Real-Time Sound Source Localization for Autonomous Vehicles
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Solution Overview
Problem
Conventional motion planning and control systems for autonomous driving vehicles do not accurately consider vehicle type differences and are inefficient in real-time sound source detection and localization, leading to suboptimal navigation and response to emergency vehicles.
Innovation Solution
A computer-implemented method for sound source detection and localization using an autonomous driving vehicle, which receives audio data from sensors, determines sound source information with confidence scores, and trains machine learning algorithms to recognize specific sounds in real-time, enabling precise localization and tracking of sound sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional motion planning and control systems are used, then the system is simple to implement, but the accuracy of vehicle navigation is insufficient because it does not consider vehicle type differences
Solution Approach 1:
The patent applies local quality by customizing motion planning and control parameters according to different vehicle types. Instead of using a universal control system, the system adapts specific parameters (such as acceleration profiles, steering angles, and response times) to match the characteristics of each vehicle type, thereby improving navigation accuracy without requiring a completely new system architecture
2Speed
If separate detection steps are used for sound source localization, then the detection process is systematic, but the response time is too long to meet real-time requirements
Solution Approach 1:
The patent merges multiple separate detection steps into a unified real-time sound source detection system. By integrating sound source detection, localization, and tracking into a single coordinated process rather than sequential steps, the system achieves both real-time response speed and accurate sound source identification simultaneously
3Reliability
If conventional motion planning is used without sound source detection, then the system is computationally efficient, but the reliability of emergency response is insufficient
Solution Approach 1:
The patent introduces sound source detection and localization as an intermediary system that bridges the gap between conventional motion planning and emergency response requirements. This intermediary layer processes acoustic information and provides enhanced situational awareness to the motion planning system, improving emergency response reliability while maintaining computational efficiency through selective activation and optimized algorithms
Data Source
AI summary
Systems and methods for sound source detection and localization utilizing an autonomous driving vehicle (ADV) are disclosed. The method includes receiving audio data from a number of audio sensors mounted on the ADV. The audio data comprises sounds captured by the audio sensors and emitted by one or more sound sources. Based on the received audio data, the method further includes determining a number of sound source information. Each sound source information comprises a confidence score associated with an existence of a specific sound. The method further includes generating a data representation to report whether there exists the specific sound within the driving environment of the ADV. The data representation comprises the determined sound source information. The received audio data and the generated data representation are utilized to subsequently train a machine learning algorithm to recognize the specific sound source during autonomous driving of the ADV in real-time.