Remote Driving Data Split for Low-Bandwidth Decision Control
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Solution Overview
Problem
Existing remote driving technologies face challenges in optimizing network quality, which affects the safety and efficiency of remote driving operations, especially in environments requiring high-bandwidth and low-latency communication.
Innovation Solution
A method and apparatus for remote driving control that involves obtaining vehicle status data and environmental data, determining data for making driving decisions and constructing a simulated environment, and transmitting these data to respective servers for processing. The method includes receiving vehicle control instructions from the remote driving server and transmitting them to the vehicle, utilizing driving assistance information generated from the simulated environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all vehicle status data and environmental data are transmitted to the remote driving server for processing, then the driving decision accuracy is improved, but the network bandwidth consumption increases and latency increases
Solution Approach 1:
The patent segments the data processing tasks by dividing data into two categories: first data (vehicle status data) transmitted to the remote driving server for driving decisions, and second data (environmental data) transmitted to the target server for simulated environment construction. This segmentation allows specialized processing at different servers, improving overall decision accuracy while optimizing network bandwidth usage by sending only necessary data to each server.
Solution Approach 2:
The patent introduces a target server as an intermediary between the vehicle and the remote driving server. This target server constructs a simulated environment from environmental data and generates driving assistance information, which is then transmitted to the remote driving server. This intermediary approach reduces the direct data transmission burden on the network while maintaining comprehensive decision-making capabilities.
2Measurement precision
If a target server is introduced to construct simulated environment, then the driving assistance information quality is improved, but the system complexity increases
Solution Approach 1:
The system segments functionality into two specialized servers: the target server handles simulated environment construction and generates driving assistance information, while the remote driving server handles driving decision-making. This functional segmentation improves the quality of driving assistance information by dedicating specific resources to environment simulation, while the modular architecture manages system complexity through clear separation of concerns.
Solution Approach 2:
The target server creates a simulated environment that copies or replicates the real-world driving conditions based on transmitted environmental data. This virtual copy allows for comprehensive analysis and generation of driving assistance information without requiring direct access to all physical sensors, thereby improving information quality while managing system complexity through virtualization.
Data Source
AI summary
A remote driving control method includes: obtaining vehicle status data of a vehicle and environmental data of a road condition of the vehicle; determining first data for making driving decisions and second data for constructing a simulated environment corresponding to the road condition, based on the vehicle status data and the environmental data; transmitting the first data to a remote driving server; transmitting the second data to a target server, the target server and the remote driving server being connected via a network; receiving a first vehicle control instruction from the remote driving server; and transmitting the first vehicle control instruction to the vehicle, wherein the first vehicle control instruction is generated based on the first data and driving assistance information transmitted from the target server, and wherein the driving assistance information is generated based on the constructed simulated environment.