On-site calibration of vehicle sensors using other vehicles

Abstract

Field calibration of vehicle sensors using other vehicles is provided. A system and method are provided for determining whether field calibration of subject sensors associated with a vehicle is necessary, and when calibration is necessary, calibrating the subject sensors using sensors associated with another vehicle. The reference vehicle may perform predetermined maneuvers to provide additional measurements used during calibration.

Description

Technical Field

[0001] The present disclosure relates to calibration of vehicle sensors that facilitate a driver assistance system or autonomous driving mode of an associated vehicle. Background Art

[0002] A driver assistance system in a vehicle may be able to provide assistance to the driver by performing driving functions associated with driving or maneuvering the vehicle. Driver assistance functions may include specific maneuvers, such as parallel parking or brake assistance. Some driver assistance functions may include autonomous vehicle operation, also known as self-driving. Self-driving vehicles and vehicles with other driver assistance functions require environmental perception sensors, such as radar, lidar, cameras, or ultrasonic sensors. In determining the function of the vehicle, other sensors may be helpful, such as steering angle sensors, wheel speed sensors, or yaw rate sensors. All of these sensors require calibration for precise operation.

[0003] Calibration of sensors can occur in a controlled environment such as an assembly plant or a specialized workshop. However, most sensors are designated for calibration over time to accommodate gradual miscalibration during normal operation or other causes of miscalibration. Bringing the associated vehicle to a specialized facility for sensor recalibration may be inconvenient, expensive, or time consuming. Summary of the invention

[0004] One aspect of the present disclosure relates to a system for online calibration of a vehicle sensor, the system comprising a processor, a body sensor for calibration, and a plurality of position sensors operable to provide reference measurements for sensor calibration. The body sensor may be associated with a vehicle, and the position sensor may be associated with a plurality of vehicles. The calibration may be coordinated by a processor in data communication with the body sensor and the position sensor. In some embodiments, one or more of the vehicles associated with the position sensor may be operable to perform a predetermined maneuver to provide a plurality of reference measurements for calibration.

[0005] Another aspect of the present disclosure relates to a system that includes a first vehicle processor in data communication with a subject sensor. The first vehicle processor is operable to communicate with at least one other vehicle processor associated with a vehicle other than the first vehicle. Each of the other vehicles having a vehicle processor may include a position sensor to be utilized to provide a reference measurement during calibration of the subject sensor.

[0006] Additional aspects of the present disclosure relate to a method of calibrating a subject sensor associated with a vehicle, the method utilizing one or more position sensors that indicate the position of the subject sensor and one or more other vehicles not associated with the subject sensor to extrapolate expected measurements of the subject sensor during calibration. In some embodiments, one or more of the vehicles associated with the reference sensor may be directed to perform a predetermined maneuver during calibration of the subject sensor. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] Figure 1 is a diagrammatic view of a vehicle including a sensor having field calibration capabilities.

[0008] Figure 2 is a diagrammatic view of a first system operable to perform in-situ calibration of a vehicle sensor.

[0009] Figure 3 is a diagrammatic view of a second system operable to perform in-situ calibration of a vehicle sensor.

[0010] Figure 4 is a diagrammatic view of a system operable to perform predetermined maneuvers during in-situ calibration of vehicle sensors.

[0011] Figure 5 is a flow chart depicting a method for calibrating a vehicle sensor in the field. DETAILED DESCRIPTION

[0012] The illustrated embodiments are disclosed with reference to the accompanying drawings. However, it is to be understood that the disclosed embodiments are intended merely as examples that may be embodied in various and alternative forms. The figures are not necessarily to scale, and some features may be exaggerated or minimized to show details of particular components. The specific structural and functional details disclosed are not to be construed as limiting, but rather as a representative basis for teaching those skilled in the art how to practice the disclosed concepts.

