Intelligent vehicle disablement

Abstract

A vehicle control system includes: a sensor for detecting a vehicle performance characteristic; and a processor for determining a severity of a vehicle system fault in response to the vehicle performance characteristic. The processor determines a security disabled location in response to a vehicle system fault. The processor generates a disable delay request indicating a secure disable location and a vehicle performance characteristic. The vehicle controller controls the vehicle to advance to the secure disabled position in response to the disabled delay request.

Description

Technical Field

[0001] The present disclosure generally relates to disabling vehicle systems in response to fault detection to protect vehicle hardware, and more specifically to methods and apparatus for receiving vehicle system fault notification, determining the severity of the vehicle system fault, determining the location of the vehicle, and facilitating additional vehicle functionality to allow the vehicle to be relocated to a preferred stopping area. Background Art

[0002] The operation of modern vehicles is becoming increasingly automated, i.e., capable of providing driving control with less and less driver intervention. Vehicle automation has been categorized into different numerical levels ranging from zero (corresponding to no automation with full human control) to five (corresponding to full automation with no human control). Various automatic driver assistance systems (such as cruise control, adaptive cruise control, and parking assistance systems) correspond to lower levels of automation, while truly "driverless" vehicles correspond to higher levels of automation. These driver assistance systems rely on various sensors and communication systems for determining the vehicle's position within the road and for detecting neighboring vehicles and other obstacles.

[0003] While the need to protect vehicle operation during damaging or destructive operating conditions is clear, it is also desirable to activate any vehicle protection algorithms in a safe position. It is desirable to overcome the foregoing problems in order to provide a system and method for vehicle system disabling for vehicle propulsion and driver assistance systems. Moreover, other desirable features and characteristics of the present invention will become apparent from the subsequent detailed description and the appended claims, taken in conjunction with the accompanying drawings and the foregoing technical field and background. Summary of the invention

[0004] Disclosed herein are vehicle control methods and systems and related electrical systems for supplying motor systems, methods for manufacturing such systems, and methods for operating such systems, as well as motor vehicles and other equipment, such as aircraft, ships, wind turbines, and other electric vehicles equipped with onboard propulsion systems. By way of example and not limitation, various embodiments of systems for mitigating vehicle hardware damage while allowing the vehicle to continue operating until in a preferred stopping position are presented.

[0005] According to aspects of the present disclosure, a vehicle disabling system for a host vehicle includes: a sensor for detecting or predicting a characteristic of a vehicle system failure; a processor for determining a severity of the vehicle system failure in response to the characteristic, for determining a safety disabling position in response to the severity of the vehicle system failure and a current position and state of the host vehicle, and for generating vehicle control data in response to the safety disabling position; and a vehicle controller for controlling the vehicle in response to the vehicle control data.

[0006] According to aspects of the present disclosure, the processor is further operable to determine a duration of a navigation time between the current position and the safe disabling position, and is operable to determine a maximum disabling delay responsive to a severity of the vehicle system fault. The vehicle control data is generated responsive to the maximum disabling delay being greater than the navigation time.

[0007] According to aspects of the present disclosure, the characteristic of the vehicle system fault is indicative of lateral control degradation, and the processor is further operable to estimate the host vehicle lane position in response to the lateral control degradation.

[0008] According to aspects of the present disclosure, the characteristic of the vehicle system fault is indicative of longitudinal control degradation, and the processor is further operable to estimate vehicle speed in response to the longitudinal control degradation.

[0009] According to aspects of the present disclosure, the vehicle control data includes a motion path between a current position and a safety disable position.

[0010] According to aspects of the present disclosure, the processor is further operable to generate a user alert indicating the safety disabled position for presentation at the user interface.

[0011] According to an aspect of the present disclosure, a processor is configured to disable a vehicle system in response to a severity of a vehicle system fault exceeding a threshold severity.

[0012] According to an aspect of the present disclosure, a processor is configured to disable a vehicle system in response to determining that the host vehicle reaches a safe disable position.

[0013] According to aspects of the present disclosure, the processor is configured to delay disabling of the vehicle system in response to a severity of the vehicle system fault and a current position not being a safe disabling position.

[0014] According to aspects of the present disclosure, a method for disabling a vehicle system includes: detecting characteristics of a vehicle system failure, determining a severity of the vehicle system failure in response to the characteristics, determining a safety disable position in response to the severity of the vehicle system failure and a current position of a host vehicle, generating vehicle control data in response to the safety disable position, and controlling the vehicle to the safety disable position in response to the vehicle control data.

[0015] According to aspects of the present disclosure, the characteristic of the vehicle system fault is indicative of at least one of lateral control degradation and longitudinal control degradation.

