Method for evaluating an object space sensor mounted on an autonomous vehicle

Abstract

Method for evaluating an object space sensor (41) arranged on an autonomous vehicle (10), wherein the object space sensor (41) is arranged to monitor a spatial environment near the autonomous vehicle (10), and wherein the autonomous vehicle (10) includes a telematics device for communicating with an off-board controller (280), the method comprising: Determining a first health status parameter, SOH parameter, for the object space sensor (41) based on internal monitoring of the object space sensor (41), wherein a first field of view (43) is assigned to the object space sensor (41); Determining a second SOH parameter for the object space sensor (41) based on a correlation analysis of data generated by a second space sensor (41') arranged on the autonomous vehicle (10); Determining a third SOH parameter for the object space sensor (41) based on historical data for the object space sensor (41) that is assigned to a geographic position; Determining a fourth SOH parameter for the object space sensor (41) based on a correlation analysis with an input from a third space sensor located on a second vehicle, wherein the input from the third space sensor includes data associated with the geographic position; Determining a fifth SOH parameter for the object space sensor (41) based on a correlation analysis with an input from a calibration space sensor located on a calibration vehicle, wherein the input from the calibration space sensor includes data associated with the geographic position; Determining an integrated SOH parameter for the object space sensor (41) based on the first, second, third, fourth and fifth SOH parameters; Comparing the integrated SOH parameter with a threshold SOH; Displaying a result of the comparison of the integrated SOH parameter with the threshold SOH via an operator interface device when the integrated SOH parameter is less than the threshold SOH, the result indicating that the object space sensor (41) is not suitable for use for monitoring the spatial environment near the vehicle (10); and Transmit the result to the off-board control (280) to schedule vehicle service based on the result.

Description

INTRODUCTION

[0001] Autonomous vehicles may include on-board monitoring systems to detect the occurrence of a fault or other indication of a need for service and / or vehicle maintenance.

[0002] DE 10 2014 216 018 A1 discloses a control device for a vehicle having two environmental sensors and a computing device, wherein the computing device is configured to check the plausibility of sensor data from the environmental sensors against each other. DE 10 2014 220 925 A1 discloses a system and a method for checking the plausibility of sensor data. US 2007 / 0282506 A1 describes a method for controlling vehicle systems based on an analysis of images of an environment in or around a vehicle. DE 10 2007 037 298 A1 discloses a method and an arrangement for checking a sensor signal of a sensor cluster.

[0003] It is the object of the present invention to provide a method that enables an improved verification of a sensor as to whether the sensor is suitable for use in monitoring a spatial environment in the vicinity of an autonomous vehicle.

[0004] This object is achieved by a method for evaluating an object space sensor arranged on an autonomous vehicle having the features of claim 1. SUMMARY

[0005] An unclaimed autonomous vehicle control system is described and includes a vehicle spatial monitoring system including an object space sensor arranged to monitor a spatial environment proximate the autonomous vehicle. A controller communicates with the object space sensor, and the controller includes a processor and a memory device including an instruction set. The instruction set is executable to evaluate the object space sensor, including determining first, second, third, fourth, and fifth SOH (state of health) parameters associated with the object space sensor and, based thereon, determining an integrated SOH parameter for the object space sensor.

[0006] In one aspect, a method for evaluating an object space sensor disposed on an autonomous vehicle is disclosed, wherein the object space sensor is disposed to monitor a spatial environment proximate the autonomous vehicle, and wherein the autonomous vehicle includes a telematics device for communicating with an off-board controller. The method comprises the following steps: determining a first state of health (SOH) parameter for the object space sensor based on internal monitoring; determining a second SOH parameter for the object space sensor based on a correlation analysis of data generated by a second spatial sensor disposed on the autonomous vehicle; determining a third SOH parameter for the object space sensor based on historical data for the object space sensor associated with a geographic location;Determining a fourth SOH parameter for the object space sensor based on a correlation analysis with an input from a third spatial sensor disposed on a second vehicle, wherein the input from the third spatial sensor comprises data associated with the geographical position; Determining a fifth SOH parameter for the object space sensor based on a correlation analysis with an input from a calibration spatial sensor disposed on a calibration vehicle, wherein the input from the calibration spatial sensor comprises data associated with the geographical position; Determining an integrated SOH parameter for the object space sensor based on the first, second, third, fourth, and fifth SOH parameters; Comparing the integrated SOH parameter to a threshold SOH;Displaying a result of comparing the integrated SOH parameter with the threshold SOH via an operator interface device if the integrated SOH parameter is less than the threshold SOH, the result indicating that the object space sensor is not suitable for use in monitoring the spatial environment near the vehicle; and communicating the result to the off-board controller for scheduling a vehicle service based on the result.

[0007] Another aspect of the disclosure includes a low value for the SOH parameters associated with a low value output by the correlation analysis and a high value for the SOH parameters associated with a high value output by the correlation analysis.

[0008] Another aspect of the disclosure includes determining the integrated SOH parameter for the object space sensor based on a weighted average of the first, second, third, fourth, and fifth SOH parameters.