[0013] Figure 1is a diagrammatic illustration of a vehicle 100 having a vehicle processor 101 operable to interact with components and systems of the vehicle. The vehicle processor 101 may be in data communication with a field adjustable sensor 103. The functionality of the vehicle processor 101 may include the ability to collect measurement data from the field adjustable sensor 103 and adjust the calibration settings of the field adjustable sensor 103. In the depicted embodiment, the field adjustable sensor 103 may include a forward facing proximity sensor, but other embodiments may include other configurations or sensor types without departing from the teachings disclosed herein. In some embodiments, the field adjustable sensor 103 may include a radar sensor, a lidar sensor, an external temperature sensor, a proximity sensor, an ultrasonic sensor, a microphone, a camera, an optical sensor, an infrared sensor, an accelerometer, a yaw rate sensor, a wheel speed sensor, a speedometer, a steering angle sensor, or any other sensor known to one of ordinary skill in the art that may be activated and verified during normal operation of the vehicle 100.

[0014] In the depicted embodiment, the vehicle 100 includes one field-adjustable sensor 103, but other embodiments may include multiple field-adjustable sensors 103 without departing from the teachings disclosed herein. In such a multi-sensor embodiment, the multiple field-adjustable sensors 103 may include different types of sensors without departing from the teachings disclosed herein. By way of example and not limitation, the vehicle 100 may include several field-adjustable sensors 103, including wheel speed sensors, yaw rate sensors, steering angle sensors, forward-facing motion sensors, and rear-facing proximity sensors. In some embodiments, the multiple field-adjustable sensors 103 may include redundant or partially redundant sensors without departing from the teachings disclosed herein. By way of example and not limitation, the vehicle 100 may include a rear-facing proximity sensor array and a back-up camera operable to assist the driver in avoiding collisions when backing up. Other embodiments may include alternative configurations of field-adjustable sensors 103 that are all calibrated by the vehicle processor 101 without departing from the teachings disclosed herein.

[0015] The vehicle 100 may also include a position sensor 105 in data communication with the vehicle processor 101. The position sensor 105 may be operable to provide position data to the vehicle processor indicating the position of the vehicle 100 with respect to the surrounding environment. Because the dimensions of the vehicle 100 including the relative position of the field adjustable sensor 103 with respect to the position sensor 105 are known, the position of the field adjustable sensor 103 may also be known. In the depicted embodiment, the position data may include global navigation satellite system (GNSS) coordinate data, but other embodiments may include other configurations without departing from the teachings disclosed herein. In some embodiments, the vehicle 100 may include multiple position sensors 105 without departing from the teachings disclosed herein. In such embodiments, each position sensor 105 may utilize different configurations without departing from the teachings disclosed herein. In some embodiments, a system of position sensors 105 may utilize other data such as densely populated map data and additional environmental sensor data to provide more detailed position measurements without departing from the teachings disclosed herein.

[0016] The vehicle processor 101 may be operable to access data describing the physical dimensions of the vehicle 100 and the placement of the field adjustable sensors 103 and the position sensors 105 within the dimensions of the vehicle 100. Because the vehicle processor 101 has access to such data, the vehicle processor 101 is able to calculate the position of the field adjustable sensors 103 based on the data generated by the position sensors 105. Similarly, the vehicle processor 101 may utilize data describing the physical dimensions of the vehicle 100 to generate data describing the chassis boundaries. Thus, the vehicle 101 may be operable to generate data describing the position of the exterior portions of the vehicle 100.

[0017] The vehicle 100 may also include a wireless transceiver 107 for data communication with the vehicle processor 101. The wireless transceiver 107 may be operable to implement data communication with other processors external to the vehicle 100. In the depicted embodiment, the wireless transceiver 107 is depicted as a single unit operable to both send and receive data communications, but other embodiments may include alternative configurations, such as different transmitters and receivers, without departing from the teachings disclosed herein. The wireless transceiver 107 may utilize a Wi-Fi protocol, a Zigby protocol, a cellular data protocol, a satellite transmission protocol, or any other wireless data communication implementation known to those of ordinary skill in the art without departing from the teachings disclosed herein.