[0016] According to aspects of the present disclosure, the safety disabling position is also determined in response to contextual data and map data received from the ADAS algorithm.

[0017] According to aspects of the present disclosure, a disable delay duration is determined in response to the safety disable position, and vehicle control data is generated in response to the disable delay duration.

[0018] According to aspects of the present disclosure, a disable delay duration is determined in response to a severity of a vehicle system fault and a safety disable position.

[0019] According to aspects of the present disclosure, a user alert is generated in response to a severity of a vehicle system fault exceeding a threshold severity.

[0020] According to aspects of the present disclosure, a delay in a disabling event is requested in response to the nature and severity of a vehicle system fault.

[0021] According to aspects of the present disclosure, a disable delay duration is determined responsive to a severity of a vehicle system fault and a safety disable position, and the disable delay duration is displayed to a vehicle operator.

[0022] According to aspects of the present disclosure, a vehicle system is disabled in response to a severity of a vehicle system fault exceeding a threshold severity.

[0023] According to aspects of the present disclosure, a vehicle control system includes: a sensor for detecting a vehicle performance characteristic; and a processor for determining a severity of a vehicle system fault in response to the vehicle performance characteristic. A safety disable position is determined in response to the vehicle system fault. A disable delay request indicating the safety disable position and the vehicle performance characteristic is generated. A vehicle controller is included for controlling the vehicle to the safety disable position in response to the disable delay request.

[0024] According to aspects of the present disclosure, the vehicle controller is further operable to determine a disable delay duration in response to the current position and the safe disable position. The vehicle is controlled to the safe disable position in response to the disable delay duration being less than a threshold duration corresponding to a severity of the vehicle system fault. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Exemplary embodiments will be described below with reference to the accompanying drawings, wherein like numerals designate like elements, and wherein:

[0026] Figure 1 illustrates a control system associated with a vehicle according to various embodiments;

[0027] Figure 2 illustrates an exemplary environment for using an intelligent vehicle disabling system in accordance with various embodiments;

[0028] Figure 3 illustrates an exemplary configuration of a system for intelligent vehicle disabling according to various embodiments; and

[0029] Figure 4 A flow chart illustrating an exemplary method for enabling a system for intelligent vehicle disabling is shown in accordance with various embodiments. DETAILED DESCRIPTION

[0030] The following detailed description is merely exemplary in nature and is not intended to limit application and use. In addition, it is not intended to be bound by any express or implied theory presented in the aforementioned technical field, background technology, invention content or the following detailed description. As used herein, the term "module" refers to any hardware, software, firmware, electronic control component, processing logic and / or processor device (alone or in any combination), including but not limited to: application-specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), electronic circuits, processors (shared, dedicated or groups) and memories that execute one or more software or firmware programs, combinational logic circuits and / or other suitable components that provide the described functions.

[0031] Embodiments of the present disclosure may be described herein in terms of functions and / or logic block components and various processing steps. It should be understood that such block components may be implemented by any number of hardware, software and / or firmware components configured to perform a specified function. For example, embodiments of the present disclosure may employ various integrated circuit components, such as memory elements, digital signal processing elements, logic elements, lookup tables, etc., which may perform various functions under the control of one or more microprocessors or other control devices. In addition, those skilled in the art will appreciate that embodiments of the present disclosure may be practiced in conjunction with any number of systems, and the systems described herein are only exemplary embodiments of the present disclosure.

[0032] For the sake of brevity, conventional techniques related to other functional aspects of signal processing, data transmission, signaling, control, machine learning, image analysis, and systems (and the various operating components of the systems) may not be described in detail herein. In addition, the connecting lines shown in the various drawings included herein are intended to represent example functional relationships and / or physical couplings between various elements. It should be noted that many alternative or additional functional relationships or physical connections may exist in embodiments of the present disclosure.

[0033] refer to Figure 1 According to various embodiments, the control system 100 is associated with a vehicle 10 (also referred to herein as a "host vehicle"). In general, the control system (or simply "system") 100 provides control of various actions of the vehicle 10 (e.g., torque control) established by reinforcement learning (RL) that is or can be stored in a DNN-type model that controls operations in response to data from vehicle inputs, for example, as described below in conjunction with Figure 2-Figure 4 Further described in more detail.

[0034] In various exemplary embodiments, the system 100 provides a process that allows DNN to be used in an ACC behavior prediction model for algorithms controlling torque and speed in the embedded controller software of the host vehicle 10 using the system 100. The system 100 enables learning of driver preferences for following distances for different vehicles, such as a target vehicle, and categorizes the driver's preferences based on driving scenarios (e.g., traffic signs, stop-and-go traffic, city driving, etc.). The system 100 builds a knowledge base for target vehicles that follows performance preferences using a Q matrix by leveraging online and historical driver and environment information.

