Autonomous Vehicle Reference Lines from Radar Arc Curves
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Solution Overview
Problem
Current methods for generating a reference line for autonomous driving vehicles are inefficient when camera and digital map data are unavailable due to hardware or software failures, lacking effective alternatives for trajectory planning.
Innovation Solution
The method involves using sensor data from multiple sensors like cameras and RADAR devices to detect objects, generate arc curves, and select the object with the smallest curvature to create a reference line, allowing for trajectory planning without relying on camera or digital map data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If camera and digital map based methods are used to generate reference line, then measurement precision and reliability are improved under normal conditions, but the system becomes vulnerable to hardware or software failures
Solution Approach 1:
The patent introduces an intermediary method using radar sensor data and arc curve fitting as a mediator between the primary camera/digital map system and the fallback mechanism. When camera or digital map data becomes unavailable, the system uses radar-detected objects as intermediate reference points to generate arc curves, which serve as substitutes for the original reference line source, maintaining system operation without direct dependency on the failed component
Solution Approach 2:
The system dynamically changes operational parameters by switching from camera-based visual data to radar-based electromagnetic wave data when failures occur. The patent modifies the data source parameter from optical sensors to electromagnetic sensors, and changes the processing method from direct digital map matching to arc curve fitting based on detected objects, allowing the system to adapt to different operational conditions
2Reliability
If multiple sensors and arc curve calculations are implemented, then tolerance to hardware or software failures is improved, but computational complexity and processing time increase
Solution Approach 1:
The patent extracts only the essential computational elements needed for reference line generation when primary systems fail. Instead of processing all sensor data comprehensively, the system extracts only radar-detected object positions and uses a simplified arc curve fitting algorithm focused on generating a single reference line, reducing computational burden while maintaining failure tolerance
Solution Approach 2:
The system employs a disposable computational approach by using temporary arc curve representations based on detected objects. Rather than maintaining complex, long-term models of the environment, the system creates simple, computationally inexpensive arc curves from current radar data that can be quickly generated and discarded, reducing overall computational complexity
Data Source
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AI summary
A computer-implemented method for operating an autonomous driving vehicle is provided, the method comprising: perceiving a driving environment surrounding an autonomous driving vehicle (ADV), including identifying one or more objects based on sensor data obtained from a plurality of sensors of the ADV; for each of the identified objects, generating an arc curve connecting a current location of the ADV and the object, and calculating a curvature of the arc curve associated with the object; selecting one of the objects associated with an arc curve that satisfies a predetermined condition; and generating a reference line from the current location of the ADV to the selected object, wherein the reference line is utilized to generate a trajectory to drive the ADV. A non-transitory machine-readable medium and a data processing system is also provided.