[0009] The above features and advantages, as well as other features and advantages of the present teachings, will become more apparent from the following detailed description of some of the best modes and other embodiments for carrying out the present teachings, as defined in the appended claims, with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In the following, one or more embodiments are described by way of example with reference to the accompanying drawings, in which: Fig. 1 schematically shows a vehicle including an autonomous vehicle control system and associated controls according to the disclosure; and Fig. Figure 2 schematically shows an information flow diagram illustrating an analysis architecture for performing an integrated assessment of a spatial sensor, e.g., one of the spatial sensors used on the vehicle space monitoring system of the autonomous vehicle described with reference to Fig. 1 is described according to the Revelation; and Fig. 3 schematically shows an embodiment of the integrated room sensor SOH determination routine according to the disclosure.

[0011] It should be understood that the accompanying drawings are not necessarily to scale and present a somewhat simplified representation of various preferred features of the present disclosure as disclosed herein, including, for example, specific dimensions, orientations, locations, and shapes. Details pertaining to such features will be determined in part by the particular intended application and use environment. DETAILED DESCRIPTION

[0012] The components of the disclosed embodiments described and illustrated herein can be arranged and constructed in a variety of different configurations. Therefore, the following detailed description of the embodiments is not intended to limit the scope of the disclosure as claimed, but is merely representative of possible embodiments thereof. Moreover, although numerous specific details are set forth in the following description to provide a thorough understanding of the embodiments disclosed herein, some embodiments may be practiced without some of these details. Moreover, for the sake of clarity, technical material understood in the related art has not been described in detail to avoid unnecessarily obscuring the disclosure.Furthermore, the disclosure as illustrated and described herein may be practiced in the absence of any element not expressly disclosed herein.

[0013] With reference to the drawings, in which like reference numerals correspond to the same or similar components in the different figures, Fig.1, in accordance with embodiments disclosed herein, a vehicle 10 includes an autonomous vehicle control system 20 and an associated vehicle health monitoring (VHM) controller 120 embodying the concepts described herein. The vehicle 10, in one embodiment, includes a four-wheel drive passenger vehicle with steerable front and rear wheels. The vehicle 10 may be, by way of non-limiting examples, a passenger car, a light or heavy-duty vehicle, a multi-purpose vehicle, an agricultural vehicle, an industrial / warehouse vehicle, or a recreational off-road vehicle.

[0014] As used herein, the autonomous vehicle control system 20 includes a vehicle control system capable of providing a level of driving automation. The terms "driver" and "operator" describe the person responsible for directing the operation of the vehicle, whether actively participating in controlling one or more vehicle functions or directing autonomous vehicle operation. Driving automation may include a number of dynamic driving and vehicle functions. Driving automation may include some degree of automatic control or intervention related to a single vehicle function, such as steering, acceleration, and / or braking, with the driver always having overall control of the vehicle. Driving automation may include some degree of automatic control or intervention associated with the simultaneous control of multiple vehicle functions, such asSteering, acceleration, and / or braking are related, with the driver constantly having overall control of the vehicle. Driving automation may include simultaneous automatic control of driving functions of the vehicle, including steering, acceleration, and braking, with the driver relinquishing control of the vehicle for a certain period of time during a trip. Driving automation may include simultaneous automatic control of driving functions of the vehicle, including steering, acceleration, and braking, with the driver relinquishing control of the vehicle for an entire trip. Driving automation includes hardware and controllers configured to monitor the spatial environment in different driving modes in order to perform various driving tasks during dynamic operation.Driving automation may include, as non-limiting examples, cruise control, adaptive cruise control, lane change warning, intervention and control, automatic parking, acceleration, braking, and the like.

[0015] The autonomous vehicle control system 20 preferably includes one or more vehicle systems and associated controllers that provide a level of driving automation, and the VHM controller 120 is arranged to monitor, predict, and / or diagnose the operation of the autonomous vehicle control system 20. The vehicle systems, subsystems, and controllers associated with the autonomous vehicle control system 20 are implemented to perform one or more operations associated with autonomous vehicle functions, including, as non-limiting examples, adaptive cruise control (ACC) operation, lane guidance and lane keeping operation, lane change operation, steering assist operation, object avoidance operation, parking assist operation, vehicle braking operation, vehicle speed and acceleration operation, vehicle lateral movement operation, e.g.as part of lane guidance, lane keeping, and lane change operations, etc. The vehicle systems and associated controllers of the autonomous vehicle control system 20 may include, as non-limiting examples, a powertrain 32 and powertrain control module (PCM) 132; a steering system 34, a braking system 36, and a chassis system 38 controlled by a vehicle control module (VCM) 136; a vehicle compartment monitoring system 40 and compartment monitoring controller 140; a human-machine interface (HMI) system 42 and HMI controller 142; an HVAC system 44 and associated HVAC controller 144; operator controls 46 and associated operator controller 146; and a vehicle lighting, illumination, and external signaling system 48 and associated controller 148.