[0035] like Figure 1 As depicted, vehicle 10 generally includes a chassis 12, a body 14, front wheels 16, and rear wheels 18. Body 14 is disposed on chassis 12 and substantially surrounds components of vehicle 10. Body 14 and chassis 12 may together form a frame. Wheels 16-18 are each rotationally coupled to chassis 12 near respective corners of body 14. In various embodiments, wheels 16, 18 comprise a wheel assembly that also includes a respectively associated tire.

[0036] In various embodiments, the vehicle 10 is autonomous or semi-autonomous, and the control system 100 and / or its components are incorporated into the vehicle 10. The vehicle 10 is, for example, a vehicle that is automatically controlled to transport passengers from one location to another. The vehicle 10 is depicted as a passenger car in the illustrated embodiment, but it should be understood that any other means of transportation may also be used, including motorcycles, trucks, sport utility vehicles (SUVs), recreational vehicles (RVs), boats, aircraft, etc.

[0037] As shown, the vehicle 10 generally includes a propulsion system 20, a transmission system 22, a steering system 24, a braking system 26, a canister purge system 31, one or more user input devices 27, a sensor system 28, an actuator system 30, at least one data storage device 32, at least one controller 34, and a communication system 36. In various embodiments, the propulsion system 20 may include an internal combustion engine, an electric machine such as a traction motor, and / or a fuel cell propulsion system. The transmission system 22 is configured to transmit power from the propulsion system 20 to the wheels 16 and 18 according to a selectable speed ratio. According to various embodiments, the transmission system 22 may include a step-ratio automatic transmission, a continuously-variable transmission, or other suitable transmission.

[0038] Braking system 26 is configured to provide braking torque to wheels 16 and 18. In various embodiments, braking system 26 may include friction brakes, brake-by-wire brakes, a regenerative braking system such as an electric motor, and / or other suitable braking systems.

[0039] The steering system 24 affects the positioning of the wheels 16 and / or 18. Although depicted as including a steering wheel for illustrative purposes, in certain embodiments contemplated within the scope of the present disclosure, the steering system 24 may not include a steering wheel.

[0040] The controller 34 includes at least one processor 44 (and neural network 33) and a computer-readable storage device or medium 46. As described above, in various embodiments, the controller 34 (e.g., its processor 44) provides data related to the expected future path of the vehicle 10 to the steering control system 84 in advance, including expected future steering instructions, for controlling steering for a limited period of time in the event that communication with the steering control system 84 becomes unavailable. In addition, in various embodiments, the controller 34 communicates with the steering control system 84 via the communication system 36 (e.g., via a communication bus and / or a transmitter ( Figure 1 (not depicted)) provides communication to the steering control system 84.

[0041] In various embodiments, the controller 34 includes at least one processor 44 and a computer readable storage device or medium 46. The processor 44 can be any custom or commercially available processor, a central processing unit (CPU), a graphics processing unit (GPU), an auxiliary processor of several processors associated with the controller 34, a semiconductor-based microprocessor (in the form of a microchip or chipset), any combination thereof, or any device generally used to execute instructions. For example, the computer readable storage device or medium 46 can include volatile and non-volatile storage in read-only memory (ROM), random access memory (RAM), and keep-alive memory (KAM). KAM is a persistent or non-volatile memory that can be used to store multiple neural networks and various operating variables when the processor 44 loses power. The computer readable storage device or medium 46 can be implemented using any of several known memory devices such as the following: PROM (programmable read-only memory), EPROM (electrical PROM), EEPROM (electrically erasable PROM), flash memory, or any other electrical, magnetic, optical, or combination memory device capable of storing data (some of which represent executable instructions used by the controller 34 to control the vehicle 10).

[0042] The instructions may include one or more separate programs, each of which includes an ordered list of executable instructions for implementing logical functions. The instructions, when executed by the processor 44, receive and process signals from the sensor system 28, execute logic, calculations, methods and / or algorithms for automatically controlling components of the vehicle 10, and generate control signals to the actuator system 30 to automatically control components of the vehicle 10 based on the logic, calculations, methods and / or algorithms. Although in Figure 1 Only one controller 34 is shown, but embodiments of the vehicle 10 may include any number of controllers 34 that communicate via any suitable communication medium or combination of communication mediums and collaborate to process sensor signals, execute logic, calculations, methods and / or algorithms, and generate control signals to automatically control features of the vehicle 10.

