Vehicle Driving Mode Controller Using Multi-Source Data Comparison
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Solution Overview
Problem
Autonomous vehicles require a method to determine the driving state of a driver for maintaining driving stability and deciding when to intervene, as current systems do not adequately assess the driver's state for seamless transition between manual and autonomous driving.
Innovation Solution
An apparatus and method that utilize a communicator, sensor, and controller to receive and compare autonomous driving data from other vehicles and servers with manual driving data, calculating error values to determine whether to maintain manual driving or switch to autonomous driving based on predefined reference values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the autonomous vehicle system allows driver intervention for some functions, then the driving flexibility and adaptability are improved, but the driving stability deteriorates due to difficulty in determining the driver's state
Solution Approach 1:
The system continuously monitors multiple driver state parameters (steering angle, acceleration pedal degree, brake pedal degree, vehicle speed) and uses this feedback to dynamically determine whether to maintain autonomous or manual driving mode. The controller compares current driver input with reference values and adjusts the driving mode accordingly, creating a closed-loop control system that maintains stability while allowing flexibility.
Solution Approach 2:
The controller acts as an intermediary between the autonomous driving system and manual driver control. It receives inputs from both sources, processes them according to predetermined conditions, and determines the appropriate driving mode. This intermediary function allows seamless transition between autonomous and manual modes while maintaining overall driving stability.
2Stability of the object's composition
If the system requires careful determination of driver state for intervention, then the driving stability is improved, but the system complexity increases
Solution Approach 1:
The driver state determination process is segmented into multiple independent parameters: steering angle, acceleration pedal degree, brake pedal degree, and vehicle speed. Each parameter is monitored separately and compared against predetermined reference values. This segmentation simplifies the overall complexity by breaking down the determination process into manageable, independent checks rather than requiring a single complex assessment mechanism.
3Measurement precision
If the system compares multiple data sources to determine driving mode, then the accuracy of driver state assessment is improved, but the processing time and computational load increase
Solution Approach 1:
The system performs partial comparisons by checking multiple driver state parameters against reference values, but does not require all parameters to be processed to the same depth. The controller determines driving mode by evaluating whether driver inputs exceed predetermined thresholds, using a sufficient but not exhaustive level of analysis to maintain real-time responsiveness while achieving accurate assessment.
Data Source
AI summary
An apparatus for controlling driving of a vehicle includes a communicator that receives autonomous driving data of another vehicle, a sensor that obtains surrounding environment information and manual driving data of a subject vehicle, and a controller that obtains autonomous driving data of the subject vehicle based on the surrounding environment information and determines whether to switch to autonomous driving of the subject vehicle based on the autonomous driving data and manual driving data of the subject vehicle and the autonomous driving data of the another vehicle.