[0016] Each of the vehicle systems and associated controllers may further include one or more subsystems and an associated controller. The subsystems and controllers are depicted as discrete elements for ease of description. The above classification of subsystems is provided for the purpose of describing one embodiment and is for illustrative purposes. Other configurations may be considered within the scope of this disclosure. It should be noted that the functions described and performed by the discrete elements may be performed with one or more devices that may include algorithmic code, calibrations, hardware, an application-specific integrated circuit (ASIC), and / or off-board or cloud-based computing systems.Each of the above-mentioned controllers includes a VHM agent, which can be implemented and executed as algorithmic code, calibrations, hardware, application-specific integrated circuits (ASICs), or other elements. Each of the VHM agents is configured to perform component and subsystem monitoring, feature extraction, data filtering, and data logging for the associated controller. Data logging may include periodic and / or event-based data logging, single-point-in-time data logging, and / or sequential point-in-time data logging for specific time periods, such as before and / or after an event trigger. Such data logging may be achieved using circular memory buffers or other suitable storage devices.

[0017] The PCM 132 communicates and is operatively connected to the powertrain 32 and executes control routines to control the operation of an engine and / or other torque machines, a transmission, and a driveline, none of which are shown, for transferring propulsion torque to the vehicle wheels in response to driver inputs, external conditions, and vehicle operating conditions. The PCM 132 is shown as a single controller, but may include a plurality of functional controllers for controlling various powertrain actuators, including the engine, transmission, torque machines, wheel motors, and other elements of a powertrain 32, none of which are shown. As a non-limiting example, the powertrain 32 may include an internal combustion engine and a transmission with associated engine and transmission controls.In addition, the internal combustion engine may include a variety of discrete subsystems with individual controls, including, for example, an electronic throttle device and controller, fuel injectors and controller, etc. The powertrain 32 may also consist of an electrically powered motor / generator with an associated power inverter module and inverter controller. The control routines of the PCM 132 may also include an adaptive cruise control (ACC) system that controls vehicle speed, acceleration, and braking in response to driver inputs and / or autonomous vehicle control inputs. The PCM 132 also includes a PCM VHM agent 133.

[0018] The VCM 136 communicates with, is functionally connected to, and executes control routines for controlling the operation of multiple vehicle operating systems. The vehicle operating systems may include brakes, stability control, and steering, which may be controlled by actuators associated with the braking system 36, the chassis system 38, and the steering system 34, respectively, which are controlled by the VCM 136. The VCM 136 is depicted as a single controller, but may include multiple functional controllers for monitoring systems and controlling various actuators. The VCM 136 also includes a VCM-VCM agent 137.

[0019] The steering system 34 is configured to control vehicle lateral movement. The steering system 34 may include an electric power steering (EPS) system coupled to an active front steering system for supplementing or replacing operator input via a steering wheel 108 by controlling the steering angle of the steerable wheels of the vehicle 10 during the execution of an autonomous maneuver, such as a lane change. An exemplary active front steering system allows for primary steering input by the vehicle operator, including increasing steering wheel angle control to achieve a preferred steering angle and / or vehicle yaw angle. Alternatively or additionally, the active front steering system may provide full autonomous control of the vehicle steering function.It will be appreciated that the systems described herein are applicable with modifications to vehicle steering control systems such as electric power steering, four / rear wheel steering systems, and direct yaw control systems that control the traction slip of each wheel to produce a yaw motion.

[0020] The braking system 36 is configured to control vehicle brakes and includes wheel braking devices, e.g., disc brake elements, brake calipers, master cylinders, and a brake actuation device, e.g., a pedal. Wheel speed sensors monitor individual wheel speeds, and a brake control may be mechanized to include anti-lock functionality.

[0021] The chassis system 38 preferably includes a plurality of on-board sensing systems and devices for monitoring vehicle operation to determine vehicle motion conditions, and in one embodiment, a plurality of devices for dynamically controlling a vehicle suspension. The vehicle motion conditions preferably include, for example, ground speed, steering angle of the steerable front wheels, and yaw rate. The on-board sensing systems and devices include inertial sensors, such as yaw rate sensors and accelerometers. The chassis system 38 estimates vehicle motion conditions, such as longitudinal vehicle speed, yaw rate, and lateral speed, and estimates the lateral displacement and yaw angle of the vehicle 10. The measured yaw rate is combined with the steering angle measurements to estimate the vehicle's lateral speed condition.The vehicle's longitudinal speed can be determined from signal inputs from the wheel speed sensors configured to monitor each of the front and rear wheels. Signals associated with the vehicle's motion conditions can be transmitted to and monitored by other vehicle control systems for vehicle control and operation.

