Dosimetry-guided motorcycle speed regulation

Abstract

Method and system of enabling hearing protection for riders of motorcycles, or similar vehicles, rely on establishing a quantitative relationship of sound-pressure level (SPL) within a helmet to the magnitude of effective wind velocity with respect to the helmet. The helmet is equipped with instruments for measuring SPL, travel speed, and travel direction, as well as a controller configured to communicate with a wearer. The quantitative relationship is determined during a training journey. At any point during any subsequent journey, instruments' measurements together with the established quantitative relationship yield the ground wind velocity as well as the magnitude of effective wind velocity. A rider's permissible SPL exposure is determined from respective sound-pressure exposure history and approved hearing-health-care guidelines. A corresponding permissible effective wind speed is determined from the established quantitative relationship. A permissible travel speed is then determined from measured travel speed and direction, and the permissible effective wind speed.

Description

[0001] DOSIMETRY-GUIDED MOTORCYCLE SPEED REGULATION

[0002] FIELD OF THE INVENTION

[0003] The invention relates to motorcycle helmets, and in particular to dosimetry-guided motorcycle speed regulation for motorcycle usage.

[0004] BACKGROUND OF THE INVENTION

[0005] Despite using noise-reduction techniques in helmets, exposure to wind and engine noise while riding a motorcycle can still cause noise-induced hearing degradation or loss. It is known that low-frequency wind sound pressure causes hearing problems which worsen with increased exposure periods. The extent of hearing degradation depends on the exposure duration and sound-pressure intensity.

[0006] Accordingly, there is a need in the industry for developing improved motorcycle helmets and corresponding dosimetry -guided methods and systems.

[0007] SUMMARY OF THE INVENTION

[0008] There is an object of the present invention to provide methods and systems for dosimetry-guided speed regulation for motorcycle usage, including accurately measuring soundpressure levels and tracking a rider’s exposure to noise, to ensure conformance to hearing-health guidelines.

[0009] There is another object of the invention to continuously and automatically determine appropriate travel speeds to ensure safe sound-pressure exposure along route segments of varying effective-wind velocities.

[0010] There is yet another object of the present invention to provide an improved motorcycle helmet, and in particular involving dosimetry-guided motorcycle speed regulation.

[0011] There is yet another object of the invention to determine wind speed and direction based on the sound-pressure level (SPL) versus speed dependency, determined during a training stage.

[0012] According to one aspect of the present invention, there is provided a method for ensuring hearing protection for a motorcycle rider, the method comprising (a) obtaining a quantitative relationship of SPL within a helmet to effective wind speed relative to said helmet, said helmet being equipped with a helmet controller and instruments for measuring SPL, travel speed, and travel direction, (b) during each journey with said motorcycle rider wearing the helmet, said helmet controller continually recording successively measured tuples of said SPL, travel speed, and travel direction, and performing processes of (bl) determining a permissible SPL exposure based on rider-specific sound-exposure history and approved health guidelines, (b2) deducing a permissible effective wind speed corresponding to said permissible SPL exposure using said quantitative relationship, (b3) determining a current ground wind velocity based on said measured tuples and said quantitative relationship, and (b4) determining a current permissible travel speed from said respective ground wind velocity, said permissible effective wind speed, and a current travel direction, thereby ensuring SPL exposure for the motorcycle rider within health guidelines.

[0013] In the method, said obtaining comprises measuring SPL and the travel speed while travelling at different speeds, provided ground wind speed is negligible compared with the travel speed. The method further comprises, prior to (a), while making a training journey traversing a closed-curve route maintaining a constant speed, said helmet controller performing processes of acquiring measurements for a set of tuples of SPL, travel speed, and travel direction for travel directions covering an entire closed-curve route, selecting measured tuples corresponding to travel speeds within predefined speed interval to form a set of selected tuples, interpolating said set of selected tuples to determine values of minimum SPL and maximum SPL, and corresponding travel directions, and determining ground wind direction as the travel direction of the tuple of minimum SPL.

[0014] The method further comprises traversing the closed-curve route for a second time at different travel speeds, and continuing acquiring measurements of the SPL and travel speed to determine said quantitative relationship, subject to determination that a difference between the maximum SPL and the minimum SPL is below a predefined negligible-wind-effect threshold.

[0015] The method further comprises, subject to a determination that a difference between the maximum SPL and the minimum SPL exceeds or equals a predefined negligible-wind-effect threshold, and provided the motorcycle rider travels along said closed-curve route again but at different travel speeds, said helmet controller performs processes of recording further measured tuples of SPL, travel speed, and travel direction, identifying a pair of tuples having SPL values within a predefined SPL interval and a magnitude of travel-speed difference exceeding a predefined speed gap, and determines ground wind speed as a function of said ground wind direction and said pair of tuples.

[0016] In the method, the process (b3) comprises said helmet controller performing processes of selecting two measured tuples where discrepancy of travel speeds exceeds a predefined minimum and discrepancy of travel directions is less than a predefined maximum, determining effective wind speeds corresponding to SPL values of the two measured tuples using said quantitative relationship, determining current ground wind speed based on said effective wind speeds and travel-speed values of the two measured tuples, and determining current ground wind direction from the travel-speed values of the two measured tuples, said effective wind speeds, and said current ground wind speed.

[0017] In the method, the process (b3) comprises said helmet controller performing processes of repeatedly, every predefined span, instructing said rider to stop then resume travelling, and for each span recording an initial SPL value at an instant when a measured tuple indicates zero travel velocity and determining a corresponding ground wind speed from the quantitative relationship, recording a current SPL and travel speed, determining a current effective wind speed corresponding to said current SPL, and determining a ground wind direction based on said ground wind speed, said effective wind speed, and said travel speed.

[0018] The method further comprises said helmet controller communicating said current permissible travel speed to said motorcycle rider. In the method, said instruments comprise a Global Positioning System (GPS) receiver for measuring travel speed and travel direction, a calibrated transducer sensing sound pressure and producing a respective electrical signal, a sampler for producing a succession of samples of the respective electrical signal at a predefined rate sufficient to identify sound-pressure peaks, and a digital filter for frequency-weighting said succession of samples.

[0019] The method further comprises, during said each journey, retaining magnitudes and duration for SPL values exceeding a predefined threshold for updating said rider-specific soundexposure history. The method further comprises, said helmet controller establishing a connection, through a network, to a server for sending a helmet-type identifier of said helmet together with a representation of said quantitative relationship to a server, following said each journey, sending an identifier of a respective rider and data relevant to magnitudes and duration for SPL values exceeding a predefined threshold, receiving long-term SPL-exposure data of said respective rider, receiving forecast wind-velocity at specified latitude-longitude reference points for use in route planning.

[0020] The method further comprises said helmet controller performing processes of acquiring at least two candidate routes for a journey sorting said candidate routes according to one of distance and travel time for each candidate route acquiring forecast wind velocities along route segments, determining an effective wind velocity along each route segment, determining an SPL corresponding to said effective wind velocity using said quantitative relationship, determining duration-weighted average SPL along said each candidate route, and determining a composite cost of said each candidate route as a function of distance, travel time, and SPL exposure, and selecting a candidate route according to said composite cost. According to another aspect of the present invention, there is provided a system for ensuring hearing protection for a community of motorcycle riders comprising a server communicatively coupled to a plurality of helmets, each helmet equipped with a respective helmet controller and instruments for measuring sound-pressure level (SPL), travel speed, and travel direction, said respective helmet controller configured to obtain a quantitative relationship of sound-pressure level (SPL) within said each helmet to effective wind speed relative to said each helmet, and during each journey of a rider wearing said each helmet continually record successive measured tuples of SPL, travel speed, and travel direction, report values and durations of SPL exceeding a prescribed level to said server, determine a permissible SPL exposure based on rider-specific sound-exposure history and approved health guidelines, deduce a permissible effective wind speed corresponding to said permissible SPL exposure using said quantitative relationship, compute a current ground wind velocity based on said measured tuples and said quantitative relationship, and determine a current permissible travel speed from said respective ground wind velocity, said permissible effective wind speed, and a current travel direction.

[0021] In the system, said server is further configured to receive a helmet-type identifier of said each helmet together with corresponding quantitative- relationship data, and for each helmet type filter quantitative-relationship data received from multiple helmets to exclude possible outliers and produce a refined quantitative relationship of SPL to effective wind speed, and disseminate said refined quantitative relationships to helmet controllers of helmets of said each helmet type.

[0022] In the system, said server is further configured to receive an identifier of a particular rider, and data measured during said each journey, using said each helmet, relevant to magnitudes and duration of SPL values exceeding a predefined threshold, and where said particular rider is a client of said sever, determine a respective long-term SPL-exposure data.

[0023] In the system, said respective helmet controller is configured to acquire measurements for a set of tuples of SPL, travel speed, and travel direction for travel directions covering an entire closed-curve route while a respective rider attempts to maintain a constant speed, select measured tuples corresponding to travel speeds within a predefined speed interval to form a set of selected tuples, apply an interpolating function to said set of selected tuples to determine values of minimum SPL and maximum SPL, and corresponding travel directions, and determine ground wind direction as the travel direction of the tuple of minimum SPL.

[0024] In the system, said helmet controller is further configured to record further measured tuples of SPL, travel speed, and travel direction while a respective rider travels along said closed-curve route again at different travel speeds, identify a pair of tuples having SPL values within a predefined SPL interval and a magnitude of travel-speed difference exceeding a predefined speed gap, and determine ground wind speed as a function of said ground wind direction and said pair of tuples.

[0025] In the system, said respective helmet controller is further configured to select two measured tuples where discrepancy of travel speeds exceeds a predefined minimum and discrepancy of travel directions is less than a predefined maximum, determine effective wind speeds corresponding to SPL values of the two measured tuples using said quantitative relationship, determine current ground wind speed based on said effective wind speeds and travel-speed values of the two measured tuples, and determining current ground wind direction from the travel-speed values of the two measured tuples, said effective wind speeds, and said current ground wind speed.

[0026] In the system, said helmet controller is further configured to communicate said current permissible travel speed to said rider. In the system, said server is further configured to acquire a wide-area wind-velocity map indicating estimates of wind speed and direction at reference geographic locations.

[0027] In the system, said server is further configured to determine On-Off activity state of said each helmet of said plurality of helmets based on receiving indications of helmet utilization, helmet type, current-rider identifier, current geographic location, and current travel direction from a helmet controller of said each helmet, determine ground wind speed and ground wind direction corresponding to said current geographic location from the wide-area wind map, determine a current permissible travel speed according to sound-exposure history of said current rider and approved health guidelines, quantitative relationship of SPL to effective wind speed specific to said each helmet, said ground wind speed and ground wind direction, and said current travel direction, and communicate the current permissible travel speed to said helmet controller of said each helmet.

[0028] In the system, said server is further configured to acquire a wide-area wind-velocity map providing wind forecast indicating estimates of future wind speed and direction at reference geographic locations for future travel on a pre-selected route.

[0029] In the system, said server is further configured to determine ground wind speed and ground wind direction corresponding to said future route geographic location from the wide-area wind map, determine a current permissible travel speed according to, sound-exposure history of said current rider and approved health guidelines, quantitative relationship of SPL to effective wind speed specific to said each helmet, said ground wind speed and ground wind direction, and said future travel direction, and communicate the current permissible travel speed to said helmet controller of said each helmet.

[0030] Thus, improved methods and systems for dosimetry-guided speed regulation for motorcycle usage have been provided.

