Autonomous Vehicle Handover Control Under Teleoperation Delay
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Solution Overview
Problem
Autonomous vehicles require human interaction for dynamic driving tasks, especially during handovers between automated driving systems and remote operators, which can be challenging due to communication delays and varying environmental conditions.
Innovation Solution
A vehicle operation system that implements a multi-stage teleoperation process based on sensor information and automation levels, allowing for real-time control and handover management between autonomous and remote operator control, using thresholds for decision-making and feature implementation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If teleoperation is implemented for autonomous vehicles, then human interaction and control are enabled during handovers, but communication delays and technological challenges arise
Solution Approach 1:
The system performs preliminary actions by proactively monitoring environment data and identifying handover triggers before actual handover is needed. The automated driving system continuously assesses whether conditions warrant human intervention and prepares for handover by detecting triggers such as unsafe environments or system limitations, enabling smoother transitions without waiting for communication delays to manifest
Solution Approach 2:
The system introduces an intermediary monitoring layer that acts as a mediator between the automated driving system and remote human operators. This intermediary continuously evaluates environment data and automatically identifies when handover triggers are met, serving as an intelligent buffer that reduces the need for constant real-time communication and mitigates the impact of communication delays
2Reliability
If multi-stage teleoperation process is implemented, then vehicle safety is maintained through real-time interaction, but system complexity increases
Solution Approach 1:
The teleoperation system is segmented into distinct automated stages: environment monitoring, trigger identification, handover initiation, and active human control. Each stage operates with specific functions and decision criteria, breaking down the complex safety management into manageable segments that can be executed systematically without requiring entire system redesign
Solution Approach 2:
The system implements dynamic control by allowing the level of automation and human involvement to change based on real-time conditions. The automated driving system operates independently when safe, dynamically transitions to teleoperation when triggers are identified, and allows flexible handover between stages based on environment data and system state, making the complexity adaptive rather than static
3Productivity
If autonomous operation is used, then productivity is improved, but human interaction is reduced which may compromise safety during handovers
Solution Approach 1:
The system implements continuous feedback loops where environment data is constantly monitored and fed back to the automated driving system. This feedback mechanism enables the system to assess whether continued autonomous operation is safe or if handover to human operators is warranted, maintaining productivity through automation while ensuring safety through ongoing environmental assessment and automatic trigger detection
Data Source
AI summary
Systems and methods for operating a vehicle by switching between an autonomous control system within the vehicle and a remote operator are described herein. For the handover between the autonomous control system and the remote operator, the system can process current maneuvering parameters of the vehicle to at least select a teleoperation control type. The system can also generate a concurrent feature profile including a set of automated features that are configured to be implemented during teleoperation of the vehicle. The system can implement the handover of vehicle control according to the teleoperation control type while the vehicle autonomously or semi-autonomously operates according to the concurrent feature profile.