Teleoperation Intervention for Autonomous Vehicle Trajectory Recovery
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Solution Overview
Problem
Autonomous vehicles (AVs) face challenges in handling system faults, extreme weather conditions, and temporary detours, requiring remote assistance to prevent risks such as collisions or traffic jams, and existing systems lack effective methods for real-time intervention and trajectory adjustments.
Innovation Solution
A teleoperation system that interacts with AVs, allowing remote operators to intervene by analyzing vehicle status and environment signals, enabling fallback interventions such as changing driving modes, identifying safe locations, and generating new trajectories, using machine learning and pattern recognition to detect malfunctions or unknown objects, and prioritizing interventions based on decision trees and past data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If autonomous driving capabilities are implemented without remote intervention, then automation level is improved, but reliability deteriorates when system faults or extreme weather conditions occur
Solution Approach 1:
A teleoperation system acts as an intermediary between the autonomous vehicle and remote operators. When system faults or extreme weather conditions are detected, the teleoperation system enables remote operators to intervene and provide assistance, thereby maintaining reliability while preserving autonomous driving capabilities during normal operation
Solution Approach 2:
The system performs preliminary actions by detecting system faults and extreme weather conditions before they lead to failures. By proactively identifying adverse conditions and enabling remote intervention in advance, the system prevents collisions and traffic jams before they occur
2Reliability
If remote intervention is enabled for all situations, then reliability is improved, but device complexity increases
Solution Approach 1:
Remote intervention capabilities are applied locally and selectively only when system faults or extreme weather conditions are detected, rather than being continuously active. This selective application maintains reliability when needed while avoiding unnecessary complexity during normal autonomous operation
3Reliability
If real-time monitoring and intervention capabilities are implemented, then reliability is improved, but loss of time increases due to communication delays
Solution Approach 1:
The system continuously monitors vehicle status and environment in real-time, performing preliminary detection of system faults and extreme weather conditions before they escalate. This early detection enables faster response times by preparing for potential interventions in advance, reducing the actual response time when events occur
Data Source
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AI summary
Among other things, a determination is made that intervention in an operation of one or more autonomous driving capabilities of a vehicle is appropriate. Based on the determination, a person is enabled to provide information for an intervention. The intervention is caused in the operation of the one or more autonomous driving capabilities of the vehicle.