[0031] BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Embodiments of the present invention will be further described with reference to the accompanying exemplary drawings, in which:

[0033] FIG. 1 illustrates a motorcycle noise-dosimetry system comprising a plurality of helmets, of motorcyclists, each helmet being equipped with acoustic-electric-acoustic transducers coupled to a helmet controller communicatively coupled to a server, in accordance with an embodiment of the present invention;

[0034] FIG. 2 illustrates the system of FIG. 1 where the plurality of helmet controller communicates with the server through a network, in accordance with an embodiment of the invention;

[0035] FIG. 3 illustrates helmet circuitry and a respective controller adapted to include dosimetry sensors and control signals, in accordance with an embodiment of the invention;

[0036] FIG. 4 illustrates an exemplary message from a helmet controller to the server controller, in accordance with an embodiment of the invention;

[0037] FIG. 5 illustrates an exemplary message from the server controller to a specific rider, in accordance with an embodiment of the invention;

[0038] FIG. 6 illustrates components of a helmet controller, in accordance with an embodiment of the invention;

[0039] FIG. 7 illustrates components of the server controller, in accordance with an embodiment of the invention;

[0040] FIG. 8 illustrates software modules installed in a helmet controller;

[0041] FIG. 9 illustrates additional software modules installed in the helmet controller;

[0042] FIG. 10 illustrates software modules installed in the server controller;

[0043] FIG. 11 details one of the modules of FIG. 10 for acquisition and dissemination of windvelocity data, in accordance with an embodiment of the invention;

[0044] FIG. 12 illustrates pre-processing of SPL measurements at a helmet controller, in accordance with an embodiment of the invention;

[0045] FIG. 13 illustrates further processing of SPL measurements at the helmet’s controller;

[0046] FIG. 14 illustrates an example of SPL signal samples of an adequate rate to permit detecting peaks, and corresponding cumulative values; FIG. 15 illustrates an example of SPL signal samples of half the rate of the samples of FIG. 14 where some peak SPL values are not detected;

[0047] FIG. 16 illustrates determining, at the helmet controller, helmet location, velocity, attitude, universal time of data collection, and an indication whether the helmet is worn or not;

[0048] FIG. 17 illustrates a basic process of determining SPL-speed relationship based on SPL measurements, helmet velocity, helmet attitude with respect to path of travel and local vertical (optional), and wind velocity;

[0049] FIG. 18 illustrates methods of generating SPL-speed relationship performed at a helmet controller (labeled Method- A, Method-B, Method-C, and Method-D), in accordance with an embodiment of the invention;

[0050] FIG. 19 details Method-A of generating the SPL-speed relationship comprising step-Al and step-A2, in accordance with an embodiment of the invention;

[0051] FIG. 20 details Method-B of generating the SPL-speed relationship, comprising four basic steps labeled Step-Bl, Step-B2, Step-B3, and step-B4, in accordance with an embodiment of the invention;

[0052] FIG. 21 illustrates the principle of determining wind direction in Step-IB, in accordance with an embodiment of the invention;

[0053] FIG. 22 illustrates an Ideal circular travel path for implementing Step-IB;

[0054] FIG. 23 illustrates a realistic closed-curve travel path for implementing Step-IB;

[0055] FIG. 24 illustrates variation of SPL with relative direction of wind of significant effect;

[0056] FIG. 25 illustrates variation of SPL with relative direction of wind of insignificant effect;

[0057] FIG. 26 is a flow chart of an implementation of Step-IB, in accordance with an embodiment of the invention;

[0058] FIG. 27 is a continuation of the flow chart of FIG. 26;

[0059] FIG. 28 illustrates the principle of determining wind speed in Step-2B, given the wind direction determined in Step-IB, in accordance with an embodiment of the invention;

[0060] FIG. 29 illustrates application of Step-2B to determine wind speed, in accordance with an embodiment of the invention;

[0061] FIG. 30 is a flow chart of an implementation of Step-2B, in accordance with an embodiment of the invention;

[0062] FIG. 31 illustrates an example of SPL-speed relationship;

[0063] FIG. 32 illustrates microphone voltage to SPL relationship combined with SPL-speed relationship, in accordance with an embodiment of the invention; FIG. 33 compares the “geographic wind coordinates” and the conventional two- dimensional polar coordinates;

[0064] FIG. 34 illustrates determining relative wind velocity based on a known absolute wind speed;

[0065] FIG. 35 illustrates relative wind velocities corresponding to differing travel speeds in a fixed travel direction;

[0066] FIG. 36 illustrates relative wind velocities corresponding to differing travel speeds and different travel directions;

[0067] FIG. 37 illustrates a first method of determining wind ground velocity using a first SPL measurement and the SPL -speed relationship, yielding two possible wind-ground velocities, in accordance with an embodiment of the invention;

[0068] FIG. 38 illustrates a step of determining the correct wind-ground velocity based on a second SPL measurement, indicating that a first of the two possible wind-ground velocities is the correct wind velocity;

[0069] FIG. 39 illustrates a subsequent step of FIG. 38, indicating that the second of the two possible wind-ground velocities is the correct wind velocity;

[0070] FIG. 40 is a flow chart of the first method of FIG. 37, in accordance with an embodiment of the invention;

[0071] FIG. 41 illustrates a second method of determining wind ground velocity using at least two SPL measurements and the SPL-speed relationship, in accordance with an embodiment of the invention;

[0072] FIG. 42 illustrates computation details of second method of FIG. 41.

[0073] FIG. 43 illustrates computation of wind ground velocity based on SPL measurements corresponding to different travel speeds but fixed travel direction along a route segment, in accordance with an embodiment of the invention;

[0074] FIG. 44 is a flow chart of the second method of FIG. 41 for the case of fixed travel direction along a route segment, in accordance with an embodiment of the invention;

[0075] FIG. 45 illustrates a step of determining a permissible travel speed corresponding to a permissible SPL exposure, in accordance with an embodiment of the invention;

[0076] FIG. 46 is a flow chart of a method of determining dosimetry-guided travel speed, in accordance with an embodiment of the invention;

[0077] FIG. 47 illustrates retained measurements per rider;

[0078] FIG. 48 illustrates notification forms communicated from the server to a client, in accordance with an embodiment of the invention; FIG. 49 illustrates dosimetry-based route selection; and

[0079] FIG. 50 is a flow chart of an algorithm for dosimetry-guided route selection, in accordance with an embodiment of the invention.

[0080] REFERENCE NUMERALS

[0081] 100: A motorcycle noise-dosimetry system comprising a plurality of helmets, of motorcyclists, each helmet being equipped with acoustic-electric-acoustic transducers coupled to a helmet controller communicatively coupled to a server

[0082] 110: Helmet circuitry and controller coupled to a transmitter-receiver (not illustrated) and an antenna 112

[0083] 112: An antenna coupled to a helmet controller

[0084] 114: Control data and measurements data transmitted from a helmet controller 110 to the server 120

[0085] 120: A server comprising a controller (not illustrated), an antenna 1220, and a network interface 160

[0086] 142: Announcements and navigation data sent from the server to individual helmet controllers 110 which may also include multicast data disseminated to all helmet controllers

[0087] 160: Network interface including a transmitter-receiver

[0088] 200: The system 100 where the plurality of helmet controller communicates with the server through a network 250

[0089] 300: Helmet circuitry and controller adapted to include dosimetry sensors and control signals

[0090] 310: Connectors from dosimetry-specific microphones within the helmet

[0091] 312: Data from common sensors

[0092] 314: Data from microphones used for dosimetry

[0093] 316: Connectors carrying electrical signals from inner sensors

[0094] 318: Electric signals from external microphones

[0095] 320: GPS receiver

[0096] 330: Inertial measurement Unit

[0097] 340: Wireless device comprising a transmitter-receiver with associated signal formation according to a wireless protocol

[0098] 342: Connectors carrying electrical signals from microphone 365 to wireless device 340 and electrical signals from wireless device 340 to the common loud speakers

[0099] 360: Helmet shell

[0100] 361: Loudspeaker close to one ear

[0101] 362: Loudspeaker close to the other ear 363: An inner microphone

[0102] 364: An inner microphone

[0103] 365: An inner microphone for transducing rider’s voice for transmission through wireless transmitter-receiver 340

[0104] 368: An external microphone

[0105] 369: An external microphone

[0106] 370: Data sent to helmet controller

[0107] 372: Announcement electrical signals to a common speaker within the helmet

[0108] 374: Dosimetry-specific electric signals to the common speaker

[0109] 380: Data received from helmet controller

[0110] 400: Exemplary message from the helmet controller to the server controller

[0111] 410: A rider (not necessarily a helmet) identifier

[0112] 420: A current location of a rider driving wearing a helmet

[0113] 430: A current time stamp of sending message 400

[0114] 440: A current velocity as determined from a GPS receiver

[0115] 442: A current velocity as determined using other means

[0116] 450: A calculated wind velocity (if already determined)

[0117] 455: Wind-velocity data acquired from external sources

[0118] 460: Inertial measurements

[0119] 470: Helmet current usage (proximity to ear)

[0120] 480: Current SPL measurement

[0121] 500: Exemplary messages from the server controller to helmet controller of a specific rider

[0122] 501: Message sent during current journey

[0123] 502: Message sent shortly after current journey

[0124] 503: Message sent periodically relevant to long-term considerations

[0125] 510: Current time of message 501 (at server location)

[0126] 512: Recommended travel speed limit for a specific rider

[0127] 514: Upper bound of travel speed for the specific rider

[0128] 516: Current wind-velocity vector at current location of the specific rider (determined from GPS data received from the specific rider)

[0129] 518: Forecast wind-velocity vectors in an area surrounding the current location of the specific rider

[0130] 520: Date of message 502 522: Recommended motorcycle usage regulation relevant to travel speed and journey durations

[0131] 524: Updated (refined) SPL -speed function if any

[0132] 530: Date of message 5032

[0133] 532: Recommended long-term motorcycle usage

[0134] 534: General recommendation relevant to motorcycle usage

[0135] 600: An overview of a helmet controller

[0136] 610: A processor assembly comprising a single processor or multiple processors operating concurrently

[0137] 620: Human-machine interface (HMI), comprising push buttons or other tactile controls and / or voice command control

[0138] 630: Software instructions (detailed in FIG. 8 and FIG. 9)

[0139] 640: Sensors’ interface

[0140] 650: Speakers’ interface

[0141] 660: Instruments interface and a module for determining SPL as a function of relative wind speed

[0142] 670: Inertial measurement unit (IMU) interface

[0143] 680: Wireless transmitter-receiver interface

[0144] 690: Data-storage medium

[0145] 700: An overview of the server controller

[0146] 710: A processor or multiple processors operating concurrently

[0147] 720: Human-machine interface (HMI)

[0148] 730: Network interface

[0149] 740: An interface with a wireless transmitter-receiver (optional)

[0150] 750: Software instructions (detailed in FIG. 10, FIG. 11)

[0151] 760: Module for acquisition and dissemination of wide area (or global) wind-velocity data, both current and short-term forecast)

[0152] 770: User-specific specific storage medium organized to hold SPL-exposure history and auditory perception of individual riders

[0153] 780: Storage medium for overall analytics

[0154] 790: Storage medium holding reference tables (such as tabulation of the SPL-speed characteristics, forecast-wind maps, audiometry -related health-directives, etc.)

