Geofence-Based Drive Mode Switch for Semi-Autonomous Vehicles
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Solution Overview
Problem
Current semi-autonomous vehicle technologies lack effective solutions for transitioning from autonomous driving mode to manual driving in areas where autonomous driving is discouraged or prohibited, such as school zones, residential neighborhoods, and parking lots, due to safety concerns related to pedestrian interactions and unpredictable environments.
Innovation Solution
The implementation of a system that utilizes geofences to define areas where autonomous driving is prohibited, incorporating a notification system to alert drivers to assume control, and performing minimal risk maneuvers if the driver does not respond, with the ability to reroute around geofences if necessary, ensuring safe transitions between autonomous and manual driving modes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If autonomous driving mode is used to reach destination efficiently, then productivity is improved, but safety deteriorates in areas with high vehicle-pedestrian interaction
Solution Approach 1:
The patent divides the driving environment into geofenced zones with different autonomous driving permissions. By segmenting the operational space into restricted and permissive areas, the system can apply autonomous driving only where safe while requiring manual control in high-risk zones, thus resolving the contradiction between productivity and safety.
Solution Approach 2:
The notification system acts as an intermediary between the autonomous driving system and the driver. It alerts the driver when approaching restricted zones, providing a transition mechanism that ensures safety handover while maintaining overall trip efficiency, thereby balancing productivity and safety requirements.
2Extent of automation
If autonomous driving mode is used to maximize automation, then extent of automation is improved, but safety deteriorates in unpredictable environments
Solution Approach 1:
The patent implements location-specific automation quality by allowing full autonomous driving in permissive zones while requiring manual control in restricted zones. This local differentiation of automation extent based on environmental characteristics resolves the contradiction between maximizing automation and ensuring safety in unpredictable areas.
Solution Approach 2:
The system performs preliminary identification of restricted zones using geofencing data before the vehicle enters them. By preparing for the transition to manual mode in advance through notifications, the system ensures safety handover while maintaining high automation extent during the majority of the journey in safe zones.
3Reliability
If geofencing restrictions are implemented to improve safety, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent leverages existing universal technologies (GPS positioning, map data systems, notification interfaces) to implement geofencing functionality. By reusing established multi-functional components rather than creating dedicated new systems, the patent improves safety through geofencing while minimizing the increase in device complexity.
Data Source
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AI summary
A system for transitioning from a semi-autonomous driving mode to a manual driving mode comprises a navigation system to determine a route to a destination, a vehicle head unit to receive data that comprises information related to a geographic zone in which autonomous driving is discouraged or prohibited along the determined route to the destination, a processor to process the received data to determine if the semi-autonomous driving vehicle in autonomous mode is approaching a geographic zone in which autonomous driving is discouraged or prohibited. A notification to the driver of the semi-autonomous driving vehicle is issued to request the driver to manually drive in response to a determination that the semi-autonomous driving vehicle is approaching the geographic zone in which autonomous driving is discouraged or prohibited.