Autonomous Driving Track Diagnosis and Safety Calibration
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Solution Overview
Problem
Autonomous vehicles face uncertainties in identifying traffic lanes and evaluating driving tracks, leading to potential accidents, as existing systems lack effective methods to diagnose and correct driving parameters in real-time.
Innovation Solution
An automatic driving method and device that uses vehicle body and traffic environment information, processed through a diagnostic equation, to assess the safety of future driving tracks and adjust parameters as needed, ensuring compliance with tolerances for curvature, distance, and collision times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If an automatic driving system operates autonomously without driver intervention, then productivity and ease of operation are improved, but reliability deteriorates due to uncertainties in identifying traffic lanes and evaluating driving tracks
Solution Approach 1:
The patent implements a feedback mechanism where the automatic driving system continuously monitors its own driving track parameters (curvature, width, distance to barriers) and compares them against predetermined tolerances. The system receives feedback from sensors detecting traffic lane lines and obstacles, processes this information through a diagnostic equation, and adjusts the driving track in real-time to maintain safety, thereby resolving the reliability issue while maintaining autonomous operation
Solution Approach 2:
The system performs preliminary diagnostic evaluation of the future driving track before actual execution. By using a diagnostic equation to predict and assess upcoming driving parameters against safety tolerances in advance, the system can identify and correct potential safety issues before they manifest, ensuring reliable autonomous operation without continuous driver intervention
2Reliability
If the automatic driving system continuously monitors and diagnoses driving parameters, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent employs a universal diagnostic equation that can evaluate multiple driving track parameters (curvature, width, distance to barriers) using a single integrated mathematical model. This multi-functional approach allows the system to monitor various safety aspects simultaneously without requiring separate complex diagnostic subsystems for each parameter, thus improving reliability while controlling device complexity
Solution Approach 2:
The system focuses on monitoring and adjusting key critical parameters (curvature, width, distance) rather than all possible driving parameters. By identifying and concentrating diagnostic efforts on the most safety-critical parameters with predetermined tolerances, the system achieves comprehensive safety monitoring through a relatively simple diagnostic framework, balancing reliability improvement with acceptable system complexity
Data Source
AI summary
An automatic driving method and device able to diagnose decisions is disclosed herein, wherein a vehicle body signal sensor detects vehicle body information, and an environment sensor detects traffic environment information. The information is transmitted to a central processor to generate a future driving track. The central processor examines whether the differences between the future driving track and the traffic environment information and the indexes of the future driving track meet tolerances. If no, the central processor transmits notification information to an automatic driving controller. If yes, the central processor transmits the future driving track to the automatic driving controller to make the automatic driving controller undertake automatic driving according to the future driving track. The present invention can automatically judge whether the future driving track generated by the central processor is within tolerances and determine whether the automatic driving track is safe.