[0043] like Figure 1 As shown, in addition to the above-mentioned steering system 24 and controller 34, the vehicle 10 generally includes a chassis 12, a body 14, front wheels 16 and rear wheels 18. The body 14 is arranged on the chassis 12 and substantially surrounds the components of the vehicle 10. The body 14 and the chassis 12 can together form a frame. The wheels 16-18 are each rotationally coupled to the chassis 12 near the corresponding corners of the body 14. In various embodiments, the wheels 16, 18 include a wheel assembly, which also includes a tire associated with each.

[0044] In various embodiments, the vehicle 10 is an autonomous vehicle, and the control system 100 and / or its components are incorporated into the vehicle 10. The vehicle 10 is, for example, a vehicle that is automatically controlled to transport passengers from one location to another. The vehicle 10 is depicted as a passenger car in the illustrated embodiment, but it should be understood that any other means of transportation may also be used, including motorcycles, trucks, sport utility vehicles (SUVs), recreational vehicles (RVs), boats, aircraft, etc.

[0045] The controller 34 comprises a vehicle controller that operates based on the output of the neural network 33 model. In an exemplary embodiment, a feed-forward operation may be applied to an adjustment factor that is a continuous output of the neural network 33 model to generate a control action for a desired torque or other similar action (e.g., in the case of a continuous neural network 33 model, a continuous APC / SPARKS prediction value is the output).

[0046] In various embodiments, the one or more user input devices 27 receive input from one or more passengers of the vehicle 10 (and the driver 11). In various embodiments, the input includes a desired travel destination for the vehicle 10. In certain embodiments, the one or more input devices 27 include an interactive touch screen in the vehicle 10. In certain embodiments, the one or more input devices 27 include a speaker for receiving audio information from the passenger. In certain other embodiments, the one or more input devices 27 may include one or more other types of devices and / or user devices (e.g., smart phones and / or other electronic devices) that may be coupled to the passenger.

[0047] The sensor system 28 includes one or more sensors 40a-40n that sense observable conditions of the external environment and / or the internal environment of the vehicle 10. The sensors 40a-40n include, but are not limited to, radar, lidar, global positioning system, optical camera, thermal imager, ultrasonic sensor, inertial measurement unit, and / or other sensors.

[0048] The actuator system 30 includes one or more actuators 42a-42n that control one or more vehicle features such as, but not limited to, the canister purge system 31, the air intake system 38, the propulsion system 20, the transmission system 22, the steering system 24, and the braking system 26. In various embodiments, the vehicle 10 may also include Figure 1 Not shown are interior and / or exterior vehicle features, such as various doors, trunk, and cabin features, such as air, music, lighting, touch screen display components (such as those used in conjunction with a navigation system), etc.

[0049] The data storage device 32 stores data for automatically controlling the vehicle 10, including storing data of the DNN established by the RL for predicting the driver's behavior for vehicle control. In various embodiments, the data storage device 32 stores the machine learning model of the DNN and other data models established by the RL. The model established by the RL can replace the DNN behavior prediction model or the model established by the RL (see Figure 2 , DNN prediction model or RL prediction model). In an exemplary embodiment, the DNN does not require separate training, instead, the DNN behavior prediction model (i.e., DNN prediction model) is implemented using a set of learning functions. In various embodiments, the neural network (i.e., DNN behavior prediction model) can be established by RL or trained by a remote system through a supervised learning method, and communicated or supplied in the vehicle 10 (wirelessly and / or wiredly) and stored in the data storage device 32. The DNN behavior prediction model can also be trained via supervised or unsupervised learning based on input vehicle data of the main vehicle operation and / or sensory data about the main vehicle operating environment.

[0050] The data storage device 32 is not limited to control data, as other data may also be stored in the data storage device 32. For example, route information may also be stored within the data storage device 32 - that is, a collection of road segments (geographically associated with one or more of the defined maps) that together define a route that a user may take to travel from a starting location (e.g., the user's current location) to a target location. As will be appreciated, the data storage device 32 may be part of the controller 34, separate from the controller 34, or part of the controller 34 and part of a separate system.

