Parallel Remote Driving Control for Driverless Vehicle Takeover
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Solution Overview
Problem
Current intelligent network vehicle driving and control methods require human drivers for monitoring and takeover, which hinders the advancement and popularization of intelligent network technology due to high human resource demands and difficulties in smooth mode transitions during emergencies.
Innovation Solution
A parallel remote control driving system that includes an intelligent network vehicle control device with a communication module and mode switching module, allowing for automatic or remote control modes, and a parallel driving control device with a virtual system module for data communication and abnormality detection, enabling remote control and centralized management of multiple vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a human driver sits in the vehicle for monitoring and takeover, then vehicle safety can be supervised and emergency takeover can be performed, but manpower costs and training requirements increase significantly
Solution Approach 1:
The vehicle control system performs self-monitoring and self-control functions through automated driving algorithms and sensors, eliminating the need for human drivers to continuously supervise and manually operate the vehicle. The system serves itself by detecting environmental conditions, planning trajectories, and controlling vehicle operations autonomously.
Solution Approach 2:
The patent replaces the mechanical system of human driver operation with an automated electronic control system. The vehicle control system uses sensors, processors, and actuators to substitute human monitoring and control functions, transforming manual mechanical operations into automated electronic control processes.
2Productivity
If remote control driving mode is implemented, then manpower costs are reduced and management efficiency is improved, but mode transition smoothness during emergencies may be compromised
Solution Approach 1:
The mode switching module dynamically adjusts between automatic driving mode and remote control driving mode based on real-time vehicle conditions and operational needs. The system can smoothly transition between modes during normal operation and during emergencies, optimizing the balance between automation and remote supervision based on situational requirements.
Solution Approach 2:
The system changes operational parameters by switching between different driving modes. The mode switching module alters the control parameter state from fully automatic to remote-controlled based on detected conditions, enabling flexible adaptation to different operational scenarios while maintaining operational smoothness through controlled parameter transitions.
3Productivity
If centralized control is implemented for managing multiple vehicles, then management efficiency is improved and costs are reduced, but system complexity increases
Solution Approach 1:
The parallel driving control device performs multiple functions including monitoring multiple vehicles, receiving abnormality information, generating takeover requests, and coordinating remote control operations. This multi-functional centralized controller manages diverse vehicle operations through a single unified system, improving efficiency while containing complexity through functional integration.
Solution Approach 2:
The parallel driving control device acts as an intermediary between multiple vehicle control systems and remote operators. It receives data from vehicles, processes abnormality information, generates appropriate takeover requests, and coordinates remote control actions, serving as a mediating layer that simplifies the overall system architecture while enabling efficient centralized management.
Data Source
AI summary
A parallel remote control driving system for an intelligent network vehicle, comprising an intelligent network vehicle control device, a parallel driving control and a remote control driving device. The remote control driving device generates, according to a remote control driving request signal from the parallel driving control device, a remote control driving instruction signal, and generates, according to user operations, a driving mode signal and a vehicle control signal and transmits the vehicle control signal to the intelligent network vehicle control device through the parallel driving control device, for remote control of the intelligent network vehicle. With the parallel remote control driving system, the human driver is no longer necessary when the intelligent network vehicle is on the road. Therefore, the manpower cost including training cost, the technical requirement, and the safety cost of the human driver is significantly reduced, thus facilitating the promotion of intelligent network vehicle.