[0155] 800: Helmet-controller software modules (FIG. 6, 630)

[0156] 810: Module for sampling SPL signals 820: Module for frequency weighting of SPL-signal samples

[0157] 830: Module for parametrizing SPL-signal samples

[0158] 840: Module(s) for determining, or acquiring, SPL -speed relationship

[0159] 850: Module for receiving and processing measurements of an IMU (Inertial-measurement unit) attached to a helmet

[0160] 860: Module for acquiring relevant wind-velocity data from external sources

[0161] 900: Helmet-controller software modules (continued)

[0162] 910: Module for forming and communicating to the server message 400

[0163] 920: Module for updating and storing SPL-exposure data relevant to a specific rider

[0164] 930: Module for accumulating SPL-exposure data for the specific rider

[0165] 940: Module for acquiring SPL-exposure health-effect data

[0166] 950: Module for determining and communicating instantaneous dosimetry-guided speed limit per active rider

[0167] 1000: Server-controller software modules (FIG. 7, 750)

[0168] 1010: Module for receiving information from helmet controllers and update relevant control data accordingly

[0169] 1020: Module for continually updating an SPL-Speed function for dissemination to helmet controllers communicatively coupled to the server controller

[0170] 1030: Module for producing rider-specific guidelines and recommendations

[0171] 1040: Module for acquiring wide-area wind-velocity data and communicating relevant parts thereof to individual riders

[0172] 1100: Module for acquisition and dissemination of wind-velocity data (FIG. 10, 1040)

[0173] 1110: Module for acquiring wind-velocity data of selected pivotal locations

[0174] 1120: Module for receiving location data from active riders (extracted from message 400)

[0175] 1130: Module for determining wind velocities at locations of active users using interpolations

[0176] 1140: Module for communicating significant changes of wind speeds to respective riders

[0177] 1200: Processing SPL measurements at helmet’s controller

[0178] 1210: Process of sampling output electrical signal of an SPL sensor to produce a stream of samples, referenced as “SPL signal samples”, at a sufficiently high rate

[0179] 1220: Process of determining the magnitude of each sample based on a calibration record

[0180] 1230: Process of selecting one of frequency-weighting functions

[0181] 1240: Process of selecting one of two methods of applying the selected frequency-weighting function (Fast Fourier Transform (FFT / Inv-FFT) or digital filtering)

[0182] 1251: Process of applying FFT to successive blocks of samples 1252: Process of modifying the transformed output according to the selected frequencyweighting function

[0183] 1253: Process of applying Inverse FFT to generate the frequency weighted successive blocks of samples

[0184] 1261: A process of synthesizing or acquiring a digital-filtering module corresponding to preferred frequency -weighting functions

[0185] 1262: Process of supplying the stream of samples to a selected digital-filtering module to produce a frequency-weighted stream

[0186] 1270: Subsequent dosimetry processes

[0187] 1300: Processing SPL measurements at helmet’s controller (processes 1270)

[0188] 1310: Memory holding frequency-weighted samples

[0189] 1320: Software module implementing a bandpass digital filter for attenuating frequency components outside a frequency band of wind sound (use of the module may be optional if the wind sound overwhelms other undesirable external sounds)

[0190] 1330: A process of determining cumulative SPL

[0191] 1340: A process of detecting samples (referenced as peak samples) of magnitudes exceeding a predefined SPL threshold

[0192] 1341: A process of recording peak samples values and timing

[0193] 1342: A process of computing inter-peak time intervals and coefficient of variation

[0194] 1400: An example of SPL signal samples, of an adequate rate to permit detecting peaks, and corresponding cumulative values

[0195] 1410: Measured SPL at consecutive sampling time instants

[0196] 1420: Cumulative SPL exposure

[0197] 1500: An example of SPL signal samples of half the rate of the samples of example 1400

[0198] 1510: Measured SPL at consecutive sampling time instants at a lower sampling rate

[0199] 1520: Cumulative SPL exposure at the lower sampling rate

[0200] 1600: Helmet location and velocity determined at helmet controller

[0201] 1622: Time stamp

[0202] 1624: Location (Latitude, longitude)

[0203] 1626: Velocity (SOG, COG)

[0204] 1630: Inertial measurement unit (IMU)

[0205] 1634: Models for determining helmet attitude 1635

[0206] 1635: Helmet attitude

[0207] 1640: Infrared sensor to detect helmet usage 1642: Helmet utilization (on / off state)

[0208] 1700: A first process of determining SPL-speed relationship

[0209] 1750: Module of helmet controller for determining SPL-speed relationship

[0210] 1760: SPL-speed relationship in the form of an array of speed-SPL reference points

[0211] 1800: Methods of generating SPL-speed relationship performed at a helmet controller (labeled Method-A 1810, Method-B 1820, Method-C 1830, and Method-D1840)

[0212] 1900: Details of Method-A of generating the SPL-speed relationship comprising step-lA and step-2A

[0213] 1910: SPL and travel-speed measurements

[0214] 1920: Process of tabulating or parameterizing measurements 1910

[0215] 2000: Details of method-B of generating the SPL-speed relationship comprising four basic steps labeled Step- IB, Step-2B, Step-3B, and step-4B

[0216] 2010: Process of determining wind direction while travelling along a closed-curve (detailed in Figures 21-27)

[0217] 2020: Process of determining wind speed based on the determined wind direction (detailed in Figures 28 to 30

[0218] 2100: Principle of determining wind speed in Step-IB

[0219] 2110: Unknown wind direction (angular displacement ff) and wind speed

[0220] 2120: Reference directions (angular displacement <p, 0<(j)<2 :)

[0221] 2132: Relative wind velocity corresponding to a first of two lowest SPL measurements

[0222] 2134: Relative wind velocity corresponding to the second of the two lowest SPL measurements

[0223] 2142: Relative wind velocity corresponding to a first of two highest SPL measurements

[0224] 2144: Relative wind velocity corresponding to the second of the two highest SPL measurements

[0225] 2200: Implementing Step-IB along an ideal circular travel path

[0226] 2210: Circular travel path

[0227] 2220: Positions (2220(1), 2220(2), ...) of motorcycle along the circular travel path

[0228] 2300: Implementing Step-IB along a realistic closed-curve travel path

[0229] 2310: Closed-curve travel path

[0230] 2320: Positions (2320(1), 2320(2), ...) of motorcycle along the circular travel path

[0231] 2400: Variation of SPL with relative direction of wind of significant effect

[0232] 2410: Measured SPL signal

[0233] 2420: Interpolated SPL signal

[0234] 2430: Maximum SPL (travel direction is opposite to wind direction) 2440: Minimum SPL (travel direction is the same as wind direction)

[0235] 2500: Variation of SPL with relative direction of wind of insignificant effect

[0236] 2530: Maximum SPL - close to mean value SPL indicating a breeze

[0237] 2540: Minimum SPL - insignificant difference from the maximum value, the SPL is mostly the effect of travel speed

[0238] 2600: Flow chart of an implementation of Step- IB

[0239] 2610: Step of travelling along a closed-curve path attempting to maintain a constant speed

[0240] 2620: Process of measuring and recording tuples {y, S, <p}. being a magnitude of SPL signal (in milli-volts, for example), S being travel speed, being travel direction.

[0241] 2630: Process of sorting the tuples {y, S, 0} according to angle in an ascending order or a descending order

[0242] 2640: Process of determining values of <p, <pmin, <pmax, corresponding to minimum and maximum values of SPL-signal values ymin, ymax

[0243] 2650: Process of determining significance, or otherwise, of wind effect based on yminand ymax

[0244] 2660: Application of Method-A, 1810, FIG, 19, since the wind-effect is negligible

[0245] 2670: Application of Method-B, 1820, FIG. 20, to account for the wind effect

[0246] 2700: Continuation of the flow chart 2600

[0247] 2710: Detect indication of a significant wind effect

[0248] 2720: A process of sanity verification to ensure that the measurements are accurate

[0249] 2730: Setting the so-far unknown wind direction 0to equal (pmm

[0250] 2740: Apply step-2B detailed in Figures 28 to 30 to determine the wind speed based on the determined value of wind direction 0

[0251] 2750: Step of reporting potential measurements error

[0252] 2760 Step of terminating execution of Method-B (1820)

[0253] 2800: Principle of determining wind speed in Step-2B, given the wind direction determined in

[0254] Step- IB

[0255] 2900: Application of Step-2B to determine wind speed

[0256] 2910: Wind velocity

[0257] 2920: A pair of SPL signal samples of close magnitudes (within a predefined tolerance), three such pairs are illustrated (2920-1, 2920-2, and 2920-3)

[0258] 3000: Flow chart of an implementation of Step-2B

[0259] 3010: Make at least one trip along a closed-curve path travelling at different speeds

[0260] 3020: Process of measuring and recording a number of tuples {y, S, <p}. y being a magnitude of SPL signal (in milli-volts, for example), S being travel speed, <> being travel direction 3030: Process of sorting the tuples {y, S, 0} according to yin an ascending order or a descending order

[0261] 3040: Process of identifying at least one pair 2920

[0262] 3050: Process of computing an estimate of the wind speed, £2, for at least one pair 2920 using a closed-form expression

[0263] 3060: Process of refining the estimate of from multiple values determined in process 3050

[0264] 3100: An example of SPL-speed relationship

[0265] 3200: Calibration of SPL sensor combined with SPL-speed relationship

[0266] 3210: Relative wind speed

[0267] 3220: Measured parameter of sensor output; e.g., root-mean-square (rms) voltage

[0268] 3230: SPL-sensor characteristics

[0269] 3240: Corresponding SPL value (in Pascal units for example)

[0270] 3300: Relating “geographic wind coordinates” to conventional two-dimensional polar coordinates

[0271] 3310: Magnitude of wind speed

[0272] 3320: Wind angular displacement according to the geographic-wind-coordinates system

[0273] 3330: Wind angular displacement according to the conventional coordinates system

[0274] 3400: Determining relative wind velocity based on a known absolute wind speed

[0275] 3410: One result of deduced relative wind speed

[0276] 3420: Other result of deduced relative wind speed

[0277] 3500: Relative wind velocity corresponding to differed travel speeds with a fixed travel direction

[0278] 3510: One result of deduced relative wind speed

[0279] 3520: Other result of deduced wind speed

[0280] 3600: Relative wind velocity corresponding to differed travel speeds and different travel directions

[0281] 3610: Trajectory segment of fixed direction

[0282] 3620: Following trajectory segment of another fixed direction

[0283] 3700: First method of determining wind ground velocity using the SPL-speed relationship

[0284] 3710: A first travel-velocity vector (speed Si, angle <pi)

[0285] 3720: Contour of relative wind velocity corresponding to measured SPL signal, labeled the Q- circle

[0286] 3730: Contour of wind ground velocity, labeled the Q-circle, with respect to vector 3710

[0287] 3740: 3740-1 and 3740-2 are points of intersection of the Q-circle and contour 3730 3750: Two solutions, 3750-1 and 3750-2, labeled W(1)and W(2), for the wind-ground velocity; one of them is the true wind ground velocity

[0288] 3800: Continued method 3700 to illustrate a process of identifying the true wind ground speed following a first change of the travel direction from <pi to <p2

[0289] 3810: A subsequent travel-velocity vector (Speed S2, angle p2)

[0290] 3820: Contour of relative wind velocity corresponding to measured SPL signal, labeled the Q- circle