[0022] The vehicle space monitoring system 40 and the space monitoring controller 140 may include a controller and a plurality of space sensors 41, each of the space sensors 41 being arranged on a vehicle to monitor a field of view 43 of objects and geographical regions proximal to the vehicle 10. A nominal object space sensor is designated by the reference numeral 41 with an associated field of view 43, and other space sensors are designated by the reference numeral 41' with associated fields of view 43'. Each of the space sensors described herein may be referred to as the object space sensor 43 in the context of the systems described with reference to the Fig. 2 and Fig.3. The spatial monitoring controller 140 generates digital representations of each of the fields of view containing near objects 155 based on data inputs from the spatial sensors. The spatial monitoring controller 140 also includes a spatial monitoring VHM agent 141. The spatial monitoring controller 140 may evaluate inputs from the spatial sensors 41 to determine a linear range, relative velocity, and trajectory of the vehicle 10 with respect to each near object. The spatial sensors 41 may be disposed at various locations on the vehicle 10, including the front corners, rear corners, rear sides, and center sides. The spatial sensors 41 may include a front radar sensor and a camera in one embodiment, although the disclosure is not so limited.The arrangement of the aforementioned spatial sensors 41 enables the spatial monitoring controller 140 to monitor traffic flow, including nearby vehicles and other objects around the vehicle 10. Data generated by the spatial monitoring controller 140 can be used by the pavement marking detection processor (not shown) to estimate the roadway. The spatial sensors 41 of the vehicle spatial monitoring system 40 can further include object-detecting sensor devices, including range sensors such as FM-CW (Frequency Modulated Continuous Wave) radars and FSK (Frequency Shift Keying) radars, LIDAR (Light Detection and Ranging) devices, and ultrasonic devices that rely on effects such as Doppler-effect measurements to locate forward objects.Possible object-sensing devices include charge-coupled devices (CCD) or complementary metal-oxide-semiconductor (CMOS) video image sensors and other camera / video image processors that use digital photographic techniques to 'view' forward objects, including one or more vehicles. Such sensing systems are used for object detection and tracking in automotive applications and are usable with systems including, for example, adaptive cruise control, autonomous braking, autonomous steering, and side object detection.

[0023] The spatial sensors 41 associated with the vehicle spatial monitoring system 40 are preferably positioned within the vehicle 10 in relatively unobstructed positions to monitor the spatial environment. As used herein, the spatial environment includes external elements, including stationary objects such as signs, posts, trees, houses, stores, bridges, etc.; and moving or mobile objects such as pedestrians and other vehicles. Each of these spatial sensors 41 provides an estimate of the actual position or condition of an object, wherein the estimate includes an estimated position and the standard deviation. As such, the sensory detection and measurement of object locations and conditions are commonly referred to as 'estimates'. It will be further recognized that the characteristics of these spatial sensors 41 are complementary in that some are more reliable than others at estimating certain parameters.The spatial sensors 41 may each have different operating ranges and angular coverages, which can estimate various parameters within their operating ranges. For example, radar sensors can typically estimate the range, range rate, and azimuth location of an object, but are typically not good at estimating the dimensions of a detected object. A camera with a vision processor is more accurate at estimating an object's shape and azimuth position, but less efficient at estimating an object's range and range rate. Scanning lidar systems are efficient and accurate at estimating range and azimuth position, but typically cannot estimate the range rate and are therefore not as accurate at new object detection / recognition. Ultrasonic sensors are capable of estimating range, but generally cannot estimate or calculate the range rate and azimuth position.Furthermore, it is recognized that the performance of each sensor is influenced by different environmental conditions. Thus, some of the 41 room sensors exhibit parametric variances during operation, although overlapping sensor detection ranges create opportunities for sensor data fusion.

[0024] The HVAC system 44 is arranged to manage the ambient environment of the passenger compartment, including, for example, temperature, humidity, air quality, and the like, in response to operator commands communicated to the HVAC controller 144, which controls its operation. The HVAC controller 144 also includes an HVAC VHM agent 145.

[0025] The operator controls 46 may be included in the passenger compartment of the vehicle 10 and may include, as non-limiting examples, a steering wheel 108, an accelerator pedal, a brake pedal, and an operator input device 110. The operator controls 46 and the associated operator control 146 enable a vehicle operator to interact with and control the operation of the vehicle 10 to provide passenger transportation. The operator control 146 also includes an operator control VHM agent 147. The operator control devices, including the steering wheel 108, the accelerator pedal, the brake pedal, the transmission range selector, and the like, may be omitted in some embodiments of the autonomous vehicle 10.

[0026] The steering wheel 108 may be mounted on a steering column 109, with the input device 110 mechanically mounted to the steering column 109 and configured to communicate with the operator control 146. Alternatively, the input device 110 may be mechanically mounted proximate the steering column 109 at a location convenient for the vehicle operator. The input device 110, depicted herein as a protruding shaft of the column 109, may be a user interface device through which the vehicle operator may command vehicle operation in one or more autonomous control modes, e.g., by commanding the activation of one or more elements of the autonomous vehicle control system 20. The mechanization of the input device 110 is exemplary. The input device 110 may be mechanized in one or more of the plurality of devices, or may take the form of a controller that is voice-activated or may be another suitable system.Input device 110 preferably includes control features and a location utilized by present turn signal activation systems. Alternatively, other input devices, such as levers, pushbuttons, buttons, and voice recognition input devices, may be used instead of or in addition to input devices 110.