[0018] In the depicted embodiment, the vehicle 100 may be an autonomous vehicle operable to perform functions associated with autonomous driving, but other embodiments may include other configurations without departing from the teachings disclosed herein. Other embodiments may include partially autonomous functions without departing from the teachings disclosed herein. Other embodiments may include advanced driver assistance system (ADAS) functions without departing from the teachings disclosed herein. Other embodiments may include only non-autonomous functions that rely on sensors without departing from the teachings disclosed herein. In some embodiments, the vehicle 100 may be selectively operable to perform in an autonomous mode or a non-autonomous mode without departing from the teachings disclosed herein.

[0019] In the depicted embodiment, vehicle 100 may include a sedan, but other embodiments may include other types of vehicles without departing from the teachings disclosed herein. By way of example and not limitation, vehicle 100 may include a van, a light truck, a multi-axle truck, a minivan, a motorcycle, a scooter, a sport utility vehicle, a crossover vehicle, a side-by-side vehicle, an off-road vehicle, or any other vehicle including a field-adjustable sensor without departing from the teachings disclosed herein.

[0020] Figure 2 1 is a diagrammatic view of a system operable for field calibration of vehicle sensors according to one embodiment of the teachings disclosed herein. In the depicted embodiment, vehicles 100a, 100b, 100c, and 100d may include a configuration of vehicle 100 (see Figure 1 ), but other embodiments may include other configurations without departing from the teachings disclosed herein. In the depicted embodiment, each of the vehicles 100a, 100b, 100c, and 100d may be functionally identical, but other embodiments may include other configurations without departing from the teachings disclosed herein. In the depicted embodiment, vehicle 100a serves as the subject vehicle, but any other vehicle 100 within the system may serve as the subject vehicle for field calibration of associated sensors without departing from the teachings disclosed herein.

[0021] In the depicted embodiment, vehicle 100a acts as a subject vehicle during calibration of field adjustable sensor 103a, and field adjustable sensor 103a acts as a subject sensor in the calibration. Vehicle processor 101a (not shown; see Figure 1) is operable to detect a condition of the vehicle 100 that may necessitate calibration of the field adjustable sensor 103a. Conditions necessitating calibration of the sensor may include routine maintenance related conditions such as a predetermined mileage, a predetermined amount of time since a previous calibration, or a request by a user or technician for the vehicle processor 100a to perform a calibration.

[0022] Without departing from the teachings disclosed herein, other conditions that necessitate calibration may be accidental conditions, such as an unexpected bump or collision, repairs to the vehicle 100a known to affect sensor operation, detection of suboptimal sensor performance, detection of undesirable driving conditions, or any other accidental condition known to one of ordinary skill in the art. By way of example and not limitation, an accidental condition may be determined after repairs to the windshield of the vehicle 100a. By way of example and not limitation, an accidental condition may be determined after an extended period of driving along a particularly bumpy or irregular road surface.

[0023] In the depicted embodiment, field calibration can be coordinated by coordination server 203. Coordination server 203 can communicate wireless data with each of vehicles 100 via server transceiver 205. In the depicted embodiment, server transceiver 205 includes a single transceiver operable to transmit and receive data, but other embodiments may include configurations with separate transmitters and receivers without departing from the teachings disclosed herein. Coordination server 203 can be operable to transmit data or commands to each of vehicles 100. Coordination server 203 can be operable to receive data from each of vehicles 100. In embodiments including partially autonomous or non-autonomous vehicles, coordination server 203 can be operable to provide driving instructions or guidance to users such as drivers or passengers of vehicles. Such driving instructions or guidance can be presented to users via a head-up display, a local display console, or a portable device in the vehicle.