[0051] The controller 34 implements the logic model established by RL or for the DNN based on the DNN behavior model that has been trained using a set of values, and the controller 34 includes at least one processor 44 and a computer-readable storage device or medium 46. The processor 44 can be any customized or commercially available processor, a central processing unit (CPU), a graphics processing unit (GPU), an auxiliary processor in several processors associated with the controller 34, a semiconductor-based microprocessor (in the form of a microchip or chipset), any combination thereof, or any device generally used to execute instructions. For example, the computer-readable storage device or medium 46 may include volatile and non-volatile storage in a read-only memory (ROM), a random access memory (RAM), and a keep-alive memory (KAM). KAM is a persistent or non-volatile memory that can be used to store various operating variables when the processor 44 loses power. The computer readable storage device or medium 46 may be implemented using any of several known memory devices such as a PROM (programmable read-only memory), an EPROM (electrical PROM), an EEPROM (electrically erasable PROM), flash memory, or any other electrical, magnetic, optical, or combination memory device capable of storing data, some of which represent executable instructions used by the controller 34 to control the vehicle 10.

[0052] The instructions may include one or more separate programs, each of which includes an ordered list of executable instructions for implementing logical functions. The instructions, when executed by the processor 44, receive and process signals from the sensor system 28, execute logic, calculations, methods and / or algorithms for automatically controlling components of the vehicle 10, and generate control signals to the actuator system 30 to automatically control components of the vehicle 10 based on the logic, calculations, methods and / or algorithms. Although in Figure 1 Only one controller 34 is shown, but embodiments of the vehicle 10 may include any number of controllers 34 that communicate via any suitable communication medium or combination of communication mediums and collaborate to process sensor signals, execute logic, calculations, methods and / or algorithms, and generate control signals to automatically control features of the vehicle 10.

[0053] The communication system 36 is configured to wirelessly communicate information to and from other entities 48, such as, but not limited to, other vehicles ("V2V" communications), infrastructure ("V2I" communications), remote transportation systems, and / or user devices (regarding Figure 2 In an exemplary embodiment, the communication system 36 is a wireless communication system configured to communicate via a wireless local area network (WLAN) using the IEEE 802.11 standard or by using cellular data communications. However, additional or alternative communication methods, such as dedicated short-range communication (DSRC) channels, are also considered within the scope of the present disclosure. A DSRC channel refers to a one-way or two-way short-range to medium-range wireless communication channel designed specifically for automotive use and a corresponding set of protocols and standards.

[0054] In various embodiments, the communication system 36 is used for communication between the controllers 34, including data related to the expected future path of the vehicle 10, including expected future steering instructions. Additionally, in various embodiments, the communication system 36 can facilitate communication between the steering control system 84 and / or more other systems and / or devices.

[0055] In certain embodiments, the communication system 36 is also configured for communication between the sensor system 28, the input device 27, the actuator system 30, one or more controllers (e.g., the controller 34), and / or more other systems and / or devices. For example, the communication system 36 may include any combination of a controller area network (CAN) bus and / or direct wiring between the sensor system 28, the actuator system 30, the one or more controllers 34, and / or one or more other systems and / or devices. In various embodiments, the communication system 36 may include a communication system for communicating with one or more devices and / or systems of the vehicle 10, a passenger's device (e.g., Figure 2 One or more transceivers for communicating with one or more sources of user equipment 54), and / or remote information (e.g., GPS data, traffic information, weather information, etc.).

[0056] Now go to Figure 2 , an exemplary environment 200 for using an intelligent vehicle disabling system according to various embodiments is shown. The exemplary environment 200 may include a host vehicle 215, neighboring vehicles 225, a road 210, a bridge 220, and an exit ramp 230.

[0057] As electronic control systems and vehicle sensors become more ubiquitous in automobiles, vehicle control systems have become able to detect and diagnose problems with various vehicle systems. These vehicle control systems are able to disable malfunctioning vehicle systems before the vehicle systems suffer permanent damage, such as disabling the engine when the engine temperature exceeds a threshold for a predetermined length of time, or disabling an automatic driver assistance system when a critical sensor has failed.

[0058] With the advent of more advanced driving systems, vehicle control systems are increasingly able to establish vehicle situational awareness, such as determining the current vehicle location, the presence of other neighboring vehicles and objects, weather and traffic conditions, etc. Currently proposed systems are configured to integrate vehicle disabling or degradation systems with more advanced situational awareness to avoid vehicle disabling or degradation of vehicle operation in undesirable locations or situations. For example, if the driver is on a highway, the intelligent vehicle disabling system can warn the driver to control the vehicle to a safe location, such as the shoulder of the road, a countdown timer can be provided until the vehicle is disabled, or the vehicle can be controlled to a safe location even before the vehicle is disabled. The intelligent vehicle disabling system utilizes existing and developing vehicle sensor systems with existing vehicle control systems to ensure safe operation during vehicle disabling.