[0027] The HMI system 42 provides human / machine interaction to control the operation of an infotainment system, a GPS system, a navigation system, and the like, and includes an HMI controller 142. The HMI controller 142 monitors vehicle operator instructions and provides information to the vehicle operator, including the status of the vehicle systems and service and maintenance information. The HMI controller 142 may also include a global positioning / navigation system. The HMI controller 142 communicates with and / or controls a plurality of user interface devices, wherein the user interface devices are capable of sending a message in connection with one of the autonomous vehicle control systems.The HMI controller 142 preferably also communicates with one or more devices that monitor biometric data associated with the vehicle operator, including, for example, gaze direction, posture, and head position detection, among others. The HMI controller 142 is a unitary device for ease of description, but may be configured as multiple control modules and the corresponding sensor devices in one embodiment of the system described herein. The HMI controller 142 also includes an HMI-VHM agent 143. Operator interface devices may include devices capable of sending a reminder message operator action and may include an electronic display module, e.g., a liquid crystal display (LCD) device, a heads-up display (HUD) (not shown), an audio feedback device, a wearable device, and a haptic seat.The user interface devices capable of prompting an operator action are preferably controlled by or via the HMI controller 142. The HUD may project information that is reflected onto an interior surface of a vehicle windshield within the driver's field of view, including conveying a confidence level associated with the operation of an autonomous vehicle control system. The HUD may also provide augmented reality information, such as lane location, vehicle path, heading and / or tracking information, and the like. The HUD and related systems are understood by those skilled in the art.

[0028] The vehicle lighting, illumination, and external signaling system 48 includes a variety of headlights, taillights, brake lights, marker lights, signal lamps, and the like, which are controllable via the lighting controller 148. The lighting controller 148 communicates with ambient light sensors, the GPS system, and the navigation system and executes control routines that selectively illuminate various headlights, taillights, brake lights, marker lights, and signal lamps based on the ambient light, the direction of intended travel from the GPS and navigation systems, and other factors. Other factors may include an override command to illuminate the vehicle lights in a design zone. The lighting controller 148 also includes a lighting VHM agent 149.

[0029] In one embodiment, vehicle 10 is configured to communicate with communications network 285, including communication between a controller associated with a smart highway system and vehicle 10. A smart highway system may be configured to monitor the positions, speeds, and trajectories of a plurality of vehicles, using such information to enable control of one or more similarly positioned vehicles. This may include communicating the geographic location, front-end speed, and acceleration rate of one or more vehicles relative to vehicle 10. In one embodiment, vehicle 10 is configured to communicate with an external controller 280 via communications network 285, wherein the off-board controller is remotely located.

[0030] The VHM controller 120 is configured to autonomously monitor the status of various vehicle-side subsystems that perform one or more functions related to autonomous vehicle operation. The VHM controller 120 includes a control architecture configured with multi-layered hierarchical VHM data processing, collection, and storage using the multiple VHM agents associated with a VHM main controller that can communicate with the off-board controller 280. This configuration can serve to reduce the complexity of data processing, data collection, and data storage costs. The VHM controller 120 provides a centralized system monitoring and a distributed system monitoring arrangement with data collection via the VHM main controller and the plurality of VHM agents to provide rapid response time and integrated vehicle / system-level coverage.The VHM controller 120 may also include a fault mitigation controller and a redundant VHM main controller to verify the integrity of the VHM information used by the fault mitigation controller.

[0031] The term "controller" and related terms such as control module, module, controller, control unit, processor, and similar terms refer to one or various combinations of application-specific integrated circuits (ASICs), electronic circuit(s), central processing unit(s), e.g., microprocessor(s), and associated non-transitory storage component(s) in the form of memory and storage devices (read-only memory, programmable read-only memory, random access memory, hard disk, etc.). The non-transitory storage component is capable of storing machine-readable instructions in the form of one or more software or firmware programs or routines, combinational logic circuit(s), input / output circuit(s) and devices, signal conditioning and buffer circuits, and other components accessible by one or more processors to provide a described functionality.Drive / output circuitry and devices include analog-to-digital converter-related devices that monitor sensor inputs at a predetermined polling frequency or in response to a trigger event. Software, firmware, programs, instructions, control routines, code, algorithms, and similar terms refer to sets of instructions executable by a control unit, such as calibrations and look-ups. Each controller executes one or more control routines to provide desired functions. The routines may be executed at regular intervals, such as every 100 microseconds during operation. Alternatively, routines may be executed in response to a trigger event. The term "model" refers to processor-based or processor-executable code and associated calibration that simulates the physical existence of a device or physical process.The term "dynamic" describes steps or processes that are performed in real time and are characterized by monitoring or otherwise determining parameter states and regularly or periodically updating parameter states while executing a routine or between iterations of program execution. The terms "calibration," "calibrating," and related terms refer to a result or procedure that compares an actual or standard measurement associated with a device with a sensed or observed measurement or a commanded position. A calibration described herein may be reduced to a storable parametric table, multiple executable equations, or other suitable form.

[0032] Communication between controllers and communication between controllers and actuators and / or sensors may be via a direct wired connection, a networked communications bus, a wireless connection, or any other suitable communications link. Communication involves the exchange of data signals by any suitable means, including, for example, electrical signals through a conductive medium, electromagnetic signals through the air, optical signals through fiber optics, and the like. Data signals may include discrete, analog, or digitized analog signals representing inputs from sensors and actuator commands, as well as communication signals between control units. The term "signal" refers to a physically perceivable indication that conveys information and may be a suitable waveform (e.g.,Electrical, optical, magnetic, mechanical, or electromagnetic, such as direct current, alternating current, sine waves, triangular waves, square waves, vibration, and the like, that can pass through a medium. A parameter is defined as a measurable quantity that represents a physical property of a device or other element that is detectable by one or more sensors and / or a physical model. A parameter may have a discrete value, e.g., "1" or "0," or may be continuously adjustable.

