# US 2025/0095485 A1 · Detecting and responding to sirens > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2025/0095485 A1 - Document ID: US20250095485A1 - Status: Published application - Kind: A1 - Application number: 18/966,262 - Filed: 2024-12-03 - Published: 2025-03-20 - Earliest claimed: 2017-06-27 - Assignees: Waymo LLC - Applicants: Waymo LLC - Inventors: David Harrison Silver; Angus Leigh; Benjamin Ingram; Jennifer Taylor; Vaibhav Nangia - Web page: https://patentgrep.com/patent/US20250095485A1 ## CPC - G08G 1/0965: responding to signals from another vehicle, e.g. emergency vehicle - G01S 3/8083: {determining direction of source} - G01S 5/22: Position of source determined by co-ordinating a plurality of position lines defined by path-difference measurements (G01S5/28 takes precedence) - G01S 11/14: using ultrasonic, sonic or infrasonic waves - G06F 16/683: using metadata automatically derived from the content - G06F 16/686: {using information manually generated, e.g. tags, keywords, comments, title or artist information, time, location or usage information, user ratings} - G06V 20/58: Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads - G08G 1/166: {for active traffic, e.g. moving vehicles, pedestrians, bikes} - H04R 3/005: {for combining the signals of two or more microphones (specially adapted for hearing aids H04R25/407)} - G01S 13/862: {Combination of radar systems with sonar systems} - G01S 13/865: {Combination of radar systems with lidar systems} - G01S 13/867: {Combination of radar systems with cameras} - G01S 17/86: Combinations of lidar systems with systems other than lidar, radar or sonar, e.g. with direction finders - G01S 2013/9318: {Controlling the steering} - G01S 2013/93185: {Controlling the brakes} - G01S 2013/9319: {Controlling the accelerator} - G01S 2013/9323: {Alternative operation using light waves} - G01S 2013/9324: {Alternative operation using ultrasonic waves} - G01S 2013/93273: {on the top of the vehicles} - G01S 2205/01: specially adapted for specific applications - G08G 1/09623: {Systems involving the acquisition of information from passive traffic signs by means mounted on the vehicle (G08G1/0967 takes precedence)} - G08G 1/09626: {where the origin of the information is within the own vehicle, e.g. a local storage device, digital map} - H04R 2499/13: Acoustic transducers and sound field adaptation in vehicles - G08G: TRAFFIC CONTROL SYSTEMS (guiding railway traffic, ensuring the safety of railway traffic B61L; arrangement of road signs or traffic signals E01F9/00; radar or analogous systems, sonar systems, lidar systems specially adapted for traffic control G01S13/91, G01S15/88, G01S17/88; {radar or analogous systems, sonar systems, lidar systems specially adapted for anti-collision purposes G01S13/93, G01S15/93, G01S17/93}) - G01S: RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING - H04R: LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; ELECTRIC HEARING AIDS; PUBLIC ADDRESS SYSTEMS (producing sounds with frequency not determined by supply frequency G10K) ## Abstract The technology relates to detecting and responding to emergency vehicles. This may include using a plurality of microphones 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. ## Claims ### Claim 1 A vehicle configured to operate in an autonomous driving mode, the vehicle comprising: a perception system including plurality of synchronized microphones configured to detect a noise emanating from another vehicle; and one or more processors operably coupled with the perception system, the one or more processors configured to: use output from the plurality of synchronized microphones to generate probabilities of the noise emanating from a particular direction relative to the vehicle configured to operate in an autonomous driving mode; estimate a bearing of the other vehicle based on the generated probabilities; identify at least one road segment associated with the other vehicle; and control the vehicle in the autonomous driving mode to perform a maneuver in response to the estimated bearing and the identified at least one road segment. ### Claim 2 (depends on 1) The vehicle of claim 1, wherein the other vehicle is an emergency vehicle. ### Claim 3 (depends on 1) The vehicle of claim 1, wherein the noise is a siren noise. ### Claim 4 (depends on 1) The vehicle of claim 1, wherein the one or more processors are configured to measure timing of the noise reaching each of the synchronized microphones to provide a probability distribution over possible bearings of the other vehicle. ### Claim 5 (depends on 4) The vehicle of claim 4, wherein the probability distribution is provided over a plurality of possible ranges of the other vehicle. ### Claim 6 (depends on 1) The vehicle of claim 1, wherein the one or more processors are configured to use a model to estimate a probability distribution over possible velocities of the other vehicle. ### Claim 7 (depends on 1) The vehicle of claim 1, where a range of directions with a highest probability corresponds to an estimated bearing for the other vehicle. ### Claim 8 (depends on 1) The vehicle of claim 1, wherein the one or more processors are configured to generate bearing data for different bearings within a 360 degree radius, the bearing data including a probability or a likelihood value associated with one or more of the different bearings. ### Claim 9 A vehicle configured to operate in an autonomous driving mode, the vehicle comprising: a perception system including plurality of synchronized microphones configured to detect a noise emanating from another vehicle; and one or more processors operably coupled with the perception system, the one or more processors configured to: form, by beamforming an array of at least a subset of the plurality of synchronized microphones, a plurality of beams in different directions external to the vehicle; and apply sound corresponding to each of the formed plurality of beams to a first model, wherein the first model focuses listening on one or more locations that are most relevant to the other vehicle. ### Claim 10 (depends on 9) The vehicle of claim 9, wherein the other vehicle is an emergency vehicle. ### Claim 11 (depends on 9) The vehicle of claim 9, wherein the noise is a siren noise. ### Claim 12 (depends on 9) The vehicle of claim 9, wherein the beamforming is used to ignore interfering sounds from locations other than a current location of the other vehicle. ### Claim 13 (depends on 9) The vehicle of claim 9, wherein a first beam of the plurality of beams is formed in front of the vehicle, and one or more additional beams of the plurality of beams that are offset a predetermined amount from the first beam of the plurality of beams. ### Claim 14 (depends on 9) The vehicle of claim 9, wherein the plurality of synchronized microphones are beamformed in order to focus on each direction in which there is a peak in probability of the noise emanating from that direction. ### Claim 15 (depends on 14) The vehicle of claim 14, wherein the peak in probability corresponds to an increased signal-to-noise ratio that provides a more accurate estimation of a bearing, velocity and a range of the other vehicle. ### Claim 16 A method for controlling a vehicle in an autonomous driving mode, the method comprising: using, by one or more processors, output from a perception system including plurality of synchronized microphones configured to detect a noise emanating from another vehicle to generate probabilities of the noise emanating from a particular direction relative to the vehicle configured to operate in an autonomous driving mode; estimating, by the one or more processors, a bearing of the other vehicle based on the generated probabilities; identifying, by the one or more processors, at least one road segment associated with the other vehicle; and controlling, by the one or more processors, the vehicle in the autonomous driving mode to perform a maneuver in response to the estimated bearing and the identified at least one road segment. ### Claim 17 (depends on 16) The method of claim 16, further comprising: forming, by beamforming an array of at least a subset of the plurality of synchronized microphones, a plurality of beams in different directions external to the vehicle; and applying sound corresponding to each of the formed plurality of beams to a first model, wherein the first model focuses listening on one or more locations that are most relevant to the other vehicle. ### Claim 18 (depends on 16) The method of claim 16, further comprising measuring timing of the noise reaching each of the synchronized microphones to provide a probability distribution over possible bearings of the other vehicle. ### Claim 19 (depends on 16) The method of claim 16, further comprising using a model to estimate a probability distribution over possible velocities of the other vehicle. ### Claim 20 (depends on 1) The vehicle of claim 1, further comprising generating bearing data for different bearings within a 360 degree radius, the bearing data including a probability or a likelihood value associated with one or more of the different bearings.