[0291] 3830: Contour of wind ground velocity with respect to vector 3810

[0292] 3840: 3840-1 and 38740-2 are points of intersection of the Q(1)-circle and contour 3830

[0293] 3850: Two solutions, 3850-1 and 3850-2 labeled W(3), W(4), for the wind-ground velocity; one of the two solutions {W(3), W(4)} equals one of the two solutions {W(1), W(2)} yielding the sought wind ground velocity

[0294] 3860: A true wind ground speed W(1)

[0295] 3900: Continued method 3700 to illustrate a process of identifying the true wind ground speed following a second change of the travel direction from <pi to <p3

[0296] 3910: A subsequent travel-velocity vector (Speed S3, angle3)

[0297] 3920: Contour of relative wind velocity corresponding to measured SPL signal, labeled the Q- circle

[0298] 3930: Contour of wind ground velocity with respect to vector 3910

[0299] 3940: 3940-1 and 3940-2 are points of intersection of the Q(2)-circle and contour 3830

[0300] 3950: Two solutions, 3950-1 and 3950-2 labeled W(5), W(6), for the wind-ground velocity; one of the two solutions {W(5), W(6)} equals one of the two solutions {W(1), W(2)} yielding the sought wind ground velocity

[0301] 3960: A true wind ground speed W(1)

[0302] 4000: Flow chart of the first method of Figures 27, 38, and 39 (processes 4010, 4020, 4030, and 4040

[0303] 4010: Process of measuring SPL at zero travel velocity

[0304] 4020: A process of acquiring measurements {SPL, S, and ^}at an instant during travel

[0305] 4030: A process of determining the magnitude Q of relative wind speed based on the SPL measurement the SPL-speed function of FIG. 31

[0306] 4040: A process of determining the wind ground direction 0 using a closed-form expression

[0307] 4100: Second method of determining wind ground velocity using the SPL-speed function

[0308] 4110: Wind ground velocity

[0309] 4121: Travel direction along one route segment 4122: Travel direction along a following route segment

[0310] 4200: Computation details of method 4100

[0311] 4300: Computation of relative wind velocity corresponding to different travel speeds but fixed travel direction along a route segment

[0312] 4310: Travel-velocity vectors (variable speeds Si, S2, angle <>)

[0313] 4320: Wind-velocity vector (speed £2, angle ff)

[0314] 4400: Flow chart of the second method 4100 for the case of fixed travel direction along a route segment (processes 4410, 4420, 4430, 4440, and 4450)

[0315] 4410: Acquire multiple measurements of travel velocities and corresponding SPL values (speeds Sm, angles <pm, SPLs, ym, arranged in tuples {Sm, j)m, ym), l<m<p, p>l)

[0316] 4420: Process of selecting tuple pairs, j, k, l<j < p, l<k< p, j ^k, where |Sk-S7| is greater than a first threshold (for example 5 km / hr) and | <- j is less than a second threshold (for example 2°)

[0317] 4430: Compute an intermediate variable |3 from a closed-form expression

[0318] 4440: Compute wind speed 12 from a closed-form expression

[0319] 4450: Compute wind direction 0from a closed-form expression

[0320] 4500: Process of determining a permissible travel speed corresponding to a permissible SPL exposure

[0321] 4600: Flow chart of a method of determining dosimetry-guided travel speed (processes 4610, 4620, 4630, 4640, 4650, 4660)

[0322] 4610: Process of acquiring SPL-speed function (FIG. 31) relating SPL to relative wind speed with respect to rider’s helmet

[0323] 4620: Process of determining overall SPL exposure of rider (both short term and archived longterm exposure data)

[0324] 4630: Process of determining a permissible SPL exposure during a current journey

[0325] 4640: Process of determining a permissible relative wind speed corresponding to the permissible SPL exposure determined in process 4630 (3230, FIG. 32)

[0326] 4650: Determine travel direction, <>, from a GPS receiver, or other helmet instruments, and wind ground velocity (FIG. 40 and FIG. 44, or from other sources)

[0327] 4660: Determine a permissible travel speed, S*, from a closed-form expression

[0328] 4700: Retained measurements per rider

[0329] 4720: Short term (journey-specific or daily) retained detailed measurements

[0330] 4730: Medium term (One-week period, for example) compact measurements 4740: Long term (one-year period, for example) distilled, parameterized measurements (such as mean values, coefficient of variation, and extreme values of SPL to which a rider was subjected and corresponding durations).

[0331] 4800: Notifications (advice, recommendation, warning, etc.) communicated from the server to a client

[0332] 4810: Notifications based on client’s current detailed measurements and compact data 4820: Text and charts based on client’s compact data and archived data 4830: Periodic report based on client’s archived data

[0333] 4900: Dosimetry-based route selection

[0334] 4910: Starting location of a journey

[0335] 4920: Destination

[0336] 4930: Alternate paths

[0337] 4940: Wind velocity

[0338] 5000: Route-selection flow chart (processes 5010, 5020, 5030, and 5040)

[0339] TERMINOLOGY

[0340] Tuple: A tuple is an ordered set of elements. For example, a tuple may be defined as an ordered set of an SPL -signal value, travel speed, and travel direction, denoted {y, S, p} , y being a magnitude of SPL signal (in milli-volts, for example), S being travel speed, and being travel direction with respect to a reference direction.

[0341] Relative wind velocity: The terms “relative wind velocity” and “effective wind velocity” are used synonymously to refer to the velocity of wind with respect to a helmet. With the vector W denoting the ground velocity of wind and the vector V denoting the travel velocity of a motorcycle with a rider wearing a helmet, the relative wind velocity with respect to the helmet (the effective wind velocity), denoted r, is r = W-V.

[0342] Time-averaged measurements: The ground wind velocity is a random variable and is practically quantified in terms of mean values over successive time intervals, each of a predetermined duration. In the present application, the ground wind velocity is not measured directly. Rather, it is deduced from measurements of SPL signals which may be time-averaged over time intervals of a predefined duration for practical considerations.

[0343] DETAILED DESCRIPTION

[0344] FIG. 1 illustrates a motorcycle noise-dosimetry system 100 comprising a plurality of helmets 110 of motorcyclists, each helmet being equipped with signal-processing circuitry, acoustic-electric-acoustic transducers coupled to a controller 116, and a transmitter-receiver connecting to an antenna 112. The server 120 comprises a controller 125, an antenna 122, and a network interface 160 comprising a transmitter-receiver unit. The helmet controllers 116 are communicatively coupled to a server 120. A helmet controller is configured to exchange measurements and control data with the server 120. The helmet controller transmits measurements and control data 114 to the server 120. The server controller 125 transmits announcements and navigation data 142 to individual helmet controllers 116. The server controller 125 may also disseminate multicast data to all helmet controllers.

[0345] FIG. 2 illustrates an implementation 200 of system 100 where the plurality of helmet controllers communicates with the server through a network 250.

[0346] For each connecting helmet, the server receives an identifier of a respective rider and SPL exposure data, measured during each journey, pertinent to magnitudes and durations of SPL values exceeding a predefined threshold. If the rider is a client of the server the server determines a respective long-term SPL -exposure data.

[0347] FIG. 3 illustrates a dosimetry-adapted helmet 300 configured to include dosimetry sensors and control signals. The helmet may include inner sensors and outer sensors and inner loudspeakers. The illustrated sensors include inner sensors 363 and 364 close to a rider’s ears, inner sensor 365 for transducing eider’s voice for transmitting through wireless transmitterreceiver 340, external sensors 368 and 369, loudspeakers 361 and 362 in proximity to rider’s ears.

[0348] The inner sensors may include dosimetry-specific sensors and common sensors. Connectors 310 carry data from the dosimetry-specific sensors to a buffer 314. Connectors 316 carry data from common sensors to a buffer 312. A buffer 318 holds data from external sensors 368A and 368B. The helmet is equipped with a GPS receiver 320, an Inertial measurement Unit 330 attached to the helmet shell 360 and a wireless device 340 comprising a transmitter-receiver with associated signal formation according to an applicable wireless protocol. Connectors 342 carrying electrical signals from microphone 365 to wireless device 340 and electrical signals from wireless device 340 to the common loud speakers.

[0349] Data 370 sent to the helmet’s controller 116 include: GPS-receiver measurements including latitude, longitude, travel speed, and travel direction; output of IMU 330; detected audio signals from external microphones; SPL -signal measurements; sound measurements from other inner sensors; and signals from wireless transmitter-receiver 340.

[0350] Data 380 received from the helmet controller 116 include announcements 372 to a common speaker within the helmet as well as dosimetry-specific data 374 to the loudspeakers.

[0351] Announcements 372 to a common speaker within the helmet as well as dosimetryspecific data 374 to the loudspeakers. FIG. 4 illustrates an exemplary message 400 from a helmet controller 116 to the server controller 125. The message comprises: a rider identifier 410, which is not necessarily a helmet identifier; a current location 420 of a rider traveling wearing a helmet; a current time stamp 430 indicating a time instant of sending message 400; a current velocity 440 as determined from GPS receiver 320; a current velocity 440 as determined using other means (optional); a calculated wind velocity 450 (if already determined); wind-velocity data 455 acquired from external sources (if any); inertial measurements 460; helmet current usage (proximity to ear) 470; and current SPL measurement 480

[0352] FIG. 5 illustrates exemplary messages 500 from the server controller 125 to helmet controller 116 of a specific rider including a message 501 sent during current journey, a message 502 sent shortly after current journey, and a message 503 sent periodically relevant to long-term considerations.

[0353] Message 501 comprises the fields: current time 510 of message 501 (at server location); recommended travel speed limit 512 for a specific rider; upper bound 514 of travel speed for the specific rider; current wind-velocity vector 516 at current location of the specific rider (determined from GPS data received from the specific rider); and forecast wind-velocity vectors 518 in an area surrounding the current location of the specific rider.

[0354] Message 502 comprises the fields: date 520 of message 502; recommended motorcycle usage regulation 522 relevant to travel speed and journey durations; and updated (refined) SPL-speed function 524 if any.

[0355] Message 503 comprises the fields: date 530 of message 503; recommended long-term motorcycle usage 532; and general recommendation 534 relevant to motorcycle usage. FIG. 6 is an overview 600 of a helmet controller 116. A processor assembly 610, comprising a single processor or multiple processors operating concurrently, is coupled to: a human-machine interface (HMI) 620; a memory 630 storing software instructions arranged into multiple modules indicated in FIG. 8 and FIG. 9; a sensors’ interface 640; a speakers’ interface 650; a GPS-receiver interface and a module 660 for determining SPL as a function of relative wind speed; an IMU(inertial measurement unit) interface 670, a wireless interface 680 to wireless transmitter-receiver 340; and a data-storage medium 690 for holding data for subsequent processing.

[0356] FIG. 7 is an overview of the server controller 125. A processor 710, which may comprise multiple processing units operating concurrently, is coupled to: a human-machine interface (HMI) 720; a network interface 730; an interface 740 with a wireless transmitter-receiver (optional); a memory 750 storing software instructions arranged into modules detailed in FIG. 10; a module 760 for acquisition and dissemination of wide area (or global) wind-velocity data, both current and short-term forecast); a rider-specific specific storage medium 770 organized to hold SPL -exposure history and auditory perception of individual riders; a storage medium 780 for holding data for overall analytics; and a storage medium 790 for holding reference tables (such as tabulation of the SPL-speed characteristics, forecast-wind maps, audiometry-related health-directives, etc.).

