Autonomous Vehicle Test Track Feedback for Objective Performance Metrics
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Solution Overview
Problem
Current methods lack an efficient and objective way to test and evaluate the performance of autonomous vehicles, particularly in determining the impact of software modifications on their operational efficiency under various conditions.
Innovation Solution
A computer-implemented method and system that compares log data from test nodes and autonomous vehicles to determine performance metrics, allowing for the evaluation of software modifications by simulating scenarios such as traffic lights, vehicles, cyclists, and pedestrians, and providing objective feedback on the vehicle's reaction times and smoothness of transitions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional testing methods are used for autonomous vehicles, then testing can be performed, but the evaluation lacks objectivity and efficiency in measuring performance metrics
Solution Approach 1:
The system implements automated feedback loops where sensor data from the test track and autonomous vehicle are continuously collected, processed, and compared against expected performance metrics. This feedback mechanism enables objective evaluation of vehicle performance and software modification effects through systematic data analysis rather than subjective assessment
Solution Approach 2:
The patent replaces traditional manual testing and evaluation methods with automated computational systems. Computing systems automatically collect, process, and analyze log data from multiple sources, substituting human judgment with algorithmic performance metric calculation to improve both objectivity and testing efficiency
2Productivity
If software modifications are made to autonomous vehicle control systems, then operational efficiency can be improved, but the impact of these modifications is difficult to evaluate objectively
Solution Approach 1:
The system performs baseline performance measurements before software modifications are implemented. By establishing pre-modification performance metrics through standardized test track evaluations, the system creates a reference point that enables objective comparison and assessment of software modification impacts
Solution Approach 2:
The system implements controlled feedback loops where software modifications are systematically introduced and their effects are measured against baseline performance. Automated comparison of pre- and post-modification metrics provides reliable assessment of operational efficiency changes while maintaining scientific rigor
3Measurement precision
If comprehensive log data collection is implemented from multiple sources, then performance measurement accuracy improves, but data processing complexity increases
Solution Approach 1:
The system segments data collection and processing into distinct modular components: sensor data acquisition from test track infrastructure, autonomous vehicle telemetry collection, log data generation, and performance metric calculation. This segmentation allows comprehensive data collection while managing processing complexity through distributed, specialized processing modules
Solution Approach 2:
The computing system performs multiple functions through integrated data processing: collecting data from diverse sources, synchronizing timestamps, filtering relevant information, calculating performance metrics, and generating evaluation reports. This multi-functional approach consolidates complex processing tasks into a unified system that manages diversity through standardization
Data Source
AI summary
The present disclosure provides systems and methods to test an autonomous vehicle. In particular, the systems and methods of the present disclosure can receive, from one or more test nodes of a preconfigured test track, log data indicating positions of elements of the test track over a period of time. Log data indicating parameters of an autonomous vehicle over the period of time can be received from the autonomous vehicle. The log data indicating the positions of the elements of the test track over the period of time can be compared with the log data indicating the parameters of the autonomous vehicle over the period of time to determine a performance metric of the autonomous vehicle on the test track over the period of time.