalignment by ensuring drivers understand their actions were received and processed correctly, thereby maintaining trust in the automation system while preserving safety through confirmed driver-system coordination.
Data Source
AI summary
A system comprises a computer including a processor and a memory. The memory includes instructions such that the processor is programmed to: execute an autonomous vehicle algorithm simulating vehicle operations determine whether a notification that provides information on how a driver intervention for actuation by system feature functions has been at least one of previously presently or confirmed and cause the notification to be generated. The notification includes information for responding to a finite number of driving options determined by the driver intervention for actuation by system.