[0357] FIG. 8 illustrates software modules 800 installed in a helmet controller (FIG. 6, 630).

[0358] Module 810 samples SPL signals (output of a sensor) to produce electrical samples at a sufficiently high rate to capture SPL peaks. Module 820 implements frequency weighting of SPL-signal samples using either Fast-Fourier-Transform (FFT) and inverse-FFT or digital filters (FIG. 12).

[0359] Module 830 characterizes and parameterizes SPL-signal samples. The module performs processes of:

[0360] (a) producing a cumulative value of the SPL samples representing cumulative exposure to SPL for a specific rider;

[0361] (b) separating peak samples of magnitude exceeding a predefined SPL value;

[0362] (c) determining time-weighted averages of the electrical samples, representing time- weighted averages of SPL exposure; and

[0363] (d) determining a coefficient of variation of inter-peak intervals.

[0364] Module 840 determines or acquires SPL-speed relationship which relates SPL to wind relative speed. The wind relative speed is the magnitude of the relative wind-velocity vector which is the wind-ground-velocity vector minus the travel-velocity vector. Methods of determining the SPL -speed relationship from measurements are illustrated in FIG. 18 to FIG. 30.

[0365] Module 850 receives and processes measurements of IMU (Inertial-measurement unit) 330 attached to helmet 300. Module 860 acquires relevant wind-velocity data from external sources or from server 120 (module760).

[0366] FIG. 9 illustrates additional software modules 900 installed in the helmet controller. Module 910 forms message 400 and communicates the message to the server 120. Module 920 updates and stores SPL -exposure data relevant to a specific rider. Module 930 for accumulates SPL -exposure data for the specific rider. Module 940 acquires SPL -exposure health-effect data. Module 950 determines (FIG. 46) and communicates instantaneous dosimetry -guided speed limit per active rider.

[0367] FIG. 10 illustrates software modules 1000 (FIG. 7, 750) installed in the server controller 125. Module 1010 receives information from helmet controllers 116 and updates relevant control data accordingly. The information includes SPL measurements, travel-velocity data, and deduced wind- velocity from connected riders as well as riders’ SPL exposure data.

[0368] Module 1020 aggregates relative wind-speed data and corresponding SPL values of clients of the server and produces a refined up-to-date SPL-speed function in the form of a table or a mathematical expression for dissemination to helmet controllers communicatively coupled to the server controller. Individual riders may generate their own SPL-speed function or use the function received from the server.

[0369] Module 1030 updates rider-specific SPL exposure data and produces rider-specific guidelines and recommendations which are communicated to respective riders. The helmet controllers may be configured to maintain SPL exposure data for respective riders or rely on the information received from the server 120. Module 1040 acquires wide-area wind-velocity data and communicates relevant parts thereof to individual riders.

[0370] FIG. 11 illustrates detailed processes 1100 of module 1040 of FIG. 10 for acquisition and dissemination of wind-velocity data. Process 1110 acquires wind-velocity data of selected reference latitude-longitude (A-X)points which may be spread over a wide-area or even globally with latitudes varying between -90° and +90° and longitude varying between -180° to +180°.

[0371] Process 1120 receives A-X coordinates from active riders (extracted from message 400). Process 1130 periodically determines for each received A-X point a respective wind-velocity vector based on proximity to a reference A-X point or interpolation from adjacent A-X points, determining wind velocities at locations of active users using interpolation. Process 1140 continually communicates significant changes of wind velocities to respective riders FIG. 12 illustrates pre-processes 1200 of SPL signals performed at a helmet controller 160. Process 1210 samples output electrical signal of an SPL sensor to produce a stream of samples, referenced as “SPL signal samples”, at a rate sufficient to identify sound-pressure peaks.

[0372] Process 1220 determines the magnitude of each sample based on a calibration record.

[0373] Process 1230 selects one of frequency -weighting functions based on a default selection or user’s input. Process 1240 selects one of two methods of applying the selected frequency-weighting function (Fast Fourier Transform (FFT / Inv-FFT) or digital filtering) based on a default method or user’s input.

[0374] Process 1251 applies an FFT process to successive blocks of samples. Process 1252 modifies the transformed output of the FFT process according to the selected frequencyweighting function. Process 1253 applies an Inverse-FFT process to generate the frequency weighted successive blocks of samples.

[0375] Process 1261 synthesizes or acquires a digital-filtering module corresponding to a preferred frequency-weighting function. Process 1262 supplies the stream of samples to the digital-filtering module to produce a frequency -weighted stream.

[0376] Subsequent dosimetry processes 1270 follow process 1253 or process 1262.

[0377] FIG. 13 illustrates further processing 1270 of SPL measurements at the helmet’s controller. A memory 1310 holds frequency -weighted samples from process 1253 or process 1262. Software module 1320 implements a bandpass (or low pass) digital filter for attenuating frequency components outside a frequency band of wind sound (use of the module may be optional if it is determined that the wind sound overwhelms other undesirable external sounds)

[0378] Process 1330 determines cumulative SPL for a respective rider. Process 1340 detects samples (referenced as peak samples) of magnitudes exceeding a predefined SPL threshold. Process 1341records magnitudes and time instants of peak samples. Process 1342 computes inter-peak time intervals and coefficient of variation.

[0379] FIG. 14 illustrates an example 1400 of SPL signal samples of an adequate rate to permit detecting peaks, and corresponding cumulative values. SPL values 1410 are measured at consecutive sampling time instants and used to determine cumulative SPL exposure 1420.

[0380] FIG. 15 illustrates another example 1500 of SPL signal samples. SPL values 1510 are measured at consecutive sampling time instants at a lower sampling rate and used to determine cumulative SPL exposure 1520. With half the sampling rate of FIG. 14, some peak SPL values are not detected. FIG. 16 illustrates processes 1600 of determining, at the helmet controller, the helmet’s location and velocity. The measurements acquired from GPS receiver 320 include a time stamp 1622, coordinates (A-X), 1624, of the location of the receiver and travel-velocity vector 1626 (SOG S, and COG (p). The measurements acquired from IMU (Inertial measurement unit) 330 are supplied to models 1634 for determining helmet attitude (e.g., roll, pitch, yaw in a localvertical body-referenced coordinate frame) 1635. Helmet utilization (on / off state) 1642 is determined using an infrared sensor 1640.

[0381] FIG. 17 illustrates a basic process 1700 of determining SPL-speed relationship based on SPL measurements, helmet velocity, and wind velocity. A generalized module 1750 is configured to determine SPL-speed relationship 1760 (FIG. 31) according to one of four methods indicated in FIG. 18. The SPL-speed relationship may be presented in the form of an array of speed-SPL reference points or a parameterized mathematical expression.

[0382] FIG. 18 illustrates methods 1800 of generating SPL-speed relationship performed at a helmet controller (labeled Method-A, Method-B, Method-C, and Method-D).

[0383] Method-A is applicable when the helmet controller determines, or learns from external sources, that a current ground wind speed is negligible (see, for example, FIG. 25).

[0384] Method-B applies when the helmet controller learns that the ground wind velocity is expected to be stable for a period of time sufficient to acquire SPL and travel-speed measurements.

[0385] Method-C is performed at the server and the resulting SPL-speed function is communicated to individual helmet controllers. The server determines the SPL-speed function based on SPL and travel-velocity measurements received from multiple helmets and filtered to exclude possible outliers.

[0386] Method-D is performed using a wind tunnel where a helmet is static and exposed to wind of controllable speed.

[0387] FIG. 19 illustrates steps 1900 of Method-A of generating the SPL-speed relationship comprising. Step 1910 (Step-IA) is a process of tabulating or parameterizing the measurements. Step 1910 measures and records SPL values at different travel speeds. Step 1920 arranges pairs of SPL and travel-speed in a look-up table and / or synthesizes a piecewise-linear SPL versus speed function and a piece-wise linear inverse travel-speed versus SPL function. It is also understood that interpolation curve may be produced based on SPL-speed measurements.

[0388] FIG. 20 illustrates processes 2000 of Method-B of generating the SPL-speed relationship, comprising four basic steps labeled Step- IB (2010), Step-2B (2020), Step-3B (2030), and Step- 4B (2040), respectively. Process 2010 determines wind direction, 0, detailed in Figures 21 to 27. While travelling along a closed-curve and attempting to maintain a constant travel speed, measured values y of SPL, and travel velocity {S, 0} are retained in a first record of tuples {y, S, <p}.

[0389] Process 2020 determines ground wind speed (detailed in Figures 28 to 30) based on the determined wind direction 0. Subsequently, while travelling along the closed-curve at different speeds, measured values y of SPL and travel velocity {S, 0} are retained in a second record of tuples {y, S, <p}.

[0390] Process 2030 calculates, for each measurement tuple of the second record, a respective relative wind speed, Q, based on the determined ground wind direction 0 and speed , and respective values of travel velocity {S, 0} .

[0391] Process 2040 arranges pairs of {SPL y, relative wind speed Q) in a lookup table. Additionally, a piecewise linear function relating SPL to relative wind speed, and an inverse piecewise linear function relating relative wind speed to a measured SPL are derived.

[0392] FIG. 21 illustrates a method 2100 of determining ground wind direction in process2010. The objective is to determine the ground wind velocity, W, 2110, i.e., the ground wind speed, denoted Q, and angular displacement, denoted 0, in order to determine the relative wind velocity (W-V) at different travel velocities V (different travel speeds S and different travel directions 0). The figure illustrates a background of reference travel directions 2120 (angular displacement 0, 0 <0<2.T) and relative wind directions at selected travel directions. The SPL signal is captured at different travel directions. At a given travel speed S, the travel direction <pminyielding the lowest SPL and the travel direction <pmaxyielding the highest SPL correspond to relative wind speeds of | S-Q| and |S+ | and have values of: <pmin= 0, and <pmax= O+.T, respectively.

[0393] Determining <pminprecisely may be realized if the SPL is measured at numerous instants along a closed-curve travel path traversing all directions 0, (0 <0<2.T), which is impractical. Alternatively, the helmet controller 116 may measure SPL at a reduced number of points along the closed-curve path then use an interpolating function (FIG. 24) to determine 0minand <pmax. In the illustrated example, the number of SPL sampling points is 24. Measured SPL signals at the relative wind directions at 0=45° and 0=60° (2132, 2134, respectively) have the lowest values while measured SPL signals at 0=225°and 0=240° (2142 and 2144, respectively) are the highest.

[0394] FIG. 22 illustrates an implementation 2200 of Step-IB using an Ideal circular travel path 2210. The helmet controller instructs the rider of the motorcycle to attempt to maintain a constant speed within the permissible speed limits. Relative wind-velocity vectors are illustrated at different instants along the travel path corresponding to travel directions 0i, 02, 03, and 04 (225°, 315°, 45°, and 135°), motorcycle positions 2220(1), 2220(2), 2220(3), and 2220(4), respectively.

[0395] FIG. 23 illustrates an implementation 2300 of Step-IB using a realistic closed-curve travel path 2310. The helmet controller instructs the rider of the motorcycle to attempt to maintain a constant speed within the permissible speed limits. As in the case of the ideal circular path, relative wind-velocity vectors are illustrated at different instants along the travel path corresponding to travel directions <pi, <p2, (j>3, and <p4(225°, 315°, 45°, and 135°), motorcycle positions 2320(1), 23220(2), 2320(3), and 23220(4), respectively.

