Moisture estimate

Abstract

A system comprising a computer with a processor and memory, wherein the memory stores instructions executable by the computer to: to determine that a first time required for a first noise produced by a vehicle to reach a first maximum noise amplitude, and a second time required for a second noise produced by the vehicle to reach a second maximum noise amplitude, lie within a time range, to determine that the second sound is a reflection of the first sound; to identify the presence of an object reflecting the first sound within a distance range of the vehicle, based on a time interval between the reception of the first and the second sound; to determine the speed of sound, at least in part, based on the time interval and a distance to the object; to determine humidity at least partially based on the speed of sound; and to adjust a vehicle subsystem based on humidity.

Description

STATE OF THE ART

[0001] Ambient humidity can affect various vehicle components. Directly measuring humidity typically requires a dedicated humidity sensor, which can be expensive.

[0002] DE 10 2012 200 230 A1 describes a method for detecting the surroundings of a vehicle. In this method, changes in an acoustic signal due to temperature differences are detected, and the changes in the signal are used to create a model of the climate situation in the vehicle's surroundings, from which the wind strength, wind direction, and changes in the propagation properties of the acoustic signal can be derived. DE 10 2005 038 599 A1 describes an ultrasonic measuring unit with integrated humidity detection. In a flow tube with ambient air, a temperature sensor is provided around which the measured value is used to correct a temperature signal detected by ultrasound. US 2009 / 0 260 422 A1 presents an ultrasonic sensor for detecting an object, which has a transmitting device with a first piezoelectric element for transmitting an ultrasonic wave to the object.A receiving device with a second piezoelectric element receives the ultrasonic wave reflected from the object and generates an output voltage corresponding to the detected ultrasonic wave. US 2016 / 0 299 014 A1 describes an acoustic detection of ambient temperature and humidity based on determining the speed of sound based on the time of flight of a coded acoustic signal and based on the resonance frequency of a Helmholtz resonator. DE 101 43 841 A1 describes an oven that has a temperature sensor and a humidity sensor and, in conjunction with a timer and an acoustic transmitter and receiver, monitors the water vapor content in the oven based on the speed of sound at the density of the air inside.DE 10 2004 038 496 A1 describes a method for measuring the distance of an obstacle located in the vicinity of a motor vehicle by means of an echo method, wherein data characterizing the environmental conditions of the motor vehicle are measured and the relative relationship between the distance-dependent echo amplitude and a threshold value determining the detection of the received echo signal is adapted to the measured environmental conditions. BRIEF DESCRIPTION OF THE DRAWINGS Fig. 1 is a block diagram of a vehicle system for estimating humidity. Fig. Figure 2 is an exemplary illustration of a vehicle incorporating the system Fig. 1 and uses an object for moisture estimation. Fig. Figure 3 is an example process for determining a humidity value based on a measured speed of sound in the air. Fig. 4 is another exemplary process for determining a humidity value based on a measured speed of sound in the air. DETAILED DESCRIPTION

[0003] Estimating ambient humidity based on a measured speed of sound provides a cost-effective way to adjust humidity-dependent vehicle subsystems. A microphone can record a sound from a vehicle tire hitting an uneven part of a road, such as a rumble strip, a pothole, etc. The microphone can then record a reflection of the sound from a nearby object, such as a traffic sign, a streetlight, a telephone pole, etc. The vehicle can determine the time difference, or propagation time, between receiving the sound and its reflection. A radar can determine the distance from the vehicle to the object. Based on the propagation time and the distance from the vehicle to the object, the vehicle can determine a speed of sound, or the speed at which acoustic waves propagate in the ambient air at the ambient humidity.Because the speed of sound in air is known to be a function of ambient humidity, the vehicle can determine the ambient humidity based on the speed of sound, e.g., by referring to a known psychometric chart. Based on this estimated humidity, vehicle subsystems can be adjusted; for example, a climate control system can adjust a dehumidifier based on the estimated humidity.

