Autonomous Driving Control for Non-Rigid Vehicle Connections
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Solution Overview
Problem
Autonomous driving vehicles with non-rigid connections face inaccuracies in dynamic modeling of connected vehicle bodies, leading to ineffective autonomous driving control due to static depiction of dynamic characteristics.
Innovation Solution
A method and device for obtaining actual position data of connected vehicle bodies and determining relative position data using multiple sensors to accurately depict dynamic characteristics, ensuring accurate autonomous driving control by combining first and second actual position data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a static dynamic model is used for non-rigid connecting parts, then the model can be established in advance, but the accuracy of depicting dynamic characteristics during vehicle driving is very inaccurate
Solution Approach 1:
The patent applies the dynamics principle by transitioning from a static dynamic model to a real-time dynamic model that continuously updates based on current vehicle states. The system dynamically adjusts the model parameters during vehicle operation to reflect the actual non-rigid connecting part characteristics, thereby resolving the contradiction between ease of model establishment and accuracy of dynamic characteristics depiction.
Solution Approach 2:
The patent implements feedback by using sensors to continuously monitor the actual positions of vehicle bodies and feeding this information back to update the dynamic model in real-time. This closed-loop approach ensures the model accurately reflects the current state of non-rigid connecting parts, improving measurement precision while maintaining ease of model establishment through automated updates.
2Measurement precision
If multiple sensors are used to obtain relative position data, then the accuracy of position data is improved, but the complexity of data processing increases
Solution Approach 1:
The patent applies the merging principle by integrating data from multiple sensors and combining it with the dynamic model to compute relative position data. Instead of processing each sensor independently, the system merges their inputs into a unified calculation framework, thereby improving measurement precision while managing data processing complexity through consolidation.
Solution Approach 2:
The patent uses the dynamic model as an intermediary that processes and reconciles data from multiple sensors. The model acts as a mediator that transforms raw sensor data into accurate relative position information, reducing the complexity of direct multi-sensor data processing while maintaining high measurement precision.
3Measurement precision
If real-time position data of both vehicle bodies is obtained, then autonomous driving control accuracy is improved, but the amount of data to be processed increases
Solution Approach 1:
The patent applies the extraction principle by selectively obtaining only the necessary position data required for autonomous driving control. Instead of processing all possible data, the system extracts and processes only the critical real-time position information of both vehicle bodies, thereby improving control accuracy while minimizing the amount of data to be processed.
Solution Approach 2:
The patent uses dynamic modeling to efficiently process real-time position data by continuously updating the model with new data points rather than processing complete historical datasets. This dynamic approach maintains high autonomous driving control accuracy while reducing the computational burden by focusing on incremental updates.
Data Source
AI summary
The present disclosure provides a method and a device for autonomous driving control, a vehicle, a storage medium and an electronic device. The method includes: obtaining first actual position data of a first vehicle body; obtaining relative position data between a second vehicle body and the first vehicle body; determining second actual position data of the second vehicle body according to the first actual position data and the relative position data, so that the vehicle performs autonomous driving control according to the first and second actual position data. The method can obtain the relative position between two vehicle bodies connected in the non-rigid manner and the real-time positions of the two vehicle bodies under different driving conditions in real time during the driving, can accurately depict the dynamic characteristics of two vehicle bodies, so that the vehicle performs autonomous driving control according to the first and second actual position data.