[0396] FIG. 24 illustrates SPL variation 2400 with relative direction of wind of significant effect while travelling along a closed-curve path at a constant speed. Samples 2410 of the SPL signal are recorded and an interpolated SPL signal 2420 is generated using known methods. The travel angle <pmincorresponding to the minimum SPL 2440, and the travel angle 0mil-< corresponding to the maximum SPL 2430, are then determined. The maximum SPL 2430 corresponds to a travel direction opposite to ground wind direction) while the minimum SPL 2440 corresponds to travel direction parallel to the ground wind direction.

[0397] FIG. 25 illustrates variation of SPL variation 2500 with relative direction of wind of insignificant effect while travelling along a closed-curve path at a constant speed. As in the case of FIG. 24, samples 2410 of the SPL signal are recorded and an interpolated SPL signal is generated using known methods. The maximum SPL 2530 is close to mean value SPL indicating a breeze of insignificant effect. The difference between the minimum SPL 2540 and the maximum SPL 2530 is insignificant. The overall SPL is mostly the effect of travel speed, thus Method-A (FIG. 18, FIG. 19) of generating the SPL-speed relationship may be applied.

[0398] FIG. 26 is a flow chart 2600 of an implementation of Step- IB. To start, a rider makes at least one tour around a closed-curve path while attempting to maintain a constant travel speed within allowed limits. The helmet controllerll6 then performs the following processes 2620 to 2650. Process 2620 measures and records tuples {y, S, <p}. being a magnitude of SPL signal (in milli-volts, for example), S being travel speed, <p being travel direction. Process 2630 sorts the tuples {y, S, 0} according to angle <p in an ascending order or a descending order.

[0399] Process 2640 determines the minimum and maximum values of <p, denoted <piow an<i <pugh), corresponding to the minimum and maximum values of SPL-signal values ymjn. ymax. The controller identifies a first set of m contiguous tuples surrounding the tuple of lowest SPL and a second set of m contiguous tuples surrounding the tuple of highest SPL. An interpolating function is then used to determine accurate approximations of <piowand (phigh and corresponding SPL values yminand y„i;i-,. The difference l^wgh-^nml should be n radians (180°) if the measurements are sufficiently accurate.

[0400] Process 2650 compares the difference (ymax-ymin) with a predefined tolerance, denoted Ay. If ymin) is less than Ay, the ground-wind effect is considered negligible and process 2660 proceeds to implement Method-A (FIG. 18 and FIG. 19). Otherwise, process 2670 proceeds to process 2720 of FIG. 27 to perform a measurement-sanity check.

[0401] FIG. 27 is a continuation of the flow chart of FIG. 26. Process 2710 detects an indication of a significant wind effect. Process 2720 examines the magnitude of \ <phigh-<pmin - | which would be zero if all measurements are precise but would be below a tolerance e2, e2>0.0, if the measurements are accurate enough. If \ <pMgh-<pmm ~ ^ \ is less than e2, process 2730 sets the unknown wind direction 0 to equalowthen process 2740 proceeds to apply step-2B, detailed in Figures 28 to 30, to determine the wind speed based on the determined value of wind direction 0. If measurement accuracy is not established, process 2720 leads to process 2750 which reports potential measurements error to a system administrator, and process 2760 terminates execution of Method-B (1820, FIG. 18).

[0402] FIG. 28 illustrates the principle 2800 of determining wind speed in Step-2B, given the wind direction determined in Step-IB. In general, Method-B is applied when the helmet controller learns that the ground wind velocity is expected to be stable for a period of time sufficient to acquire SPL and travel-speed measurements. It is plausible that this condition be normally met for a short period during which sufficient measurements of travel velocity and corresponding SPL value be recorded.

[0403] For any pair of helmet locations along a path where the magnitudes of the relative wind velocities (the relative wind speeds) with respect to the helmet are equal, the wind speed, , is is determined from the expression: = 0.5 X (Sk2-Sj2) / ((SkXcos(0- k) -SjXcos (G- )), using the notation of the illustrated example.

[0404] In the illustrated example, the ground-wind velocity W (magnitude , angle 0) at a first location (location-j) remains unchanged at a second location (location-k). The travel speed and angle at location-j are denoted Sj cmd respectively. The travel speed and angle at location-k are denoted Sk and respectively.

[0405] For any pair of helmet locations along a path where the magnitudes of the relative wind velocities (i.e., the relative wind speeds) with respect to the helmet are determined to be equal, the wind velocity, , may be determined from the travel velocities at the two locations and the direction of the ground-wind. In the example of FIG. 28, the outputs of an SPL sensor at two points, j, k, are almost equal, within a tolerable difference. The direction, 0, of the ground wind is determined to be 0 = 55°. The travel velocities at the two points, denoted as Vj and Vk, where V) = Sj (j>j, and Vk= SkZtpk, are measured as: Sj = 60 km / hour, = 170°, Sk= 100 km / hour, (pk= 112°. The relative wind velocity vectors, Fj and Fk, have different angular displacements but almost equal magnitudes (85.02 km / hr and 85.10 km / hr, respectively), leading to SPL signals of close magnitudes. The resulting estimate of the ground wind speed is then Q «= 40.09 km / hr

[0406] FIG. 29 illustrates a method 2900 of applying the principle of FIG. 28 to determine ground-wind speed given that the wind speed has been determined. After determining the ground-wind direction, 0, the helmet controller instructs the rider to travel along the closed- curve path, or along any curved path within the vicinity of the closed-curve path, at different speeds within permissible speed limits. The helmet controller continues to measure and store tuples {y, S, 0} at successive time intervals. Upon collecting a predefined number of tuples, the helmet controller sorts the tuples, in an ascending or descending order, according to the value yof the SPL. Pairs of tuples 2920 having sufficiently-close values of SPL are then identified and the expression indicated above with reference to FIG. 28 is used to determine respective values of the unknown wind speed . In the illustrated example of FIG. 29, three pairs of tuples 2920(1), 2920(2), and 2920(3), of close (or luckily equal) values of SPL levels are identified. The three pairs correspond to travel velocities of {Sa, (pa}, {Sb, (j>b}, and {Sc, Thus, three approximations of can be determined from which a refined approximation can be determined.

[0407] FIG. 30 is a flow chart 3000 of an implementation of method 2900 at the helmet controller 116. In process 3010, the helmet controller instructs the rider to make at least one trip along the closed-curve path, or a nearby curved path, travelling at different speeds.

[0408] Process 3020 measures and records a number M of tuples {y, S, ). y being a magnitude of SPL signal (in milli-volts, for example), S being travel speed, being travel direction; M>Mmin, Mmin being a predefined number. Process 3030 sorts the M tuples {y, S, 0} according to values of yin an ascending order or a descending order. Process 3040 identifies at least one pair of tuples of values of y within a predefined proximity. Process 3050 computes an approximation of the wind speed, 12, for each pair of tuples {y, Sj, }, {y, Sk, of sufficiently close values of y using the closed-form expression: = 0.5 X (Sk2-Sj2) / ((SkX cos(0-(j)2) -SjXcos(0-^))).

[0409] Process 3060 refines the approximation of from multiple values determined in process 3050 if more than one approximation of has been determined. FIG. 31 illustrates an example 3100 of SPL-speed relationship function 3150 relating SPL values 3120 (typically logarithmic values) in Pascals, to relative wind speed 3110, in kilometers / hour, which is the magnitude of the relative wind velocity r, r= W-V, W being the ground wind velocity and V the travel velocity.

[0410] FIG. 32 illustrates combined functions 3200 of the SPL-speed function 3150, which relates SPL values in Pascal, for example, to relative wind-speed, in kilometers / hour, for example, and a transducer (sensor) function 3230 relating calibrated SPL-signal parameter (a root-mean-square, rms, value, for example) 3220 to SPL values in acoustic units. The signal parameter of sensor output is preferably root-mean-square (rms) voltage. An SPL signal is an output electrical signal of an acoustic-electrical transducer, also referenced as sound sensors.

[0411] A helmet controller of each helmet reports to the server a helmet-type identifier together with a representation of a respective quantitative SPL-speed relationship as well as an identifier of a respective rider and data relevant to magnitudes and durations for SPL values exceeding a predefined threshold. The helmet controller receives from the server long-term SPL -exposure data of the respective rider as well as forecast wind-velocity at specified latitude-longitude reference points for use in route planning.

[0412] The server is configured to receive a helmet-type identifier of each connecting helmet together with a respective corresponding quantitative SPL-speed relationship data. For each helmet type, the server filters quantitative-relationship data received from multiple helmets to exclude possible outliers and produce a refined quantitative relationship of SPL to effective wind speed. The server disseminates the refined quantitative relationships to the helmet controllers of helmets of said each helmet type.

[0413] FIG. 33 illustrates a relationship 3300 between two planar polar coordinate systems; specifically, the “geographic wind coordinates” and the conventional two-dimensional polar coordinates. For a given ground-wind velocity vector 3310 of magnitude , the angular displacement 3320, according to the geographic-wind-coordinates system, is denotes ip, and the angular displacement 3330, according to the conventional coordinates system, is denoted 0. The angle ip is measured from the North direction in the clockwise direction while the angle Ois measured from the east direction in the counterclockwise direction. Consequently, |0+ rp| = n / 2.

[0414] FIG. 34 illustrates a step 3400 of determining ground-wind direction, 0, based on an SPL measurement at a travel speed S, travel direction <p, and a known ground- wing speed . Using the SPL-speed function of FIG. 31, the magnitude, Q, of the relative wind velocity corresponding to the measured SPL can be determined. The ground-wind direction, 0, is then determined from the expression: cosftl-ft) = (2+ S2- Q2) / 2X XS, which yields two values of 0, denoted 01 and 02, hence, two possible vectors, W(1)and W(2), of the ground-wind velocity with corresponding vectors T(1)(3410) and T(2)(3420) of the relative wind velocity.

[0415] FIG. 35 illustrates an example 3500 of relative wind velocities corresponding to differed travel speeds with a fixed travel direction. Two relative wind-velocity vectors of equal magnitudes (equal relative wind speeds) are determined for each travel speed. The SPL is a function of relative wind speed regardless of relative wind direction. Relative wind-velocity vectors T(1)(3510) and T(2)(3520) correspond to travel-speed S.

[0416] FIG. 36 illustrates an example 3600 of relative wind velocities corresponding to differed travel speeds and different travel directions. Travelling along a first route segment 3610, at a first point where the travel speed is Si and travel direction is <pi (210° in the illustrated example), the helmet controller 116 acquires an SPL signal measurement and the functions 3230 and 3150 are used to determine a corresponding relative wind speed Qi. With a known ground wind speed, , the ground wind direction, 0a, is determined from the expression: cos(ft^) = (2+ Si2- Qi2) / 2X XS1, which yields two values of 0a, denoted ft and ft, hence two vectors of ground wind velocity, denoted W(1)and W(2), and two vectors of relative wind velocity of equal magnitudes, each being equal to Qi. Only one of the ground wind velocity vectors W(1)and W(2)corresponds to the actual wind direction.

[0417] As illustrated, the rider makes a right turn to travel along a second route segment 3620. At a second point, in the vicinity of the first point as determined from GPS measurements), where the travel speed is S2, and the travel direction is <p2(120°in the illustrated example), the helmet controller 116 acquires another SPL measurement and the functions 3230 and 3150 are used to determine a corresponding relative wind speed Q2. With the known ground wind speed, , the ground wind direction, 0b, is determined from the expression: cos(ft-2) = (2+ S22- Q22) / 2X XS2, which yields two values of 0b, denoted ft and ft, hence two vectors of ground wind velocity, denoted W(3)and W(4), and two vectors of relative wind velocity of equal magnitudes, each being equal to Q2. Only one of the ground wind velocity vectors W(3)and W(4)corresponds to the actual wind direction.

