Tele-Operated Driving Event Prediction for Reliable Session Triggering
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Solution Overview
Problem
Current technologies lack effective solutions for triggering and supporting tele-operated driving (ToD) services, particularly in establishing communication sessions and predicting the need for ToD events.
Innovation Solution
The proposed method involves a server-based system that receives requests for ToD support, processes them to identify suitable servers, and establishes communication sessions. It also includes prediction algorithms to anticipate ToD events based on vehicle, map, traffic, and QoS information, allowing for adaptation of vehicle behavior and selection of remote drivers and network quality of service.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If prediction algorithms are implemented to anticipate ToD events, then the reliability of ToD operations is improved, but the device complexity increases
Solution Approach 1:
The system performs prediction of ToD events in advance using prediction algorithms that analyze vehicle, map, traffic, and QoS information before actual ToD operations occur. This preliminary action allows the system to prepare and adapt to future ToD events, improving reliability by anticipating needs before they arise.
Solution Approach 2:
A server-based system acts as an intermediary between vehicles and remote drivers, centralizing the complexity of prediction algorithms, communication session management, and resource optimization in a dedicated server infrastructure rather than distributing it across multiple devices.
2Ease of operation
If communication sessions are established for ToD events, then the ease of operation is improved, but the loss of time in establishing connections increases
Solution Approach 1:
The system establishes communication sessions and prepares network resources in advance based on predicted ToD events. By anticipating future ToD operations through prediction algorithms, the system can pre-configured communication channels, reducing the time required to establish connections when actual ToD events occur.
3Productivity
If network resources are optimized for ToD operations, then the productivity is improved, but the device complexity increases
Solution Approach 1:
The server-based system serves as an intermediary that centralizes network resource management and optimization functions. It handles QoS parameter adjustment, bandwidth allocation, and resource coordination for multiple vehicles and remote drivers, improving overall productivity while containing complexity in a dedicated server infrastructure.
Solution Approach 2:
The system dynamically adjusts network parameters such as QoS settings, bandwidth allocation, and communication priorities based on predicted ToD events and actual operational needs. This parameter optimization improves productivity by ensuring adequate network resources are available when needed without requiring permanent over-provisioning.
Data Source
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AI summary
A method is performed by a first server communicatively connected to a network for supporting tele-operated driving of a vehicle. The method includes receiving a request from a tele-operated driving application client by the client device in the vehicle for teleoperated driving support. The client processes the request and sends a trigger request for teleoperated driving to the first server. This request includes a trigger and information for supporting a tele-operated driving event. The first server processes the request to identify a second server for providing support for the Tele-operated driving event, wherein the processing is based on parameters of the network for providing tele-operated driving support. Finally the first server will set-up a tele-operated driving session between the second server and the application client. The first server may also predict whether a tele-operated driving event is likely in a future time period based on prediction information obtained from one or more of the vehicle, the second server, a network server, and a third party application server.