[0004] Fig. 1 illustrates an example system 100 for estimating ambient humidity and adjusting a vehicle subsystem based on the estimated humidity. A computing device 105 is programmed to receive collected data 115 from one or more data collectors 110, e.g., from sensors of the vehicle 101, regarding various measurements related to the vehicle 101. For example, the measurements may include a speed of the vehicle 101, acceleration and / or deceleration of the vehicle 101, data related to the trajectory or steering of the vehicle 101, etc., including lateral acceleration, curving road trajectory, distance to an object, noise from a vehicle tire during a crash event, etc. Other examples of such measurements may include measurements from systems and components of the vehicle 101 (e.g.,a steering system, a powertrain system, a braking system, internal sensing, external sensing). The computing device 105 may be programmed to collect data 115 from the vehicle 101 in which it is installed, sometimes referred to as a "host vehicle," and / or it may be programmed to collect data 115 about and / or from a second vehicle different from the vehicle 101, e.g., a "target vehicle," e.g., via DSRC communication or the like. Additionally, it is possible for the computer 105 to receive data from a remote server, e.g., via a cellular or other wireless network.

[0005] Computing device 105 is generally programmed to communicate on a Controller Area Network (CAN) bus or the like. Computing device 105 may also include a connection to an on-board diagnostics (OBD-II) connector. Via the CAN bus, OBD-II, and / or other wired or wireless mechanisms, computing device 105 may transmit messages to various devices within a vehicle and / or receive messages from the various devices, e.g., from controllers, actuators, sensors, etc., including data collectors 110. In cases where computing device 105 actually comprises multiple devices, the CAN bus or the like may alternatively or additionally be used for communications between devices, which are represented in this disclosure as computing device 105.Additionally, the computing device 105 may be programmed to communicate with the network 120, which, as described below, may include various wired and / or wireless network technologies, such as cellular, Bluetooth, wired and / or wireless data packet networks, etc.

[0006] Data storage 106 may be of any known type, e.g., hard disk drives, solid-state drives, servers, or any volatile or non-volatile media. Data storage 106 may store the collected data 115 sent by data collectors 110.

[0007] The vehicle 101 may include multiple subsystems 107. Examples of subsystems 107 include a propulsion subsystem (e.g., throttle), an entertainment subsystem, a steering subsystem, an ignition timing subsystem, a climate control subsystem, etc. The subsystems 107 may be electronic control units (ECUs), as known, that control various components of the vehicle 101. For example, the ignition timing subsystem may be an engine control unit that may receive instructions to adjust the ignition timing based on the estimated humidity.

[0008] Data collectors 110 may include a variety of devices. For example, various controllers within a vehicle may operate as data collectors 110 to provide data 115 via the CAN bus, e.g., data 115 related to vehicle speed, acceleration, system and / or component functionality, etc., from any number of vehicles 101, including the host vehicle and / or the target vehicle. Furthermore, sensors or the like, Global Positioning System (GPS) equipment, etc., may be included within a vehicle and configured as data collectors 110 to provide data directly to computer 105, e.g., via a wired or wireless connection. Sensor data collectors 110 may include mechanisms such as radar, lidar, sonar, sensors that could be employed to determine environmental data, e.g.,to measure a distance between the vehicle 101 and other vehicles or objects, the types of objects near the trajectory of the vehicle 101, road conditions, the location of roads and traffic signs, etc. Still other data collectors 110 could include cameras, breathalyzers, motion detectors, etc., i.e., data collectors 110 to provide data 115 for evaluating a condition or state of a user of the vehicle 101.

[0009] Collected data 115 may include a variety of data collected in a vehicle 101. Examples of collected data 115 are provided above, and in addition, data 115 is generally collected using one or more data collectors 110 and may additionally include data calculated therefrom in computer 105. In general, collected data 115 may include any data accumulated by and / or calculated from data collectors 110. Data 115 may include biometric data of the human user, such as heart rate, blood pressure, respiratory rate, etc.

[0010] Fig. Figure 2 illustrates vehicle 101. Vehicle 101 may include a radar 111 and a microphone 112. Radar 111 is a data collector 110, as is known, that transmits and receives radio waves to determine a distance of an object. Microphone 112 is a data collector 110, as is known, that detects acoustic waves, i.e., sounds. Although vehicle 101 includes radar 111 and microphone 112 in this example, vehicle 101 may include any number and / or type of data collectors 110 necessary to determine the estimated humidity.

[0011] The vehicle 101 may include a tire 150. The tire 150 may contact a road, generating a noise. For example, on a smooth road, the tire 150 may only generate a steady, low-amplitude noise. In another example, when the tire 150 hits a pothole, the tire 150 may generate a short, high-amplitude noise. In yet another example, when the tire 150 rolls over rumble strips, the tire 150 may generate a periodic, rattling noise.