[0418] With the two points at which the SPL measurements were taken being in the same vicinity, the ground wind directions are considered to equal. Thus, the direction pair {0 02) and the direction pair {03, 04) have one direction in common. In the illustrated example, ()■>,«= 0i, hence the wind direction is determined as (ft+ ft) / 2.

[0419] FIG. 37 illustrates a first method 3700 of determining wind ground velocity W (magnitude , direction 0) using SPL measurements and the SPL-speed relationship. The ground wind speed is determined from the SPL-speed function (FIG. 31) and an initial SPL measurement taken when the helmet controller determines that the helmet speed is zero or negligibly small.

[0420] At a first travel-velocity 3710 Vi (speed Si, angle (pi), the SPL is measured and a corresponding relative wind speed Q(1)is determined (FIG. 31, FIG. 32). Thus, only the magnitude of the relative wind velocity T(1)is known. The relative wind-velocity T(1), which equals (W-Vh), is determined from the intersection of a circular contour 3720 of radius Q(1), labeled Q(1)circle, and a circular contour 3730 of radius , labeled Q-circle, with respect to vector 3710. The intersection points 3740-1 and 3740-2 define two candidate directions of the wind directions. Thus, two candidate vectors, W(1)and W(2)(references 3750-1 and 3750-2), for the wind-ground velocity are determined; one of them is the true wind ground velocity.

[0421] FIG. 38 illustrates a process 3800 of identifying the true wind-ground velocity based on a second SPL measurement following a change of the travel direction from (pi to (p2. Based on a subsequent travel-velocity vector 3810 (speed S2, angle (p2) and a measured SPL signal with a corresponding relative wind speed Q(2) determined from the SPL-speed function (FIG. 31), two candidate vectors, W(3)and W(4)(references 3850-1 and 3850-2), for the ground wind velocity are determined. As described above with reference to FIG. 36, the pair of candidate vectors {W(1)and W(2)} and the pair of candidate vectors {W(3)and W(4)} of the ground wind velocity have one vector in common corresponding to the true ground wind velocity. In the example of FIG. 37 and FIG. 38, the common vector is W(1), or (W(1)+ W(2)) / 2. Contour of wind ground velocity with respect to vector 3810 is designated by reference numeral 3830.

[0422] FIG. 39 illustrates a process 3900 similar to process 3800 where the wind velocity is W(2)instead of W(1).

[0423] FIG. 40 is a flow chart 4000 of the first method of FIG. 37. Process 4010 measures SPL at zero travel velocity when the helmet is in a standstill position. The measured SPL is used to determine the wind speed using the functions of FIG. 32 which related SPL to the relative wind speed. The relative wind is the magnitude of the relative wind velocity which is the wind velocity minus the travel velocity. Process 4020 acquires measurements {SPL, S, and ^}at an instant during travel. An SPL is acquired from a sensor. The travel speed, S, and direction, (p, are read from the GPS receiver 320. Process 4030 determines the magnitude Q of relative wind velocity based on the SPL measurement the SPL-speed functions of FIG. 32. Process 4040 determines the wind ground direction 0 from the expression: cos(0- ) = (2+ S2- Q2) / 2X XS.

[0424] FIG. 41 illustrates a second method 4100 of determining wind ground velocity using at least two SPL measurement and the SPL-speed function. At the start of a journey, the wind ground velocity 4110 (W, magnitude , direction 0) is unknown.

[0425] Travelling along a route segment 4121 at a speed Si and angle <pi, the corresponding relative wind speed, Qi, can be determined from an SPL measurement and the functions of FIG. 32. The unknown and 0 relate to the known Sb and Qi according to:

[0426] Travelling along another route segment 41221 at a speed S2and angle <p2, the corresponding relative wind speed, Q2, can be determined from an SPL measurement and the functions of FIG. 32. The unknown and 0 relate to the known S2, <p2, and Q2according to:

[0427] Q22=2+ S22-2X X S2XCOS (0-< >2).

[0428] While there is enough information to compute and 0, the computation can be significantly simplified if the direction is kept constant, so that ^2=^i = ^. Maintaining a constant direction may not be feasible. However, taking a sufficient number of measurements of SPL, S, and >, can yield several measurements of close angular displacements and each pair of such measurements can be used to determine and 0 from closed-form expressions, as illustrated in FIG. 43.

[0429] FIG. 42 illustrates computation details of method 4100.

[0430] FIG. 43 illustrates computation 4300 of wind ground wind velocity 4320 in an area of interest, such as a route segment, based on SPL measurements corresponding to different travel speeds but fixed travel direction along a route segment.

[0431] Travel-velocity vectors 4310 have variable speeds SbS2, ...but the same direction (angular displacement) (j). As discussed above in the discussion of FIG. 41, vectors 4310 may be interleaved with vectors of different directions, along a route segment, which are not considered.

[0432] Values of SPL (electrical) signals from an SPL sensor are measured at several points of different speed values Si, S2, . . ., and corresponding relative-speed values QbQ2, ... are determined (FIG. 32). As mentioned above, the selected points correspond to angular displacements (pl, (p2, ... of sufficiently close values and approximated to a same value (j).

[0433] The wind ground velocity (speed , angle 0) is then determined as follows. An intermediate variable |3 is defined as:

[0434] P= (Sk+ Sj) -((Qk2-Qj2) / (Sj-Sk)), then and 0 are determined from: 2 = Qj2- Sj2+ pXSj and cos(0-^) = 0.5 X p / Q.

[0435] FIG. 44 is a flow chart 4400 of the second method of FIG. 41 for the case of fixed travel direction along a route segment. Process 4410 acquires multiple measurements of travel velocities and corresponding SPL values (speeds Sm, angles pm, SPLs, ym, arranged in tuples {Sm, <pm, ym), l<m< p, p>l). Process 4420 selects tuple pairs, j, k, l<j < p, l<k< p, j ^k, where | Sk-S,| is greater than a first threshold (for example 5 km / hr) and l^-^j is less than a second threshold (for example 2°).

[0436] Process 4430 computes an intermediate variable |3 from a closed-form expression: p= (Sk+ Sj) -((Qk2-Qj2) / (Sj-Sk)).

[0437] Process 4440 computes wind speed from a closed-form expression: 2 = Qj2- Sj2+ pxSj.

[0438] Process 4450 computes wind direction 0 from a closed-form expression: cos(0-^) = 0.5 X |3 / .

[0439] FIG. 45 illustrates a process 4500 of determining a permissible travel speed Smaxcorresponding to a permissible SPL exposure based on a permissible SPL value ymax. a known ground wind velocity 4505 (speed , direction 0), and a travel direction (p. The functions of FIG. 32 are used to determine a permissible relative wind speed Qmaxcorresponding to ymax. The permissible travel speed Smaxis then determined as: where a= ()-([>, and |oc| = amoduio2n, if a>0, or (2n+a) if a<0.

[0440] Two cases 4510 and 4520 where riders travel under the same ground wind velocity and subject to the same constraint ymaxbut traveling in different directions are illustrated.

[0441] FIG. 46 is a flow chart 4600 of the method of determining dosimetry-guided travel speed.

[0442] Process 4610 acquires SPL-speed function 3150 (FIG. 31) relating SPL to relative wind speed with respect to rider’s helmet and SPL sensor characteristics 3230 (FIG. 32). Process 4620 determines overall SPL exposure of a rider (both short term and archived long-term exposure data) from logged data. Process 4630 determines a permissible value ymaxof SPL exposure during a current journey. Process 4640 determines a permissible relative wind speed corresponding ymax. Process 4650 determines travel direction, (p, from a GPS receiver, or other helmet instruments, and wind ground velocity (algorithm 4000 or 4400, or from other sources). Process 4660 determines a permissible travel speed, Smax, from the closed-form expression of FIG. 45. The helmet controller of each helmet communicates current permissible travel speed to a respective motorcycle rider.

[0443] FIG. 47 illustrates an example 4700 of retained measurements for a rider. The retained measurements include SPL exposure in terms of duration and intensity, and includes detailed short-term data 4720, compact medium-term data 4730, and parameterized long-term data 4740. The data may be retained in a memory device coupled to controller 116 of the rider’s helmet. Additionally, the measurements may be communicated to the server controller 125. The data stored in the server 120 is preferably rider-specific not helmet specific.

[0444] The short-term data 4720 may be journey-specific or daily -travel-based and used to provide guidelines or warnings in real-time according to reference health directives. The medium-term data, which may be stored for a week, or so, may be used for short-term travel planning taking into account hearing-health considerations. The Long-term data, which may be stored for much longer periods, may be used for regulating motorcycle usage. Considering the requisite storage size and processing requirements, long-term data are preferably distilled and parameterized as mean values, coefficients of variation, and extreme values of SPL intensity and exposure durations.

[0445] The durations TbT2, and T3of time-limited storage of short-term, medium-term, and long-term data may be specified. The information stored for each time scale is preferably also be specified. As illustrated, the detailed data 4722 retained for a period Ti is reduced in size to compact data 4732 to be held for a week, for example, and subsequently reduced to distilled data 4742 to be held for a year, or so. The indicated data sizes 4722, 4732, and 4742 are not drawn to scale; the data size 4722 would be orders of magnitude larger than data size 4742.

[0446] The stored SPL measurements may include: moments of SPL values and moments of inter-peak time intervals.

[0447] FIG. 48 illustrates notification forms 4800 communicated from the server to a client. A notification of any form may include an advice, a recommendation, a warning, etc. Notification form 4810 may comprise a text based on client’s current detailed measurements or compact data. Notification form 4820 may comprise a text and charts based on client’s compact data and archived data. Notification form 4830 may be a periodic report based on client’s archived data

[0448] The server 120 is configured to acquire a wide-area wind-velocity map providing wind forecast indicating estimates of future wind speed and direction at reference geographic locations for future travel on a pre-selected route. The server then determines ground wind speed and ground wind direction corresponding to future route geographic location from the wide-area wind map. FIG. 49 illustrates an example 4900 dosimetry-based route selection for a planned journey from a starting location 4910 to a destination 4920. A set of alternate routes 4930 is determined using any of known algorithms, or acquired from an external source. A forecast of ground wind velocities 4940 within the traversed region may be acquired from external sources based on knowledge of coordinates of reference points within the traversed region. Using the ground wind velocities, the route-dictated travel directions, the relative wind velocities along different segments of the candidate routes can be calculated at the helmet controller 116 and corresponding SPL values can be determined using the SPL-speed function 3150 which is stored in each helmet.

[0449] FIG. 50 is a flow chart 5000 of an algorithm for dosimetry-guided route selection. Process 5010 acquires at least two routes for the intended journey. Process 5020 sorts the routes according to a criterion of interest such as distance or estimated travel time. Process 5030 determines a “cost” of each candidate route according to the steps:

[0450] (a) Acquire expected wind velocity (speed and direction 0) along segments of the route according to an acquired wind map;

[0451] (b) Measure SPL along each segment;

[0452] (c) Determine a weighted-time-average of SPL exposure along the entire route;

[0453] (d) Determine a composite cost of the route as a weighted cost function of distance, travel-time, and SPL exposure (perhaps giving more weight to the latter).

