Teleoperation Control Center Selection for Latency-Critical Driving
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Solution Overview
Problem
Existing teleoperated driving systems face challenges in optimizing the allocation of teleoperation control centers due to varying session characteristics, latency issues, and resource inefficiencies, which can lead to unsafe or inefficient vehicle maneuvers.
Innovation Solution
A teleoperation selection system that identifies computational parameters based on session characteristics, maneuver type, and control capabilities of available centers to match vehicles with suitable control centers, ensuring safe and efficient resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If teleoperation control centers are selected without matching control capabilities and latency requirements, then resource allocation is simplified, but safety and performance deteriorate
Solution Approach 1:
The system performs preliminary identification of control types (trajectory control vs. direct vehicle system control) and computational parameters (latency requirements, processing capabilities) before selecting a teleoperation control center. This advance preparation ensures that when a teleoperation request is made, the system can quickly match the request with an appropriate control center that has the required capabilities, thereby ensuring safety without adding significant complexity to the selection process.
Solution Approach 2:
The system changes parameters by identifying and categorizing different control types (trajectory control, direct vehicle system control) and their associated computational parameters (latency thresholds, processing requirements). By transforming the selection problem into a parameter-matching problem, the system can reliably select appropriate control centers while maintaining manageable system complexity through structured parameter comparison.
2Productivity
If teleoperation control centers are selected without matching control capabilities, then allocation speed is improved, but control precision deteriorates
Solution Approach 1:
The system identifies specific computational parameters including latency requirements and processing capabilities associated with different control types. By establishing clear parameter thresholds (e.g., maximum acceptable latency for direct vehicle system control vs. trajectory control), the system can quickly filter and match teleoperation requests with appropriate control centers, achieving both fast allocation and precise control matching.
Solution Approach 2:
The system replaces manual or heuristic-based control center selection with an automated parameter-matching mechanism. By using computational comparisons of control capabilities against session requirements, the system achieves rapid and precise allocation without relying on complex manual evaluation processes, thereby maintaining both speed and precision.
3Adaptability or versatility
If computational parameters are not identified based on session characteristics, then system complexity is reduced, but adaptability deteriorates
Solution Approach 1:
The system identifies computational parameters (latency requirements, processing capabilities) that change based on session characteristics and control types. By dynamically adjusting these parameters according to the specific teleoperation session requirements, the system achieves high adaptability without requiring a completely complex system architecture, as the parameter identification follows a structured approach based on control type classification.
Data Source
AI summary
Systems, methods, and other embodiments described herein relate to selecting a teleoperation control center for a requested teleoperation driving session based on characteristics of the requested teleoperated driving session and a type of control for the session. In one embodiment, a method includes identifying 1) a type of control for a requested teleoperated driving session and 2) a computational parameter for the requested teleoperated driving session based on a session characteristic for the requested teleoperated driving session and the type of control. The method also includes identifying control capabilities of different teleoperation control centers. The method also includes transmitting control of a requesting vehicle to a target teleoperation control center of the different teleoperation control centers based on 1) the computational parameter, 2) the type of control, and 3) the control capabilities of the different teleoperation control centers.