[0033] The terms "forecast," "forecasting," and related terms are associated with data monitoring, algorithms, and evaluations that provide advance indication of a likely future event associated with a component, subsystem, or system. Forecasting may involve classifications that include a first state indicating that the component, subsystem, or system is operating according to its specification ("Green" or "G"), a second state indicating deterioration in the operation of the component, subsystem, or system ("Yellow" or "G"), and a third state indicating a failure in the operation of the component, subsystem, or system ("Red" or "R").The terms "diagnostics," "diagnosis," and related terms are associated with data monitoring, algorithms, and evaluations that provide an indication of the presence or absence of a specific fault in a component, subsystem, or system. The term "mitigation" and related terms are associated with operations, actions, or control routines designed to reduce the impact of a fault in a component, subsystem, or system.

[0034] Telematics controller 125 includes a wireless telematics communication system capable of additional vehicle communication, including communication with communication network system 285 having wireless and wired communication capabilities. Telematics controller 125 is capable of additional vehicle communication, including short-range vehicle-to-vehicle (V2V) communication. Alternatively or additionally, telematics controller 125 includes a wireless telematics communication system capable of short-range wireless communication with a handheld device, such as a cellular phone, a satellite phone, or other telephony device.In one embodiment, the handheld device is provided with a software application including a wireless protocol for communicating with the telematics controller, and the handheld device performs the additional vehicle communication, including communication with the off-board controller 280 via a communication network 285. Alternatively or additionally, the telematics controller performs the additional vehicle communication directly by communicating with the off-board controller 280 via the communication network 285.

[0035] Prognostic classification routines for determining a prognosis, i.e., R / G / G, for each of the subsystems may be executed in the VHM controller 120. The prognostic classification routines may detect the occurrence of a green prognosis associated with one of the vehicle subsystems and associated controllers of the autonomous vehicle control system 20, and the VHM controller 120 may block the associated data transmission off-board via the communication network 285 to reduce the data communication load on the off-board controller 280. Alternatively, the transmission of a green prognosis may take the form of a simple acknowledgment of the green determination for a component, subsystem, or system of one of the vehicle systems and associated controllers of the autonomous vehicle control system 20 with a timestamp, thus minimizing the data transmission load to the off-board controller 280.

[0036] The VHM controller 120 includes executable routines that evaluate vehicle devices that monitor the spatial environment of the autonomous vehicle 10, including, for example, the spatial sensors 41, the vehicle space monitoring system 40, the space monitoring controller 140, and the space monitoring VHM agent 141 described with reference to Fig. 1 are described.

[0037] Fig. Figure 2 schematically shows an information flow diagram illustrating an analysis architecture 200 for performing an integrated evaluation of a space sensor, e.g., the object space sensor 41, connected to the vehicle space monitoring system 40 of the system described with reference to Fig. 1. In one embodiment, the control routines and calibrations are contained in and executed by the room monitoring controller 140.

[0038] The analysis architecture 200 includes a sensor-level diagnostic / prediction routine (D&P routine) 130 for monitoring the object space sensor 41, a vehicle-level diagnostic / prediction routine 150 for monitoring the object space sensor 41, a historical data diagnostic / prediction routine 160 for monitoring the object space sensor 41, a fleet data diagnostic / prediction routine 170 for monitoring the object space sensor 41, and a calibration vehicle data diagnostic / prediction routine 180 for monitoring the object space sensor 41. An integrated vehicle-level diagnostic / prediction routine 190 combines the results of the preceding routines to determine an integrated assessment of the object space sensor 41, which is communicated to the vehicle operator or the off-board controller 280 for maintenance. Each of the spatial sensors 41' can be referred to as the object space sensor 41 for evaluation purposes.Each of the spatial sensors 41 is arranged to monitor a field of view located proximal to the vehicle 10 and includes executable routines that provide diagnostic and prognostic analyses based thereon.

[0039] A detailed implementation of the analysis architecture 200 may be implemented via an integrated room sensor SOH determination routine 300 to generate an SOH result for the object space sensor 41, which may be executed in the VHM controller 120. The integrated room sensor SOH determination routine 300 may be triggered for execution at any desired time and is executed as a control routine stored in a memory device in one of the vehicle controllers.

[0040] Fig.Figure 3 schematically illustrates one embodiment of the integrated room sensor SOH determination routine 300. Table 1 provides a breakdown in which the numerically labeled blocks and the corresponding functions are implemented as follows, according to the integrated room sensor SOH determination routine 300. The teachings herein may be described in terms of the functional or logical block components, or various processing steps, respectively. It should be noted that such block components may be constructed from hardware, software, and / or firmware components configured to perform the specified functions. Table 1 BLOCK BLOCK CONTENT 302 Estimating individual room sensor SOH 304 Estimate overlap room sensor-SOH 306 Estimating history-based room sensor SOH 308 Estimating fleet-based spatial sensor SOH 310 Estimate calibration vehicle-based spatial sensor SOH 312 Calculate integrated SOH 314 Is integrated SOH > threshold? 316 Show errors with room sensor 318 Do not display an error with room sensor

[0041] The execution of the integrated room sensor SOH determination routine 300 may proceed as follows. The steps of the integrated room sensor SOH determination routine 300 may be executed in any suitable order and are not limited to the order described with reference to Fig. 3 is limited.