[0454] In the methods described above, an instantaneous ground wind speed is characterized normally as a probability density function, and thus meteorological wind speeds are reported as the average of some time period usually between 2 and 10 minutes. Therefore, in the methods for computing wind speed, averages of the constituent measurements may need to be used for calculations.

[0455] It is also understood that, in addition to the motorcycle helmet, methods and systems of the present invention may be also applicable to other helmets and other vehicles similar to the motorcycle, or other vehicles where SPL versus speed relationship is determined and used similar to the present invention.

[0456] It should be noted that methods and systems of the embodiments of the invention and data sets described above are not, in any sense, abstract or intangible. Instead, the data is necessarily presented in a digital form and stored in a physical data-storage computer-readable medium, such as an electronic memory, mass-storage device, or other physical, tangible, datastorage device and medium. It should also be noted that the currently described data-processing and data-storage methods cannot be carried out manually by a human analyst, because of the complexity and vast numbers of intermediate results generated for processing and analysis of even quite modest amounts of data. Instead, the methods described herein are necessarily carried out by electronic computing systems having processors on electronically or magnetically stored data, with the results of the data processing and data analysis digitally stored in one or more tangible, physical, data-storage devices and media.

[0457] Methods and systems of the present invention have tangible and practical advantages, providing dosimetry-guided motorcycle speed regulation for motorcycle usage.

[0458] Systems and apparatus of the embodiments of the invention may be implemented as any of a variety of suitable circuitry, such as one or more microprocessors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), discrete logic, software, hardware, firmware or any combinations thereof. When modules of the systems of the embodiments of the invention are implemented partially or entirely in software, the modules contain a memory device for storing software instructions in a suitable, non-transitory computer-readable storage medium, and software instructions are executed in hardware using one or more processors to perform the techniques of this application.

[0459] Although specific embodiments of the invention have been described in detail, it should be understood that the described embodiments are intended to be illustrative and not restrictive. Various changes and modifications of the embodiments shown in the drawings and described in the specification may be made within the scope of the following claims without departing from the scope of the invention in its broader aspect.

Claims

CLAIMS:

1. A method for ensuring hearing protection for a motorcycle rider, the method comprising:(a) obtaining a quantitative relationship of sound-pressure level (SPL) within a helmet to effective wind speed relative to said helmet, said helmet being equipped with a helmet controller and instruments for measuring SPL, travel speed, and travel direction;(b) during each journey with said motorcycle rider wearing the helmet, said helmet controller continually recording successively measured tuples of said SPL, travel speed, and travel direction, and performing processes of:(bl) determining a permissible SPL exposure based on rider-specific sound-exposure history and approved health guidelines;(b2) deducing a permissible effective wind speed corresponding to said permissible SPL exposure using said quantitative relationship;(b3) determining a current ground wind velocity based on said measured tuples and said quantitative relationship; and(b4) determining a current permissible travel speed from said respective ground wind velocity, said permissible effective wind speed, and a current travel direction; thereby ensuring SPL exposure for the motorcycle rider within health guidelines.

2. The method of claim 1, wherein said obtaining comprises measuring SPL and the travel speed while travelling at different speeds, provided ground wind speed is negligible compared with the travel speed.

3. The method of claim 1, further comprising prior to (a), while making a training journey traversing a closed-curve route maintaining a constant speed, said helmet controller performing processes of: acquiring measurements for a set of tuples of SPL, travel speed, and travel direction for travel directions covering an entire closed-curve route; selecting measured tuples corresponding to travel speeds within predefined speed interval to form a set of selected tuples; interpolating said set of selected tuples to determine values of minimum SPL and maximum SPL, and corresponding travel directions; and determining ground wind direction as the travel direction of the tuple of minimum SPL.

4. The method of claim 3 further comprising: traversing the closed-curve route for a second time at different travel speeds; andcontinuing acquiring measurements of the SPL and travel speed to determine said quantitative relationship, subject to determination that a difference between the maximum SPL and the minimum SPL is below a predefined negligible-wind-effect threshold.

5. The method of claim 3 further comprising, subject to a determination that a difference between the maximum SPL and the minimum SPL exceeds or equals a predefined negligible- wind-effect threshold, and provided the motorcycle rider travels along said closed-curve route again but at different travel speeds, said helmet controller performing processes of: recording further measured tuples of SPL, travel speed, and travel direction; identifying a pair of tuples having SPL values within a predefined SPL interval and a magnitude of travel-speed difference exceeding a predefined speed gap; and determining ground wind speed as a function of said ground wind direction and said pair of tuples.

6. The method of claim 1 wherein the process (b3) comprises said helmet controller performing processes of: selecting two measured tuples where discrepancy of travel speeds exceeds a predefined minimum and discrepancy of travel directions is less than a predefined maximum; determining effective wind speeds corresponding to SPL values of the two measured tuples using said quantitative relationship; determining current ground wind speed based on said effective wind speeds and travel-speed values of the two measured tuples; and determining current ground wind direction from the travel-speed values of the two measured tuples, said effective wind speeds, and said current ground wind speed.

7. The method of claim 1 wherein the process (b3) comprises said helmet controller performing processes of: repeatedly, every predefined span, instructing said rider to stop then resume travelling, and for each span: recording an initial SPL value at an instant when a measured tuple indicates zero travel velocity and determining a corresponding ground wind speed from the quantitative relationship; recording a current SPL and travel speed; determining a current effective wind speed corresponding to said current SPL; and determining a ground wind direction based on said ground wind speed, said effective wind speed, and said travel speed.

8. The method of claim 1 further comprising said helmet controller communicating said current permissible travel speed to said motorcycle rider.

9. The method of claim 1 wherein said instruments comprise: a Global Positioning System (GPS) receiver for measuring travel speed and travel direction; a calibrated transducer sensing sound pressure and producing a respective electrical signal; a sampler for producing a succession of samples of the respective electrical signal at a predefined rate sufficient to identify sound-pressure peaks; and a digital filter for frequency-weighting said succession of samples.

10. The method of claim 1 further comprising: during said each journey, retaining magnitudes and duration for SPL values exceeding a predefined threshold for updating said rider-specific sound-exposure history.

11. The method of claim 1 further comprising said helmet controller establishing a connection, through a network, to a server for: sending a helmet-type identifier of said helmet together with a representation of said quantitative relationship to a server; following said each journey, sending an identifier of a respective rider and data relevant to magnitudes and duration for SPL values exceeding a predefined threshold; receiving long-term SPL -exposure data of said respective rider; and receiving forecast wind-velocity at specified latitude-longitude reference points for use in route planning.

12. The method of claim 1 further comprising said helmet controller performing processes of: acquiring at least two candidate routes for a journey; sorting said candidate routes according to one of distance and travel time; for each candidate route: acquiring forecast wind velocities along route segments; determining an effective wind velocity along each route segment; determining an SPL corresponding to said effective wind velocity using said quantitative relationship; determining duration-weighted average SPL along said each candidate route; and determining a composite cost of said each candidate route as a function of distance, travel time, and SPL exposure; and selecting a candidate route according to said composite cost.

13. A system for ensuring hearing protection for a community of motorcycle riders comprising: a server communicatively coupled to a plurality of helmets, each helmet equipped with a respective helmet controller and instruments for measuring sound-pressure level (SPL), travel speed, and travel direction, said respective helmet controller configured to: obtain a quantitative relationship of sound-pressure level (SPL) within said each helmet to effective wind speed relative to said each helmet; and during each journey of a rider wearing said each helmet: continually record successive measured tuples of SPL, travel speed, and travel direction; report values and durations of SPL exceeding a prescribed level to said server; determine a permissible SPL exposure based on rider-specific sound-exposure history and approved health guidelines; deduce a permissible effective wind speed corresponding to said permissible SPL exposure using said quantitative relationship; compute a current ground wind velocity based on said measured tuples and said quantitative relationship; and determine a current permissible travel speed from said respective ground wind velocity, said permissible effective wind speed, and a current travel direction.

14. The system of claim 13 wherein said server is further configured to: receive a helmet-type identifier of said each helmet together with corresponding quantitative- relationship data; and for each helmet type: filter quantitative-relationship data received from multiple helmets to exclude possible outliers and produce a refined quantitative relationship of SPL to effective wind speed; and disseminate said refined quantitative relationships to helmet controllers of helmets of said each helmet type.

15. The system of claim 13 wherein said server is further configured to: receive an identifier of a particular rider, and data measured during said each journey, using said each helmet, relevant to magnitudes and duration of SPL values exceeding a predefined threshold; and wherein said particular rider is a client of said sever, determine a respective long-term SPL- exposure data.

16. The system of claim 13 wherein said respective helmet controller is configured to:acquire measurements for a set of tuples of SPL, travel speed, and travel direction for travel directions covering an entire closed-curve route while a respective rider attempts to maintain a constant speed; select measured tuples corresponding to travel speeds within a predefined speed interval to form a set of selected tuples; apply an interpolating function to said set of selected tuples to determine values of minimum SPL and maximum SPL, and corresponding travel directions; and determine ground wind direction as the travel direction of the tuple of minimum SPL.

17. The system of claim 16 wherein said helmet controller is further configured to: record further measured tuples of SPL, travel speed, and travel direction while a respective rider travels along said closed-curve route again at different travel speeds; identify a pair of tuples having SPL values within a predefined SPL interval and a magnitude of travel-speed difference exceeding a predefined speed gap; and determine ground wind speed as a function of said ground wind direction and said pair of tuples.

18. The system of claim 13 wherein said respective helmet controller is further configured to: select two measured tuples where discrepancy of travel speeds exceeds a predefined minimum and discrepancy of travel directions is less than a predefined maximum; determine effective wind speeds corresponding to SPL values of the two measured tuples using said quantitative relationship; determine current ground wind speed based on said effective wind speeds and travel-speed values of the two measured tuples; and determining current ground wind direction from the travel-speed values of the two measured tuples, said effective wind speeds, and said current ground wind speed.

19. The system of claim 13 wherein said helmet controller is further configured to communicate said current permissible travel speed to said rider.

20. The system of claim 13 wherein said server is further configured to acquire a wide-area wind-velocity map indicating estimates of wind speed and direction at reference geographic locations.

21. The system of claim 20 wherein said server is further configured to: determine On-Off activity state of said each helmet of said plurality of helmets based on receiving indications of helmet utilization, helmet type, current-rider identifier, current geographic location, and current travel direction from a helmet controller of said each helmet;determine ground wind speed and ground wind direction corresponding to said current geographic location from the wide-area wind map; determine a current permissible travel speed according to: sound-exposure history of said current rider and approved health guidelines; quantitative relationship of SPL to effective wind speed specific to said each helmet; said ground wind speed and ground wind direction; and said current travel direction; and communicate the current permissible travel speed to said helmet controller of said each helmet.

22. The system of claim 13 wherein said server is further configured to acquire a wide-area wind-velocity map providing wind forecast indicating estimates of future wind speed and direction at reference geographic locations for future travel on a pre-selected route.

23. The system of claim 22 wherein said server is further configured to: determine ground wind speed and ground wind direction corresponding to said future route geographic location from the wide-area wind map; determine a current permissible travel speed according to: sound-exposure history of said current rider and approved health guidelines; quantitative relationship of SPL to effective wind speed specific to said each helmet; said ground wind speed and ground wind direction; and said future travel direction; and communicate the current permissible travel speed to said helmet controller of said each helmet.

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