[0024] In the depicted embodiment, the vehicle 100a may report to the coordination server the conditions that necessitate calibration of the field adjustable sensor 103a. In response, the coordination server may identify other vehicles 100 within a predetermined proximity of the vehicle 100a to serve as target vehicles. Once one or more target vehicles have been identified, the coordination server 203 may direct the vehicle 100a to measure the distance between the vehicle 100a and the other vehicles 100 using the field adjustable sensor 103a. In the depicted embodiment, the distance may be represented as a multi-dimensional vector to provide a sufficient description of the orientation and spacing of the vehicle in three-dimensional space, but other embodiments may include other configurations without departing from the teachings disclosed herein. In the depicted embodiment, the distance β represents the measured distance between the field adjustable sensor 103a and the vehicle 100b. The distance γ represents the measured distance between the field adjustable sensor 103a and the vehicle 100c. The distance δ represents the measured distance between the field adjustable sensor 103a and the vehicle 100d. The coordination server 203 may then request location data for each of the vehicles 100, which will be retrieved using each vehicle's corresponding location sensor 105 (see Figure 1 ) to measure.

[0025] After receiving the distance measurements and position measurements for each of the vehicles 100, the coordination server 203 can use this data to calculate whether each of the distance measurements is accurate to within the specified tolerances for the field adjustable sensors 103a. By using the associated vehicle processor 101 (see Figure 1 ) Knowledge of the physical dimensions of the vehicle 100 may further improve the accuracy of the comparison. In the depicted embodiment, each of the measurements β, γ, and δ may be for the closest outer surface of the vehicle 100b, vehicle 100c, and vehicle 100d to the field adjustable sensor 103a, respectively. Thus, the expected distance between vehicle 100a and another of the vehicles 100 will include a calculated distance between the location of the field adjustable sensor 103a and a point on the corresponding vehicle 100. In the depicted embodiment, the closest point on the corresponding vehicle 100 may be used to calculate the distance, but other embodiments may include other measurements without departing from the teachings disclosed herein. In some embodiments, multiple points on the corresponding vehicle may be used to measure the distance, and each of the measurements may be used in operation. Because each of the vehicles 100 is operable to provide position data describing its own boundary surface, the expected distance may be calculated based on which portion of the respective vehicle 100 intersects the following linear measurement: the linear measurement is between the field adjustable sensor 103a and the position sensor 105 associated with the particular vehicle.

[0026] In the depicted embodiment, expected distances β', γ', and δ' (not shown) may be calculated based on data describing the physical dimensions of each vehicle 100. The expected distances may be compared to the measured values ​​β', γ', and δ', respectively. If one or more of the measured values ​​are determined to be inaccurate beyond a predetermined threshold, the coordination server 203 may indicate that the field adjustable sensor 103a requires calibration. The vehicle processor 101a may then perform calibration of the field adjustable sensor 103a in response to the difference between the measured data and the expected measured value. The decision to calibrate the field adjustable sensor 103a may be determined in part using a weighted algorithm of the difference. By way of example and not limitation, if it is known that the field adjustable sensor 103a is more accurate within a specific distance range, the measured distance within the specified range may be considered with a greater weight than the measured distance outside the specified range. Other embodiments may utilize different weights in their decision algorithms without departing from the teachings disclosed herein.

[0027] The depicted embodiment utilizes three target vehicles, but any number of target vehicles may be utilized without departing from the teachings disclosed herein. In the depicted embodiment, each of the vehicles 100 is represented as a single type of vehicle (a sedan), but other embodiments may include other types of vehicles to serve as subject vehicles or target vehicles without departing from the teachings disclosed herein. For example, a subject vehicle may interact with multiple target vehicles of different types without departing from the teachings disclosed herein. In some embodiments, non-vehicle target objects such as road signs, roadblocks, overpasses, natural objects, or specialized beacons may be utilized in place of or in addition to one or more target vehicles without departing from the teachings disclosed herein.