[0042] A single spatial sensor SOH for one of the in-vehicle spatial sensors 41 (hereinafter "the object space sensor 41") may be determined based on internal monitoring of operating conditions, as provided by the spatial monitoring VHM agent 141 (302). This may include monitoring internal calibrations, power levels, etc., to verify signal integrity and other parameters derived from monitoring the object space sensor 41. The object space sensor 41 has a field of view 43 that may overlap with fields of view from the other spatial sensors, designated by reference numeral 41'.

[0043] An overlap spatial sensor SOH for the object space sensor 41 may be determined using information from one or more of the other in-vehicle spatial sensors 41 that have a field of view that overlaps with the field of view associated with the spatial sensor 41 (304). The overlap spatial sensor SOH for the object space sensor 41 may be determined based on a correlation analysis of data generated by a second of the spatial sensors or by two or more of the spatial sensors 41. This involves attempting to detect inconsistencies between the data related to the overlapping fields of view of the object space sensor 41 and the second of the spatial sensors 41. A high value for the overlap spatial sensor SOH may be associated with high levels of consistency between the overlap data, and a low value for the overlap spatial sensor SOH may be associated with low levels of consistency between the overlap data.

[0044] A history-based spatial sensor SOH for the object space sensor 41 may be determined using data from the object space sensor 41 previously acquired for a predefined geographic location and an associated GPS location and time / date stamp (306). The routine may compare historical data for the same GPS location with the object space sensor 41, which has an orientation and field of view relative to the geographic location that matches the geographic location associated with the historical data. This includes attempting to detect inconsistencies between the currently acquired data from the object space sensor 41 and the historical data.A high value for the history-based spatial sensor SOH may be associated with high levels of consistency between the currently sensed data and the historical data from the object space sensor 41, and a low value for the overlap spatial sensor SOH may be associated with low levels of consistency between the currently sensed data and the historical data from the object space sensor 41 at the geographic location.

[0045] A fleet-based spatial sensor SOH for the object space sensor 41 may be determined by comparing data from the object space sensor 41 at a predefined geographic location with fleet data generated by spatial sensors located on other vehicles at the predefined geographic location (308). The fleet data may be stored in a storage device that is part of the off-board controller 280. The routine may compare the fleet data for the same GPS location with data from the object space sensor 41 at a common orientation and field of view for the predefined geographic location. This includes attempting to detect inconsistencies between the currently collected data from the object space sensor 41 and the fleet data.A high value for the fleet-based spatial sensor SOH may be associated with high levels of consistency between the currently acquired data from the object spatial sensor 41 and the fleet data, and a low value for the fleet-based spatial sensor SOH may be associated with low levels of consistency between the currently acquired data from the object spatial sensor 41 and the fleet data at the geographic location.

[0046] A calibration-based spatial sensor SOH for the object space sensor 41 may be determined by comparing data from the object space sensor 41 at a predefined geographic location with data acquired from spatial sensors located on other vehicles at the predefined geographic location (310). The calibration data may be stored in a storage device that is part of the off-board controller 280. The routine may compare the data from the object space sensor 41 and calibration data from the calibration vehicle at a common orientation and field of view for the geographic location. This includes attempting to detect inconsistencies between the currently acquired data from the object space sensor 41 and the calibration data.A high value for the calibration-based spatial sensor SOH may be associated with high levels of consistency between the currently acquired data from the object spatial sensor 41 and the fleet data, and a low value for the calibration-based spatial sensor SOH may be associated with low levels of consistency between the currently acquired data from the object spatial sensor 41 and the fleet data at the geographic location.

[0047] Routine 300 determines an integrated SOH for the object space sensor 41 (312), which may be in the form of a weighted average of all or selected individual space sensor SOHs, the overlap space sensor SOH, the history-based space sensor SOH, the fleet-based space sensor SOH, and the calibration-based space sensor SOH. In one embodiment, the integrated SOH may be calculated as follows: SOHINT=Windv∗SOHindv+Woverlap*SOHoverlap+Whist*SOHhist+ Wfleet*SOHfleet+Wcal*SOHcal wherein SOH INT the integrated SOH; SOH indv is the individual room sensor SOH; SOH overlap is the overlap room sensor SOH; SOH hist is the history-based room sensor SOH; SOH fleet is the fleet-based spatial sensor SOH; and SOH cal is the calibration-based room sensor SOH; W indv is a weighting factor for the individual room sensor SOH; W overlap is a weighting factor for the overlap room sensor SOH; W hist is a weighting factor for the history-based room sensor SOH; W fleet is a weighting factor for the fleet-based spatial sensor SOH; and W cal is a weighting factor for the calibration-based room sensor SOH.