[0012] Fig. 2 further illustrates an object 160. The object 160 reflects the noise generated by the tire 150 back to the vehicle 101, where the noise is received by the microphone 112. The radar 111 can detect multiple objects 160, including a distance from the vehicle 101 to the objects 160. The object 160 can be, for example, a traffic sign, a telephone pole, a streetlight, etc.

[0013] The radar 111 can determine the location of the multiple vehicle components and objects and the distance between the components and the objects. As shown in Fig. 2, the radar 111 can determine a distance D0 from the radar 111 to a nearby object 160. Similarly, the radar 111 can determine a distance D1 from the tire 150 to the object 160, the distance D2 from the object 160 to the microphone 112, and the distance D3 from the tire 150 to the microphone 112. The distances D0, D1, D2, D3 can represent the path a sound can travel through the ambient air, i.e., a trajectory for a sound traveling between the tire 150, the object 160, the radar 111, and the microphone 112.

[0014] Fig. 3 illustrates a process 300 for actuating a vehicle subsystem 107 based on estimated humidity. The process 300 begins at a block 310 where a microphone 112 collects a first sound from the vehicle tire 150. Here, the first sound is a set of acoustic waves reaching the microphone 112 that are generated by the vehicle tire 150 interacting with the road. The first sound may come from a vehicle tire 150 contacting, for example, an uneven patch of road, a pothole, a rumble strip, etc. The microphone 112 (i.e., a processor included therein) may be programmed to detect sounds that include acoustic waves at frequencies known to be included in sounds generated by the vehicle tire 150 and to identify the first sound according to a set of acoustic waves received in the range of the known frequencies.

[0015] Next, in a block 315, the microphone 112 collects a second sound reflected from an object 160. Here, the second sound is a next set of acoustic waves received by the microphone 112 after receiving the first sound, as described above. The microphone 112 may detect multiple sounds after detecting the first sound and may determine the second sound as the next sound received by the microphone 112 according to the range of known frequencies of sounds generated by the vehicle tire 150, as described above. The second sound may be the reflection of the first sound by the object 12 in the vicinity of the vehicle 101. The computing device determines a time interval between the reception of the first sound and the reception of the second sound, wherein the time interval has a travel time t ffor the second sound to travel from the tire 150, be reflected from the object 160, and return to the microphone 112. The travel time may be determined as the time difference between the reception of the first and second sounds, or it may include an estimated travel time of the first sound from the tire 150 to the microphone 112 over the distance D3.

[0016] Next, in a block 320, the computing device 105 compares the first sound with the second sound and determines whether the two sounds match, i.e., whether the second sound is a reflection of the first sound off an object. The first sound has a characteristic rise time, i.e., the time until the first sound reaches its maximum amplitude, which is substantially unique to the first sound because the characteristic rise time is a result of at least some of the following factors: the pressure of the tire 150, the wheel size, the size of the obstacle impacting the tire 150 that produced the first sound, the spring constant of the suspension of the vehicle 101, and / or the condition and mass of the shock absorber state of the vehicle 101. The characteristic rise time may be measured by the data collectors 110 in a known manner, e.g., by measuring peak values ​​of the amplitude, i.e.,local maxima of the amplitude of a sound over time, and the timestamp of these peak values, comparing a fast Fourier transform (FFT) over the length of several cycles in an audible frequency range, e.g., 20 Hz - 20 kHz, etc. If the characteristic rise time of the first sound is within a predetermined range of the characteristic rise time of the second sound, then the computing device 105 determines that the first sound matches the second sound. The predetermined range is a range of values ​​of the characteristic rise time that the computing device 105 compares to the difference in rise times between the first sound and the second sound. If the first and second sounds are within the range, then the computing device 105 determines that the first sound matches the second sound.That is, the computing device 105 determines that the second sound is the first sound reflected from the object 160. If the first and second sounds match, the process 300 continues to a block 325; otherwise, the process 300 ends. The computing device 105 may also be programmed to detect specific sounds, such as the sound of the tire 150 hitting rumble strips or a pothole.