[0028] Some embodiments may not rely on a coordination server to operate correctly. Figure 3 A diagrammatic illustration of a system is provided which is operable to perform operations substantially as described above with respect to Figure 2 Field calibration is performed in the same manner as depicted, relying only on one or more vehicle processors associated with the vehicle to perform functions associated with the coordination server. Figure 3 In the depicted embodiment, vehicle 100a remains the subject vehicle for calibration, and its associated vehicle processor 101a performs the same Figure 2 In such an embodiment, the vehicle processor 101 associated with the subject vehicle 100 may be utilized to perform these tasks. Figure 3In the depicted embodiment, the subject vehicle is vehicle 101a, but without departing from the teachings disclosed herein, any of the depicted vehicles or vehicles having other configurations of a vehicle processor, field adjustable sensors, position sensors, and vehicle transceivers may serve as the subject vehicle for field calibration.

[0029] The subject vehicle may utilize multiple measurements of the target vehicle to provide a greater amount of data from which to determine whether calibration is necessary. In some embodiments, one or more target vehicles may perform a predetermined maneuver to provide a greater amount of measurement data, or to provide a wider range of measurement data about the relative position of the target vehicle to the subject vehicle. Figure 4 is a diagrammatic view of calibration during a predetermined maneuver. In the depicted embodiment, vehicle 100a acts as a subject vehicle, and the distance to a target vehicle 100b at three different points is measured during the predetermined maneuver. In the depicted embodiment, the predetermined maneuver includes a lane change of vehicle 100b in a direction 400 along the road, but other embodiments may include any predetermined maneuver without departing from the teachings disclosed herein. By way of example and not limitation, the predetermined maneuver may include the target vehicle changing its speed with respect to the subject vehicle, adjusting its relative position with respect to the subject vehicle, maintaining its relative speed and position with respect to the subject vehicle, or moving to a specific range of the sensor with respect to the subject vehicle. Other embodiments may include other types of predetermined maneuvers without departing from the teachings disclosed herein.

[0030] exist Figure 4 In the depicted embodiment, vehicle 100a and vehicle 100b may each comprise a fully autonomous self-driving vehicle, but other embodiments may include other configurations without departing from the teachings disclosed herein. Vehicles including partially autonomous or ADAS functionality may be utilized without departing from the teachings disclosed herein. Non-autonomous vehicles may be utilized without departing from the teachings disclosed herein and provide instructions or guidance to the driver to properly perform one or more predetermined maneuvers.

[0031] During the predetermined operation, the subject vehicle can make multiple measurements of the target vehicle to generate multiple corresponding data sets. In the depicted embodiment, when vehicle 100b performs the predetermined operation, vehicle 100a makes three measurements β0, β1 and β2. Each of these three measurements can then be associated with the instantaneous position measurement of each of vehicle 100a and vehicle 100b, thereby providing a basis for comparison between expected data and measured data. In the depicted embodiment, vehicle 100a interacts only with vehicle 100b, but without departing from the teachings disclosed herein, the subject vehicle can interact with any number of target vehicles that perform the predetermined operation. Without departing from the teachings disclosed herein, the subject vehicle can interact with multiple target vehicles, only a portion of which perform the predetermined operation.

[0032] The above description is directed to extrinsic calibration, or calibration to external conditions of the subject sensor. In some embodiments, an intrinsic calibration of the field adjustable sensor 103 may be performed using a predetermined manipulation. The field adjustable sensor 103 may be operable across a range of angles or relative positions with respect to objects within the external environment, and may exhibit intrinsic distortion at some of the angles or relative positions. For example, Figure 4 The field adjustable sensor 103a depicted in FIG. 1 may exhibit distortion at one or more of the angles associated with the measurements β0, β1, and β2. Because the actual shape and size of the vehicle 100b is consistent for each of the measurements, the consistency of the field adjustable sensor 103a may be compared between each of the measurements to determine the level of intrinsic calibration.

[0033] In the depicted embodiment, the field adjustable sensor 103a may include a proximity sensor, but other embodiments may include other sensors without departing from the teachings disclosed herein. By way of example and not limitation, other embodiments may include sensors such as radar sensors, lidar sensors, ultrasonic sensors, microphones, cameras, optical sensors, infrared sensors, accelerometers, yaw rate sensors, wheel speed sensors, speedometers, steering angle sensors, or any other sensors known to one of ordinary skill in the art without departing from the teachings disclosed herein. Each sensor type may utilize a different predetermined maneuver suitable for generating data suitable for determining whether calibration is necessary without departing from the teachings disclosed herein.

