Microphone Array Siren Detection for Occluded Emergency Vehicles
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Solution Overview
Problem
Autonomous vehicles struggle to detect and respond to emergency vehicles, especially when they are occluded or out of range of the perception system, as visual cues like flashing lights may not be discernible, and sirens can be difficult to identify accurately.
Innovation Solution
Equipping autonomous vehicles with microphone arrays to detect siren noise, using models to estimate bearing, range, and velocity of the emergency vehicle, and comparing this information with environmental data to determine an appropriate response.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If visual perception systems are used to detect emergency vehicles, then detection accuracy can be improved when vehicles are visible, but detection fails when emergency vehicles are occluded or out of range
Solution Approach 1:
The patent combines visual perception systems with acoustic detection systems (microphone arrays) to create a multi-modal detection system. The acoustic system detects sirens and estimates emergency vehicle characteristics, while the visual system provides complementary detection when vehicles are visible. This merging of different sensing modalities ensures reliable detection whether the vehicle is visible or occluded.
Solution Approach 2:
The acoustic detection system acts as an intermediary that provides detection capability when visual systems fail. The microphone array detects siren sounds and infers emergency vehicle presence, position, and motion characteristics, serving as a mediator that bridges the gap when direct visual observation is impossible.
2Reliability
If acoustic detection systems are added to detect sirens, then detection capability in occluded situations is improved, but system complexity increases
Solution Approach 1:
The acoustic detection system serves multiple functions: detecting siren presence, estimating emergency vehicle bearing, determining range, and calculating velocity. This multi-functionality reduces the need for separate systems and justifies the added complexity by providing comprehensive detection and tracking capabilities from a single acoustic subsystem.
Solution Approach 2:
The microphone array system is self-contained, using multiple microphones to automatically perform beamforming, siren detection, and parameter estimation without requiring external assistance. The system processes acoustic signals internally to generate emergency vehicle characteristics, reducing the burden on other vehicle systems.
3Measurement precision
If multiple microphones are used to estimate bearing and velocity, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The microphone array is segmented into multiple spatially distributed microphones, each capturing acoustic signals from different positions. This segmentation enables the system to perform spatial processing, beamforming, and time-difference-of-arrival calculations to accurately estimate bearing and velocity of emergency vehicles.
Solution Approach 2:
The system transitions from single-point acoustic detection to spatial acoustic field analysis by distributing microphones across multiple dimensions. This dimensional expansion enables the system to extract bearing and velocity information from the spatial and temporal characteristics of acoustic wavefronts.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables the autonomous vehicle to detect and respond to emergency vehicles even when they are not visibly detected, providing critical information for safe maneuvering and reaction to the emergency situation.
Implementation Method 1
an audio recording of the environment can be captured by a microphone array of the perception system
Data Source
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Figure 3A
AI summary
The technology relates to detecting and responding to emergency vehicles. This may include using a plurality of microphones (152) to detect a siren noise corresponding to an emergency vehicle and to estimate a bearing of the emergency vehicle. This estimated bearing is compared to map information to identify a portion of roadway on which the emergency vehicle is traveling. In addition, information identifying a set of objects in the vehicle's environment as well as characteristics of those objects is received from a perception system is used to determine whether one of the set of objects corresponds to the emergency vehicle. How to respond to the emergency vehicle is determined based on the estimated bearing and identified road segments and the determination of whether one of the set of objects corresponds to the emergency vehicle. This determined response is then used to control the vehicle in an autonomous driving mode.