[0017] In block 325, the computing device 105 searches for objects 160 within a distance range of the vehicle 101. The distance range can be determined by considering the time interval between the reception of the first and second sounds and estimating a speed of sound based on an ambient temperature, with a lower limit of the distance range based on the speed of sound without humidity and an upper limit for the distance range based on maximum humidity. The time interval indicates a travel time for the second sound to travel from the tire 150 to the vehicle 101 under reflection from the object 160. Because the speed of sound is greater when the humidity is higher, i.e.is closer to the maximum humidity at a given temperature, a higher humidity at a given time interval would result in a farther away object 160 reflecting the second sound than the object 160 would be at a lower humidity. Because the humidity is restricted to a known range at a given ambient temperature, the possible distance range that the object 160 can be at can be determined based on the known humidity range, the ambient temperature, and the time period. For example, if the ambient temperature is 20°C, the speed of sound in air is 343.4 meters per second (m / s) at 0% humidity and 344.6 m / s at 90% humidity. The speed of sound without humidity, v. s,dry , and the speed of sound at maximum humidity, v s,wet, are known for a given temperature. With these speeds of sound and the travel time t f the distance range can be determined as follows: Distance range=[vs,dry⋅tf,vs,wet⋅tf]

[0018] Radar 111 can search for objects within this distance range of vehicle 101 that could reflect the second sound back to vehicle 101. Such objects 160 can include, for example, traffic signs, telephone poles, streetlights, etc. Radar 111 stores data, such as estimated positions and dimensions, of objects 160 in the distance range and stores them in data storage 106.

[0019] Next, in block 330, the computing device 105 determines whether exactly one object 160 is present in the distance range. If multiple objects 160 are present in the distance range, then multiple humidity values ​​may be determined based on the distance of the objects 160 from the vehicle 101. Corresponding vehicle subsystems 107 may be adjusted differently based on different estimated humidity values, so a single estimated humidity value may be desirable. Thus, the process 300 only continues if exactly one object 160 is present in the distance range and thus an estimated humidity value is present. If exactly one object 160 is present in the distance range, the process 300 continues in a block 335; otherwise, the process 300 ends.

[0020] In block 335, the computing device 105 estimates the humidity based on the distance of the object 160 from the vehicle 101, the ambient temperature, and the travel time of the second sound. The speed of sound in air is at least partially a function of ambient temperature and humidity, as is known. A speed of sound can be measured based on the travel time of the second sound and the distance to the object 160. For example, as shown in Fig. 2, the distance D1 represents a distance from the tire 150 to the object 160, and the distance D0 represents a distance from the object 160 to the radar 111, wherein the distances D0, D1 are detected, for example, by the radar 111. Although the example of Fig. Figure 2 illustrates that the distances D0, D1, D2, D3 are aligned in a plane. The distances can be determined in a 3-dimensional space, and thus the distances can be represented as vectors, as is known. As described above, the distance D2 represents the distance from the object 160 to the microphone 112. Because the distance between the radar 111 and the microphone 112 is known, the distance D2 is simply the vector representing the distance from the object 160 to the radar 111, D0 added to the vector representing the distance from the radar 111 to the microphone 112, using known vector addition techniques. The travel time t f of the second sound can be determined by the time interval between the reception of the first sound and the reception of the second sound, as described above. Thus, the speed of sound v s estimated as follows: vs=D1+D2tf

[0021] Using the speed of sound and the measured ambient temperature, the adiabatic constant of the ambient air can be determined as follows: vs=γRT where γ is the adiabatic constant of air (also known as the ratio of specific heat capacities), R is the universal gas constant, and T is the ambient temperature. The adiabatic constant γ is, as is known, a function of humidity, and thus the estimated humidity can be determined based on the adiabatic constant, which can be found, for example, in a psychometric diagram stored in data memory 106.

[0022] The computing device 105 may determine the estimated humidity using known psychometric equations for the speed of sound.

[0023] For example, the speed of sound in air without moisture can be v s,dry and in air with maximum humidity v s,wetbe defined as follows: vs,drγ=γdry⋅Pρdrγ vs,wet=γwet⋅Pρwet where γ dry, γ wet , as is known, are the adiabatic constants for air without moisture and at maximum humidity, respectively, P is the absolute pressure measured by a data collector 110, and ρ dry , ρ wet , as is well known, are the densities of air without moisture and at maximum humidity, respectively. The adiabatic constants and densities are generally functions of humidity.

[0024] Using the sound speeds without moisture, at maximum moisture and based on the second noise, an absolute moisture ratio AHR such as folate can be determined: AHR=vs,wet−vs(vs,wet−vs,dry)2 Using the absolute humidity ratio (AHR) and the measured ambient temperature, the estimated humidity can be determined using a psychometric chart, as is known. The psychometric chart can be stored in data memory 106, as mentioned above.

