Remote Operator Handover for High-Risk Autonomous Vehicle Segments
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Solution Overview
Problem
Autonomous vehicles face challenges in navigating through high-risk scenarios where they may struggle to detect and respond to emergency situations or disengage due to failures, leading to potential collisions or operational inefficiencies.
Innovation Solution
A method that involves accessing historical data to identify high-risk road segments and locations where manual control is frequently triggered, associating these locations with remote operator triggers on navigation maps, and automatically requesting assistance from remote operators when approaching these areas, allowing for real-time sensor data transmission and manual control to ensure safe navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If autonomous vehicles operate fully autonomously without remote operator intervention, then productivity and operating efficiency are improved, but reliability deteriorates due to inability to handle high-risk scenarios and emergency situations
Solution Approach 1:
The system performs preliminary identification of high-risk road segments by analyzing historical driving records and accident data before autonomous vehicles encounter them. Remote operator triggers are pre-associated with these locations, so when vehicles approach these segments, operators are already prepared to intervene, thus maintaining both efficiency and safety.
Solution Approach 2:
A remote operator system acts as an intermediary between fully autonomous operation and manual control. The system provides on-demand human intervention for high-risk scenarios while maintaining autonomous operation for normal conditions, resolving the contradiction between automation efficiency and human judgment reliability.
2Reliability
If remote operator assistance is continuously available for all driving scenarios, then reliability is improved, but device complexity and operational overhead increase
Solution Approach 1:
Remote operator triggers are selectively placed only at specific high-risk locations identified through historical data analysis, rather than being uniformly distributed throughout all driving environments. This localized approach ensures reliability where needed while minimizing system complexity in low-risk areas.
Solution Approach 2:
The system implements partial remote operator intervention only for identified high-risk scenarios rather than continuous or excessive monitoring. This selective approach provides sufficient safety coverage for critical situations while avoiding the complexity and overhead of constant human supervision.
3Reliability
If the system preemptively requests remote operator assistance at identified high-risk locations, then reliability is improved, but loss of time occurs during control transitions
Solution Approach 1:
The system requests remote operator assistance in advance before autonomous vehicles actually encounter high-risk scenarios. By preemptively engaging operators at identified trigger locations, the system allows time for smooth control transitions rather than reacting abruptly when hazards are detected, thus reducing time loss while maintaining safety.
Data Source
AI summary
Control of a mobile device is transferred to and from an operator. In one aspect, a specification for triggering manual control of the mobile device is accessed. A location is identified within a geographic region that exhibits characteristics defined by the specification. The location is represented in a navigation map and is associated with an operator trigger. As the mobile device approaches the location, a request for manual control is provided to the operator based on the operator trigger, and manual control is initiated.