[0059] The intelligent vehicle disabling system can be configured to coordinate control for a fail-safe mode through an explicit handshake between an advanced driver assistance system (ADAS) and propulsion and chassis control to enable the vehicle to be placed in a safe environment before disabling vehicle propulsion, or to place the vehicle in a contingent state through systematic coordination and novel ADAS control adaptation. In certain exemplary embodiments, the intelligent vehicle disabling system can redirect and / or restrict vehicle motion to a safe position via autonomous vehicle control when a vehicle system failure that may restrict vehicle motion is pending. The intelligent vehicle disabling system in the host vehicle 215 can receive data indicating vehicle conditions and an impending disabling event from the vehicle disabling system. The intelligent vehicle disabling system can then receive contextual data, such as the location of a neighboring vehicle 225, geographic location data, map data, etc. from the ADAS system. The intelligent vehicle disabling system can determine a predicted disabling position A in response to the impending disabling event and the contextual data. If the disabling position A is determined to be a high-risk area, such as in the left lane on the bridge 220, the intelligent vehicle disabling system can determine a safe disabling position B in response to the nature of the disabling event and the contextual data. For example, if the vehicle condition is an engine overheat event, the intelligent vehicle disabling system may determine a safe disabling position B and send this position to the ADAS vehicle controller, as well as a disable override command to the vehicle disabling system. The ADAS vehicle controller may then control the vehicle to the safe disabling position B. In response to the disable override command, the vehicle disabling system may extend the time to the vehicle disabling event, may degrade vehicle performance, such as reducing the number of active engine pistons or adjusting and / or reducing the peak magnitude of vehicle propulsion current, in order to minimize possible vehicle system damage, until the safe disabling position B is reached.

[0060] In an exemplary embodiment where the vehicle disabling system indicates a sensor failure (such as a lidar, etc.) required by ADAS, the intelligent vehicle disabling can control the vehicle control system to use data from other sensors (such as GPS, cameras, infrared sensors, V2V communication systems, etc.) to control the main vehicle 215 to a safe disabling position B. In some cases, controlling vehicle navigation with a subset of operating sensors may not result in the same control accuracy as navigating with a complete set of operating sensors. In order to warn the driver of any degradation of the ADAS vehicle controller, the intelligent vehicle disabling system can notify the driver of an impending disabling event and provide an ADAS control override control so that the driver can immediately disable the vehicle during the intelligent vehicle disabling operation. Therefore, if the main vehicle may contact a neighboring object and / or a neighboring vehicle B when navigating to the safe disabling position B, the driver can disable the vehicle before the contact event. Alternatively, in certain cases where the safety control of the main vehicle 215 cannot be performed, the ADAS controller can return control of the vehicle to the driver.

[0061] Now go to Figure 3 , an exemplary system 300 for using an intelligent vehicle disabling system according to various embodiments is shown. The exemplary system 300 may include a user interface 310, an autonomous driving control system (ADCS) processor 330, a vehicle controller 360, a powertrain control system 370, a brake controller 380, and a steering controller 390. Although the vehicle controller 360 and the ADCS processor 330 are described as discrete units in the following exemplary embodiments, any of the components or functions may be combined into any combination, including a single vehicle control processor operable to execute a vehicle control algorithm, an ADCS algorithm, an ADAS algorithm, a vehicle disabling algorithm, and an intelligent vehicle disabling algorithm.

[0062] The user interface 310 may include user input and / or user communication devices for communicating information to the driver or autonomous vehicle user. The communication device may include a display, such as a center console infotainment display, a warning light, an audible notification or alarm, tactile feedback, etc. The vehicle controller 360 and the ADCS processor 330 may receive user input from the user interface 310, such as smart vehicle disable confirmation or preference, and may display warnings, operating instructions, or navigation instructions to the user. For example, the ADCS processor 330 may provide a prompt to the user to request user confirmation that the vehicle system shutdown is expected to be delayed to navigate to a safer disabled position. In some cases, the user may desire to shut down the vehicle immediately, rather than continue to operate to a safe disabled position and risk additional vehicle system damage.

[0063] In certain exemplary embodiments, the vehicle controller 360 may be configured to receive sensor data from vehicle sensors such as an inertial measurement unit (IMU), wheel speed sensors, engine temperature sensors, etc., as well as control data such as steering wheel position, throttle position, brake position, etc. In a vehicle equipped with ADAS, the vehicle controller 360 may also receive control signals from the ADAS controller indicating desired vehicle speed, steering direction, brake application, etc. The vehicle controller 360 is configured to generate control signals to couple to the powertrain control system 370, the brake controller 380, and the steering controller 390 to control vehicle movement.