[0025] Next, in a block 340, computing device 105 sends instructions to adjust vehicle subsystems 107 based on the estimated humidity, and process 300 ends. For example, an ignition timing subsystem 107 may receive an instruction to retard ignition timing based on a higher estimated humidity. In another example, a climate control subsystem 107 may receive an instruction to adjust operation of a dehumidifier, a heater, and / or an air conditioner based on the estimated humidity. In yet another example, climate control subsystem 107 may adjust a windshield defroster based on the humidity. In another example, a fuel injection subsystem 107 may adjust an air-fuel ratio of an intake charge to the engine cylinders.

[0026] Fig.4 illustrates an example process 400 for actuating a vehicle subsystem 107 based on estimated humidity. The process 400 begins at a block 410 where the computing device 105 receives a start message from a vehicle suspension subsystem 107. The start message may be, for example, an instruction and / or a signal sent from the suspension subsystem 107 to the computing device 105 to, for example, actuate the microphone 112 to receive an incoming sound generated by the tire impacting a portion of the road. The start message indicates that the vehicle suspension subsystem 107 has encountered an event on the road, such as a bump. B. a pothole, a rumble strip, an uneven patch, etc. Instead of receiving an initial sound, as in process 300, process 400 starts when tire 150 experiences the event and vehicle suspension subsystem 107 sends the message to computing device 105.

[0027] Next, in a block 415, the microphone 112 receives a sound. The sound is typically similar to the second sound of process 300, i.e., it is the sound coming from the tire 150, reflected from an object 160 to the vehicle 101. The computing device 105 may be programmed to detect specific sounds, such as the sound of the tire 150 hitting rumble strips or a pothole. The computing device 105 determines a time interval between receiving the start message and receiving the sound, where the time interval indicates the propagation time of the sound.

[0028] Next, in a block 420, the radar 111 detects objects within a distance range of the vehicle 101. As in process 300, the distance range is determined based on the time interval, the distance to the object 160, the ambient temperature, and the speeds of sound based on no humidity and the maximum humidity at the ambient temperature.

[0029] Next, in a block 425, the computing device 105 determines whether exactly one object 160 is present in the distance range. If multiple objects 160 are present in the distance range, then, as described above, multiple humidity values ​​may be estimated based on the distance of the objects 160 from the vehicle 101. If exactly one object 160 is present in the distance range, the process 400 continues to a block 430; otherwise, the process 400 ends. The process 400 may alternatively continue to block 430 if multiple objects 160 are detected but are all within the predetermined distance threshold of each other. The process 400 may also alternatively continue to block 430 if the computing device 105, having detected multiple objects 160, selects one of the objects in a known manner.

[0030] At block 430, computing device 105 estimates the humidity based on the distance of object 160 from vehicle 101, the ambient temperature, and the travel time of the second sound. As described for block 335 of process 300, computing device 105 uses the ambient temperature, the travel time, the distance of object 160, and the psychometric chart stored in data storage 106 to determine the estimated humidity.

[0031] Next, at a block 435, computing device 105 sends instructions to adjust vehicle subsystems 107 based on the estimated humidity, and process 400 ends. For example, an ignition timing subsystem 107 may receive an instruction to retard ignition timing based on a higher estimated humidity. In another example, a climate control subsystem 107 may receive an instruction to adjust the operation of a dehumidifier based on the estimated humidity.

[0032] In the present usage, the adverb "substantially" modifying an adjective means that a shape, structure, measurement, value, calculation, etc. may vary from an accurately described geometry, distance, measurement, value, calculation, etc. due to imperfections in materials, machining, manufacturing, sensor measurements, calculations, processing time, communication time, etc.

[0033] Computing devices 105 generally each include instructions executable by one or more computing devices, such as those identified above, and for performing blocks or steps of processes described above. Computer-executable instructions may be compiled or interpreted by computer programs generated using a variety of programming languages ​​and / or technologies, including, without limitation, and either alone or in combination, Java™, C, C++, Visual Basic, Java Script, Perl, HTML, etc. In general, a processor (e.g., a microprocessor) receives instructions, for example, from memory, a computer-readable medium, etc., and executes those instructions, thereby performing one or more processes, including one or more of the processes described herein.Such instructions and other data may be stored and transmitted using a variety of computer-readable media. A file in computing device 105 is generally a collection of data stored on a computer-readable medium, such as a storage medium, random access memory, etc.