[0034] In addition to providing multiple data sets for comparison, the vehicle may also perform a predetermined maneuver for additional reasons. For example, a predetermined maneuver may result in an adjustment of the relative position of a target vehicle so that it is within the range of a field-adjustable sensor of a subject vehicle. In one such embodiment, a target vehicle in front of the subject vehicle may be maneuvered to the rear of the vehicle in order to provide a target for a rear-facing field-adjustable sensor. In another example, a first target vehicle may utilize a predetermined maneuver after a first measurement in order to avoid obstructing a second target vehicle from the subject vehicle for a second measurement. Other predetermined maneuvers may have other purposes recognized by those of ordinary skill in the art without departing from the teachings disclosed herein.

[0035] Figure 5 1 is a flow chart illustrating a method of calibration and calibration assessment of a field adjustable sensor according to one embodiment of the teachings disclosed herein. The method begins at step 500, where a condition indicating that calibration may be necessary is identified with respect to a subject vehicle. The condition may be a routine condition or an occasional condition without departing from the teachings disclosed herein.

[0036] Once the condition has been identified, the method proceeds to step 502, where one or more other nearby vehicles within the environment are identified as serving as the target vehicle. After identifying a suitable vehicle, the method proceeds to step 504, in which a field-adjustable sensor generates measurement data about the target vehicle. At step 506, position data indicating the position of the target vehicle and the subject vehicle are generated using a position sensor. In some embodiments, the position of the target vehicle can be advantageously measured with respect to a specific portion of the vehicle, such as the outer surface closest to the subject vehicle. In some embodiments, the position of the field-adjustable sensor of the subject vehicle can be measured relative to the position of the position sensor to improve the accuracy of calibration considerations. In some embodiments, without departing from the teachings disclosed herein, steps 504 and 506 can be performed in any order. In some embodiments, without departing from the teachings disclosed herein, steps 504 and 506 can be performed simultaneously.

[0037] After obtaining the measurement data and position data, the position data is utilized at step 508 to generate expected data reflecting the expected results of the measurement data based on the position data. The expected data may be mathematically interpolated or extrapolated based on the position data describing each of the subject vehicle and one or more target vehicles, depending on the type of sensor being considered for possible recalibration. The expected data is compared to the measurement data to generate difference data describing the difference.

[0038] At step 510, signifier data is generated indicating whether the difference data is within a specified tolerance. The specified tolerance may be determined based on the specifications of the field adjustable sensor. If the signifier data is within the specified tolerance, calibration is not necessary and the method ends at step 512. If the signifier data is not within the specified tolerance, the method instead proceeds to step 513 to calibrate the field adjustable sensor before proceeding to step 512 to complete the method. In some embodiments, the specified tolerance may be sufficient to place the field adjustable sensor in a condition for optimal performance, but other embodiments may include other specified tolerances without departing from the teachings disclosed herein.

[0039] Although exemplary embodiments are described above, it is not intended that these embodiments describe all possible forms of the disclosed apparatus and methods. Rather, the words used in the specification are words of description rather than limitation, and it should be understood that various changes may be made without departing from the spirit and scope of the present disclosure as claimed. The features of various implementation embodiments may be combined to form additional embodiments of the disclosed concepts.

