Emergency Siren Localization for Autonomous Path Selection
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Solution Overview
Problem
Autonomous vehicles struggle to accurately detect and respond to emergency vehicles due to limited line-of-sight perception, leading to inefficient driving paths that can cause traffic congestion and safety risks.
Innovation Solution
Implementing a sound localization model using audio sensors to estimate the location and velocity of emergency vehicles, combined with electromagnetic sensor data, to simulate trajectories and adjust driving paths accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If autonomous vehicles use only electromagnetic sensors (radar, optical) for detection, then the device complexity is reduced, but the measurement precision and detection accuracy of emergency vehicles deteriorate due to limited line-of-sight perception
Solution Approach 1:
The patent combines electromagnetic sensors (radar, optical) with audio sensors to create a multi-modal sensing system. This merging of different sensor types enables the vehicle to detect emergency vehicles through both visual/electromagnetic means and acoustic means, overcoming the line-of-sight limitation while maintaining manageable system complexity through integrated processing.
Solution Approach 2:
The sensing system is designed to perform multiple functions: electromagnetic sensors detect visible and radio wave signatures, while audio sensors detect sirens and acoustic signals. This multi-functionality allows the system to operate effectively in various conditions where one sensor type might fail, improving overall detection accuracy without proportionally increasing complexity.
2Reliability
If autonomous vehicles make conservative driving decisions to ensure safety, then the reliability improves, but the productivity decreases due to unnecessary stops and inefficient driving paths
Solution Approach 1:
The system performs preliminary simulation of emergency vehicle trajectories and potential intersection points before the autonomous vehicle reaches critical decision points. By pre-calculating safe paths and predicting emergency vehicle movements, the system can make informed decisions that ensure safety without requiring conservative unnecessary stops, thus maintaining productivity.
Solution Approach 2:
The system continuously monitors audio signals, updates emergency vehicle location estimates, and adjusts the driving path in real-time based on this feedback. This closed-loop control allows the vehicle to maintain high reliability by responding to actual conditions while avoiding unnecessary conservatism, as decisions are based on current accurate information rather than predetermined conservative rules.
3Measurement precision
If autonomous vehicles simulate multiple emergency vehicle trajectories to ensure safety, then the measurement precision improves, but the computing power requirements and device complexity increase
Solution Approach 1:
The system simulates multiple trajectories for emergency vehicles, but focuses computational resources on the most probable and relevant paths based on audio localization data. By simulating a partial set of trajectories concentrated on high-probability scenarios rather than all possible trajectories, the system achieves sufficient measurement precision while controlling computing power requirements.
Solution Approach 2:
The system pre-processes audio signals to generate probability maps of emergency vehicle locations before trajectory simulation. This preliminary action narrows down the search space and provides informed initial conditions for trajectory simulations, reducing the computational power needed while maintaining or improving location estimation accuracy.
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
Enhances timely and accurate detection of emergency vehicles, ensuring safe and efficient driving paths that avoid unnecessary stops and reduce traffic congestion.
Implementation Method 1
obtain, using one or more audio detectors of a vehicle, a sound recording comprising a sound emitted by an emergency vehicle (EV)
Data Source
AI summary
The described aspects and implementations support sound-based emergency vehicle detection, localization, and tracking for autonomous vehicle and driver-assist systems. The techniques include obtaining, using one or more audio detectors of a vehicle, a sound recording that includes a sound emitted by an emergency vehicle (EV). The techniques further include applying a sound localization (SL) model to the sound recording to obtain a SL output, which includes a first map of possible locations of the EV in a driving environment of the vehicle and can further include a second map of possible velocities of the EV. The techniques further include simulating, using the SL output, trajectories of simulated EV(s) in the driving environment of the vehicle, and causing, responsive to proximity of the simulated trajectories to a driving path of the vehicle, modification of the driving path of the vehicle.