[0048] The weighting factors may be determined based on system-specific factors, and in one embodiment, the overall relationship between the weighting factors is as follows: Windv+Woverlap+Whist+Wfleet+Wcal=1

[0049] The integrated SOH is compared to a threshold SOH (314) to evaluate its suitability for use. If the integrated SOH is greater than the threshold SOH (314)(1), this is an indication that the object space sensor 41 is suitable for use in monitoring the spatial environment located proximal to the vehicle 10, and this result can be displayed to the vehicle operator via one of the operator interface devices of the HMI system 42 (318). This result can also be communicated to the off-board controller 280.

[0050] If the integrated SOH is less than the threshold SOH (314)(0), this is an indication that the object space sensor 41 is not suitable for use in monitoring the spatial environment proximal to the vehicle 10, and this result may be displayed to the vehicle operator via one of the operator interface devices of the HMI system 42 (316). This result may also be communicated to the off-board controller 280, which may communicate the result to a service center for scheduling vehicle service. The controller may also perform mitigation efforts using information from other of the object space sensors 41' to monitor the field of view.

[0051] The flowchart and block diagrams in the flowcharts illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the block or flowcharts may represent a module, segment, or portion of code that includes one or more executable instructions for implementing the specified logical function(s). It should also be understood that each block of the block diagrams and / or flowchart representations and combinations of blocks in the block diagrams and / or flowchart representations may be implemented by special-purpose hardware-based systems that perform the specified functions or operations, or combinations of special-purpose hardware and computer instructions.These computer program instructions may also be stored in a computer-readable medium that can direct a controller or other programmable data processing device to function in a particular manner such that the instructions stored in the computer-readable medium produce an article of manufacture, including instructions that implement the function / operation specified in the flowchart and / or block diagram block or blocks.

[0052] While the detailed description and drawings or figures support and describe the present teachings, the scope of the present teachings is defined solely by the claims. While some of the best modes and other modes for carrying out the present teachings have been described in detail, various alternative designs and embodiments are possible for practicing the present teachings, as defined in the appended claims.

Claims

[1] A method for evaluating an object space sensor (41) arranged on an autonomous vehicle (10), wherein the object space sensor (41) is arranged to monitor a spatial environment near the autonomous vehicle (10), and wherein the autonomous vehicle (10) includes a telematics device for communicating with an off-board control (280), the method comprising: Determining a first state of health parameter, SOH parameter, for the object space sensor (41) based on internal monitoring of the object space sensor (41), wherein a first field of view (43) is associated with the object space sensor (41); Determining a second SOH parameter for the object space sensor (41) based on a correlation analysis of data generated by a second space sensor (41') arranged on the autonomous vehicle (10); Determining a third SOH parameter for the object space sensor (41) based on historical data for the object space sensor (41) associated with a geographic location; Determining a fourth SOH parameter for the object space sensor (41) based on a correlation analysis with an input from a third space sensor disposed on a second vehicle, wherein the input from the third space sensor includes data associated with the geographical position; Determining a fifth SOH parameter for the object space sensor (41) based on a correlation analysis with an input from a calibration space sensor located on a calibration vehicle, the input from the calibration space sensor including data associated with the geographical position; Determining an integrated SOH parameter for the object space sensor (41) based on the first, second, third, fourth and fifth SOH parameters; Comparing the integrated SOH parameter with a threshold SOH; Displaying a result of the comparison of the integrated SOH parameter with the threshold SOH via a user interface device if the integrated SOH parameter is less than the threshold SOH, the result indicating that the object space sensor (41) is not suitable for use in monitoring the spatial environment in the vicinity of the vehicle (10); and Transmitting the result to the off-board controller (280) to plan a vehicle service based on the result. [2] The method of claim 1, wherein determining the integrated SOH parameter for the object space sensor (41) based on the first, second, third, fourth, and fifth SOH parameters comprises determining a weighted average of the first, second, third, fourth, and fifth SOH parameters. [3] The method of claim 1, wherein the second SOH parameter is determined based on a correlation analysis of data generated by the second spatial sensor (41'), the second spatial sensor (41') having a second field of view (43') overlapping with a portion of the first field of view (43). [4] The method of claim 3, wherein a low value for the SOH parameters is associated with a low value output by the correlation analysis, and a high value for the SOH parameters is associated with a high value output by the correlation analysis. [5] The method of claim 1, wherein the third SOH parameter is determined based on historical data for the object space sensor (41) associated with the geographic location and located in an orientation consistent with the data for the object space sensor (41). [6] The method of claim 5, wherein a low value for the third SOH parameter is associated with a low value output by the correlation analysis, and a high value for the third SOH parameter is associated with a high value output by the correlation analysis. [7] The method of claim 1, wherein the fourth SOH parameter is determined based on a correlation analysis with the input from the third spatial sensor located on the second vehicle associated with the geographical position and in an orientation consistent with the data from the object spatial sensor (41). [8] The method of claim 7, wherein a low value for the fourth SOH parameter is associated with a low value output by the correlation analysis, and a high value for the fourth SOH parameter is associated with a high value output by the correlation analysis. [9] The method of claim 1, wherein the fifth SOH parameter is determined based on a correlation analysis with the input from the calibration space sensor located on the calibration vehicle associated with the geographical position and in an orientation consistent with the data from the object space sensor (41).

Images