Claims

1. A method for in-situ calibration of a subject sensor associated with a subject vehicle, the method comprising: identifying a first target vehicle within an environment defined by an operating range of the subject sensor; identifying a second target vehicle within the environment defined by the operating range of the subject sensor; generating, using the subject sensor, first target sensor data indicative of a measurement of a distance between the subject vehicle and a first target vehicle; generating, using the subject sensor, second target sensor data indicative of a measurement of a distance between the subject vehicle and a second target vehicle; generating subject position data indicating a coordinate position of a subject vehicle; generating first position data indicating a coordinate position of a first target vehicle; generating second position data indicating a coordinate position of a second target vehicle; generating first boundary data indicating a position of an outer surface of a first object vehicle based on the first position data; generating second boundary data indicating a position of an outer surface of a second object vehicle based on the second position data; generating first expected data based on the subject position data and the first boundary data; generating second expected data based on the subject position data and the second boundary data; The subject sensor is calibrated when the first target sensor data does not match the first expected data within a specified tolerance or the second target sensor data does not match the second expected data within a specified tolerance. 2 . The method of claim 1 , wherein the step of generating the first target sensor data further comprises acquiring a plurality of iterations of the first target sensor data while the first target vehicle is performing a predetermined maneuver with respect to the subject vehicle. 3 . The method of claim 1 , wherein the step of generating the second target sensor data further comprises acquiring a plurality of iterations of the second target sensor data while the second target vehicle is performing a predetermined maneuver with respect to the subject vehicle. 4 . The method of claim 1 , further comprising transmitting the first target sensor data, the second target sensor data, the first expected data, and the second expected data to a coordination server.

5. The method of claim 1 , wherein the step of generating first target sensor data further comprises acquiring multiple iterations of the first target sensor data while the first target vehicle is performing a predetermined maneuver with respect to the subject vehicle, and wherein the first target vehicle performing the predetermined maneuver is controlled by a coordination server.

6. A sensor calibration system comprising: a subject sensor associated with the subject vehicle and operable to generate measurement data; a subject processor associated with the subject vehicle, the subject processor being in data communication with the subject sensors and operable to detect a condition of the subject sensors necessitating calibration; a subject position sensor associated with the subject vehicle and in data communication with the subject processor, the subject position sensor operable to generate subject position data indicative of a position of the subject position sensor; a first processor associated with the first target vehicle, the first processor operable for data communication with the subject processor; a first position sensor associated with the first target vehicle and in data communication with the first processor, the first position sensor operable to generate first position data indicative of a position of the first position sensor; a second processor associated with a second target vehicle, the second processor operable for data communication with the first processor; a second position sensor in data communication with the second processor, the second position sensor being operable to generate second position data indicative of a position of the second position sensor; wherein the body processor is operable to control the body sensor to generate first measurement data indicative of a distance between the body sensor and a first target vehicle, wherein the body processor is operable to generate body position data indicating a position of the body sensor based on the body position data, and the first processor is operable to generate first boundary data indicating a position of an outer surface of a first target vehicle based on the first position data, wherein the subject processor is further operable to generate first expected data based on the subject position data and the first boundary data, and wherein the second processor is operable to generate second boundary data indicating a position of an outer surface of a second target vehicle based on the second position data, wherein the body processor is operable to control the body sensor to generate second measurement data indicative of a distance between the body sensor and the second vehicle, The body processor is also operable to generate second expected data based on the body position data and the second boundary data, and wherein, when the first measurement data does not conform to the first expected data within a specified tolerance or the second measurement data does not conform to the second expected data within a specified tolerance, the body processor is also operable to calibrate the body sensor. 7 . The system of claim 6 , wherein the first processor is operable to control the first target vehicle to perform a predefined autonomous maneuver during the generation of the first measurement data and the first expected data.

8. The system of claim 7, wherein the first processor is operable to control the first target vehicle to perform a predefined autonomous maneuver in response to a request generated by the subject processor.

9. The system of claim 8, wherein the first processor is operable to perform an intrinsic calibration of the body sensor using data generated by a predefined autonomous maneuver of the first target vehicle.

10. The system of claim 9, wherein the first processor is operable to perform an extrinsic calibration of the body sensor using data generated by a predefined autonomous maneuver of the first target vehicle.

11. The system of claim 6, wherein the subject processor is operable to detect a condition of the subject sensor that necessitates calibration.

12. The system of claim 6, wherein the subject processor is located remotely from the subject vehicle and is operable to wirelessly communicate with the subject sensor.

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