[0034] A computer-readable medium includes any medium involved in providing data (e.g., instructions) that can be read by a computer. Such a medium can take many forms, including, but not limited to, non-volatile media, volatile media, and so on. Examples of non-volatile media include optical or magnetic disks and other permanent storage. Volatile media includes dynamic random access memory (DRAM), which typically forms main memory. Common forms of computer-readable media include, for example, a floppy disk, a diskette, a hard disk, magnetic tape, any other magnetic medium, a CD-ROM, a DVD, any other optical medium, punched cards, punched tape, any other physical medium with hole patterns, a RAM, a PROM, an EPROM, a flash EEPROM, any other memory chip or cartridge, or any other medium from which a computer can read.

[0035] With respect to the media, processes, systems, methods, etc. described herein, it is understood that although the steps of such processes, etc., have been described as occurring according to a certain ordered sequence, such processes could be implemented such that the described steps are performed in a different order than that described herein. It is further understood that certain steps could be performed concurrently, that other steps could be added, or that certain steps described herein could be omitted. For example, one or more steps in process 200 could be omitted, or the steps could be performed in a different order.In other words, the present descriptions of systems and / or processes are provided for the purpose of illustrating particular embodiments and should not be construed in any way as limiting the disclosed subject matter.

[0036] Accordingly, it is to be understood that the present disclosure, including the above description and the associated figures and the following claims, is intended to be illustrative, not limiting. Many embodiments and applications other than the examples provided will become apparent to those skilled in the art upon review of the above description. The scope of the invention should not be determined with reference to the above description, but should instead be determined with reference to the claims appended hereto and / or included in a final patent application based hereon, along with the full scope of equivalents to which such claims are entitled. It is anticipated and intended that future developments will occur in the art discussed herein and that the disclosed systems and methods will be incorporated into such future embodiments.In summary, it is understood that the disclosed subject matter may be modified and altered.

Claims

[1] System comprising a computer having a processor and a memory, the memory storing computer-executable instructions to: to determine that a first time required for a first noise generated by a vehicle to reach a first maximum noise amplitude and a second time required for a second noise generated by the vehicle to reach a second maximum noise amplitude are within a time range, to determine that the second sound is a reflection of the first sound; to identify a presence of an object reflecting the first sound within a distance range of the vehicle based on a time interval between the receipt of the first and second sounds; to determine a speed of sound based at least in part on the time interval and a distance to the object; to determine humidity at least partly based on the speed of sound; and adjust a vehicle subsystem based on humidity. [2] The system of claim 1, wherein the instructions further include instructions to identify objects within a range of distances from the vehicle determined based on an ambient temperature and speeds of sound in the absence of humidity and at maximum humidity. [3] The system of claim 1 or claim 2, wherein the instructions further include instructions to identify the object with a radar. [4] The system of any one of claims 1 to 3, wherein the vehicle subsystem is a climate control subsystem. [5] The system of claim 1, wherein the instructions further include instructions to identify exactly one object and to determine the humidity only when exactly one object is identified. [6] The system of any one of claims 1 to 5, wherein the instructions include instructions to receive the first sound from a vehicle tire. [7] The system of any one of claims 1 to 6, wherein the instructions include instructions to send an instruction to an ignition timing subsystem to adjust ignition timing based on humidity. [8] Procedure comprising: Determining that a first time required for a first vehicle-generated sound to reach a first maximum sound amplitude and a second time required for a second vehicle-generated sound to reach a second maximum sound amplitude are within a time range to determine that the second sound is a reflection of the first sound; identifying a presence of an object reflecting the first sound within a distance range of the vehicle based on a time interval between receiving the first and second sounds; determining a speed of sound based at least in part on the time interval and a distance to the object; Determining a humidity based at least in part on the speed of sound; and Adjusting a vehicle subsystem based on humidity. [9] The method of claim 8, further comprising identifying objects within a distance range from the vehicle, the distance range being determined based on an ambient temperature and sound speeds in the absence of humidity and at maximum humidity. [10] The method of claim 8, further comprising identifying exactly one object and determining the humidity only when exactly one object is identified. [11] A method according to any one of claims 8 to 10, wherein the vehicle subsystem is a climate control subsystem. [12] The method of any one of claims 8 to 11, further comprising adjusting ignition timing with an ignition timing subsystem based on humidity. [13] A method according to any one of claims 8 to 12, further comprising identifying the object with a radar.

Images