[0064] The vehicle controller 360 may be configured to monitor vehicle data via a vehicle controller area network (CAN) bus and / or ADAS algorithms. In response to vehicle data outside of a normal operating range, such as engine temperature, sensor failure, etc., the vehicle controller 360 may disable vehicle functions, such as propulsion or ADAS algorithms, or may shut down vehicle operation entirely. The vehicle controller 360 may couple this disable control signal indicating a shutdown command to the appropriate control systems (ADCS, propulsion, braking, and steering).

[0065] The ADCS processor 330 can be configured to receive a disabling control signal, and determines the severity of the system and system failure to be disabled in response to the disabling control signal. The ADCS processor 330 can determine whether the failure mode can be delayed subsequently. The delay determination can be made in response to the severity of the system and system failure to be disabled. In addition, contextual data (such as the position of traffic density, adjacent vehicles and other obstacles and / or the type of road being advanced) can be used to determine whether the delay is feasible. In response to feasible system delays, the ADCS processor 330 can then determine the safe disabling position in response to the contextual data from the ADAS controller and the data from other vehicle sensors. Considering the duration of the severity of system failure, system failure and possible disabling system delay, if the safe disabling position can be navigated, the ADCS processor 330 can request to delay the disabling system delay subsequently, and send the safe disabling position, navigation data and / or vehicle control data to the vehicle controller 360 to control the vehicle towards the safe disabling position. In addition, the ADCS processor 330 can send control data to the vehicle controller 360 to restrict or limit the use of certain vehicle systems, such as inhibiting vehicle acceleration, inhibiting transmission shifting and / or deceleration, and other remedial actions to prevent further damage to the vehicle system. Once the vehicle has reached a safe disable position or a disable delay is no longer possible, the ADCS processor 330 can send a complete disable of a vehicle system or feature to the vehicle controller 360.

[0066] Now go to Figure 4, a method 400 for operating an intelligent vehicle disabling system according to various embodiments is shown. The exemplary method 400 is first operable to receive system data from one or more vehicle data sources such as vehicle sensors, vehicle control systems, and / or external vehicle data sources such as V2V, V2I, and vehicle-to-everything (V2X). The method 400 can then be configured to identify 410 a fault mode of the vehicle in response to the received vehicle data.

[0067] The method 400 next determines 415 whether the fault mode is lateral control degradation. Vehicle lateral control degradation is a condition in which the vehicle's ability to stay in its lane is impaired. This may be due to several factors, including faulty sensors, damaged tires, and / or poor road conditions. Sensors used to measure the lateral positioning and orientation of the vehicle may become faulty, resulting in inaccurate readings. This may make it difficult for the lateral control system to keep the vehicle in its lane. Damaged tires may cause the vehicle to wander or drift, and driving on rough or slippery roads may also make it difficult for the lateral control system to keep the vehicle in its lane.

[0068] In the event that vehicle lateral control is degraded, method 400 next determines 420 whether an electronic power steering (EPS) fault has occurred. EPS uses an electric motor to help turn the steering rack in the car. EPS systems have sensors that determine how much force is used to turn the wheels. EPS can improve handling and steering feel, and can improve vehicle safety by adapting steering torque to vehicle speed. EPS may fail due to problems with the installed electric motor, such as overheating, or the system being infiltrated by water, dust, or other contaminants.

[0069] In response to the determination of the EPS failure, the method 400 next determines the severity of the EPS failure 422. The method 400 then determines 425 whether a failure mode of the vehicle can be delayed in response to the severity of the EPS failure. If the failure mode cannot be delayed, the method 400 next disables 470 the vehicle system.

[0070] If the failure mode can be delayed, the method 400 next determines a safe disabling position in response to sensor and map data from an ADAS controller, etc. In response to the determination of the safe disabling position, the method 400 next requests 435 a delay in disabling the vehicle. The duration of the delay may depend on the distance to the safe disabling position, the severity of the EPS failure, the density of neighboring vehicles, the availability of alternative safe disabling positions, etc.

[0071] After receiving confirmation of the request for a delay in vehicle disabling from the vehicle disabling system, the vehicle can be controlled toward the safe disabling position. This control can be performed by an automatic driver system, a driver assistance system, and / or in response to instructions and / or warnings provided to the driver. The communication can be further enhanced by displaying the time remaining in the requested delay. For example, a display on a center console infotainment system can display an indication of the time remaining before the delayed vehicle disabling event. After the vehicle reaches the safe disabling position, the method 400 can disable 470 the vehicle system.

