Remote Vehicle Control Using Predicted QoS Command Timing
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Solution Overview
Problem
Existing remote driving systems face challenges in maintaining communication link quality, leading to insufficient delivery of driving commands during fluctuations in Quality of Service (QoS), which can result in deadlock situations for vehicles unable to resolve obstacles autonomously.
Innovation Solution
Predicting the Quality of Service (pQoS) and adjusting the effective length and timing of driving commands to ensure they are received before QoS becomes insufficient, thereby guiding the vehicle through potentially problematic areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If driving commands are transmitted regularly with fixed effective length, then the system operation is simple, but the commands may not be received in time when QoS drops, leading to deadlock situations
Solution Approach 1:
The system performs preliminary actions by predicting future QoS conditions and adjusting the effective length of driving commands in advance. Before QoS degradation occurs, the command effective length is extended based on predicted QoS values, ensuring the vehicle receives sufficient guidance even when communication quality deteriorates. This proactive adjustment prevents deadlock situations without requiring complex real-time communication protocols.
2Reliability
If the effective length of driving commands is extended to cover QoS degradation periods, then command delivery reliability improves, but the device complexity increases due to QoS prediction and dynamic adjustment mechanisms
Solution Approach 1:
The system obtains predicted QoS values in advance and uses these predictions to proactively adjust the effective length of driving commands before actual QoS degradation occurs. This allows the system to prepare appropriate command lengths based on forecasted communication conditions, ensuring reliable delivery without requiring complex real-time adaptation mechanisms during command transmission.
Solution Approach 2:
The system dynamically changes the effective length parameter of driving commands based on predicted QoS conditions. By adjusting this key parameter according to forecasted communication quality, the system optimizes command delivery reliability while maintaining manageable complexity through a focused parameter adjustment approach rather than comprehensive system redesign.
3Reliability
If driving commands are provided with fixed timing intervals, then the communication protocol is simple, but commands may arrive too late to prevent deadlock situations during QoS fluctuations
Solution Approach 1:
The system performs preliminary adjustments to command timing and effective length based on predicted QoS conditions. By anticipating future communication quality degradation, the system extends command effective lengths and adjusts transmission timing in advance, ensuring commands remain valid and actionable even when QoS fluctuates. This proactive timing adjustment prevents late arrivals that would fail to prevent deadlock situations.
Data Source
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AI summary
Embodiments provide a computer program, an apparatus, and a method for a remote control center and for operating a vehicle from remote. The method comprises obtaining information on a pQoS of a communication link between the remote control center and the vehicle. Further, the method comprises providing at least one driving command to the vehicle via the communication link and adapting a range of the at least one driving command based on the information on the pQoS.