[0072] In certain exemplary embodiments, the method 400 may employ alternative control algorithms based on system failures. For example, in the case of a lateral control failure caused by uncertainties in actuator and sensor measurements that prevents the ADAS system from ensuring lane centering, the method 400 may seek an acceptable safety margin of error and ensure that the vehicle stays within the bounded error. Data from other vehicle sensors (e.g., camera and / or GPS location data, etc.) may be used to control the vehicle to stay within the bounded error.

[0073] If lateral control is not degraded, method 400 may then determine 445 whether longitudinal control has been degraded. Degraded vehicle longitudinal control is a condition in which the vehicle's ability to maintain a desired speed or a desired distance from the vehicle ahead is impaired. This may be caused by several factors, including defective sensors, damaged actuators, and / or software failures. Sensors used to measure vehicle speed, distance to the vehicle ahead, and other factors may become faulty over time. This may result in inaccurate readings, which may damage the longitudinal control system. Actuators used to control the vehicle's throttle, brakes, and other systems may also become damaged over time. This may result in the vehicle's response to commands to the longitudinal control system being impaired, which may result in degradation. In addition, the software used to control the longitudinal control system may also be affected, causing the system to operate in an impaired state or with reduced responsiveness.

[0074] In response to the determination of longitudinal control degradation 445, method 400 next determines 450 whether a propulsion system fault has occurred. If a propulsion system fault has occurred, method 400 next determines 455 whether the fault mode can be delayed. If the fault mode cannot be delayed, method 400 then disables 470 the vehicle system.

[0075] If the fault mode determined in response to the propulsion fault can be delayed, the method 400 next determines 458 a safe disable position and requests 460 a propulsion mode downgrade delay to the ECM in response to the safe disable position. The method 400 next controls the vehicle to the safe disable position using the ADAS fault mode control, or may request the driver to control the vehicle to the safe disable position. The driver may also be requested to reduce the vehicle speed when navigating to the safe disable position.

[0076] Although at least one exemplary embodiment has been presented in the foregoing detailed description, it should be understood that there are a large number of variations. It should also be understood that the exemplary embodiment or multiple exemplary embodiments are merely examples and are not intended to limit the scope, applicability or configuration of the present disclosure in any way. On the contrary, the foregoing detailed description will provide a convenient roadmap for implementing the exemplary embodiment or multiple exemplary embodiments for those skilled in the art. It should be understood that various changes may be made to the functions and arrangements of the elements without departing from the scope of the present disclosure as set forth in the attached claims and their legal equivalents.

Claims

1. A vehicle disabling system for a host vehicle, comprising: A sensor for predicting or detecting characteristics of a vehicle system failure; a processor configured to: determine a severity of the vehicle system fault in response to the characteristic, determine a safety disable position in response to the severity of the vehicle system fault and a current position and state of the host vehicle, and generate vehicle control data in response to the safety disable position; as well as A vehicle controller is configured to control a vehicle in response to the vehicle control data.

2. A vehicle disabling system for a host vehicle according to claim 1, wherein the processor is further operable to determine a duration of a navigation time between the current position and the safe disabling position, and to determine a maximum disabling delay responsive to the severity of the vehicle system fault, and wherein the vehicle control data is generated responsive to the maximum disabling delay being greater than the navigation time.

3. The vehicle disabling system of claim 1 , wherein the characteristic of the vehicle system fault indicates lateral control degradation, and wherein the processor is further operable to estimate a host vehicle lane position in response to the lateral control degradation. 4 . The vehicle disabling system of claim 1 , wherein the characteristic of the vehicle system fault indicates longitudinal control degradation, and wherein the processor is further operable to estimate vehicle speed in response to the longitudinal control degradation. 5 . The vehicle disabling system of claim 1 , wherein the vehicle control data includes a path of motion between the current position and the safe disabling position. 6 . The vehicle disabling system of claim 1 , wherein the processor is further operable to generate a user alert indicating the safety disabling position for presentation at a user interface. 7 . The vehicle disabling system of claim 1 , wherein the processor is configured to disable a vehicle system in response to the severity of the vehicle system fault exceeding a threshold severity. 8 . The vehicle disabling system of claim 1 , wherein the processor is configured to disable a vehicle system in response to determining that the host vehicle has reached the safe disabling position. 9 . The vehicle disabling system of claim 1 , wherein the processor is configured to delay disabling of a vehicle system in response to the severity of the vehicle system fault and the current position not being the safe disabling position.

10. A method of disabling a vehicle system, comprising: Features for detecting vehicle system failures; determining a severity of the vehicle system fault in response to the characteristic; determining a safety disable position in response to said severity of said vehicle system fault and a current position of a host vehicle; generating vehicle control data in response to the safety disable position; as well as A vehicle is controlled to the safety disable position in response to the vehicle control data.

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