Control subsystem and method for detecting and guiding response to tire failure of autonomous vehicle

Abstract

A control subsystem, a method, and a computer program product are provided for detecting a failure of a tire of an autonomous vehicle (AV) and making an appropriate response to the detected tire failure according to a specific situation. In this regard, the control subsystem includes processing circuitry configured to receive signals from microphone (s) carried by the AV. The processing circuitry is configured to evaluate a signal characteristic of the signal to identify the signal indicative of a tire fault. Where the tire fault is identified, the processing circuitry is configured to determine a type of tire fault based on the signal characteristic. The processing circuitry is further configured to determine a remedial action to take based at least in part on the type of tire fault. Different remedial measures are determined to be taken for different types of tire faults.

Description

Technical Field

[0001] Example embodiments relate generally to the detection of tire failures of an autonomous vehicle, and more particularly to the determination of remedial actions to be taken in response to a detected tire failure. Background Art

[0002] Manually operated vehicles, including manually driven tractor trailers, often rely on the driver to identify a situation where a vehicle tire has failed. A driver may identify a tire failure in a variety of ways. For example, in the event that a tire on a tractor trailer, such as a trailer tire, blows out, the driver may identify the tire failure as a result of a change in the steering characteristics of the tractor trailer. For example, a blown tire may cause the tractor trailer to veer sideways to one side, rather than traveling in a straight line. Additionally, a blown tire may cause the tractor trailer to vibrate or oscillate, including the steering of the tractor trailer.

[0003] As another example, a tire that is experiencing a thermal event, e.g., a tire that is on fire, such as during a sharp descent during which the brakes are firmly applied in a relatively continuous manner, may have at least some effect on the steering characteristics of a tractor trailer. In order to increase the likelihood that a tractor trailer driver will be alerted when a thermal event occurs with a tire, a warning system has been developed. In this regard, an axle on which the tire is mounted can be pressurized with a pressure maintained by a valve. In response to the thermal event, the valve is configured to open, such as by melting, thereby producing a whistle sound that is intended to alert the driver that the tire is experiencing a thermal event.

[0004] In response to a tire failure, the driver will typically slow down and move the vehicle off the road, such as onto the shoulder of the road. The failed tire can then be repaired or replaced, and any other damage caused by the tire failure can also be addressed if necessary.

[0005] With the advent of autonomous vehicles, including autonomous tractor trailers, a human operator is no longer required to be on board the autonomous vehicle in order to identify a tire failure and take appropriate action. However, it is still possible for an autonomous vehicle to experience a tire failure, and an autonomous vehicle that does experience a tire failure should still take appropriate action in order to repair the tire and avoid any problems that may arise from continued operation of the autonomous vehicle after a tire failure. Summary of the invention

[0006] According to an example embodiment, a control subsystem, method, and computer program product are provided to detect a failure of a tire of an autonomous vehicle and to respond appropriately to the detected tire failure as appropriate to the circumstances. In this regard, the control subsystem, method, and computer program product are configured to determine the type of tire failure and then customize the remedial action to be taken based on the type of tire failure, thereby facilitating an appropriate response to the tire failure. By detecting tire failure and determining the remedial action to be taken, the control subsystem, method, and computer program product of the example embodiment facilitates safe and timely repair of the tire and return of the autonomous vehicle to service.

[0007] In an example embodiment, a control subsystem of an autonomous vehicle (AV) is provided, the control subsystem comprising a processing circuit system configured to receive a signal from one or more microphones carried by the AV. The processing circuit system is further configured to evaluate a signal characteristic of the signal to identify a signal having a signal characteristic indicative of a tire failure. In the event that a tire failure is identified, the processing circuit system is configured to determine a type of tire failure based on the signal characteristic. The processing circuit system is further configured to determine a remedial action to be taken based at least in part on the type of tire failure. Different remedial actions are determined to be taken for different types of tire failures.

[0008] The processing circuit system of the example embodiment is configured to determine the type of tire failure by distinguishing between a tire experiencing a thermal event and a tire that has burst. In an example embodiment, the processing circuit system is configured to determine remedial action by updating the driving instructions of the AV to cause the AV to steer to the side of the road if the tire is experiencing a thermal event. In the case where the tire is experiencing a thermal event, the processing circuit system may be additionally or alternatively configured to determine to contact emergency services. The processing circuit system of the example embodiment may also be configured to determine remedial action by indicating that the AV needs tire repair in the case of a tire burst. In an example embodiment, the processing circuit system is configured to determine remedial action by causing an operations server to receive an alert about the identified tire failure.

[0009] The one or more microphones carried by the AV may include one or more microphones symmetrically mounted on opposite sides of the AV. The one or more microphones carried by the AV may include one or more microphones externally mounted on a tractor of the AV and one or more microphones externally mounted on a trailer of the AV. With respect to microphones mounted on the tractor, one or more microphones may be externally mounted on a lateral surface of the tractor, and one or more microphones may be externally mounted on a rearward surface of the tractor.

[0010] The processing circuitry of an example embodiment is configured to determine a remedial action based at least in part on one or more of a type of trailer of the AV, a load carried by the AV, characteristics of a road on which the AV is traveling, or a speed of the AV. In an example embodiment, the processing circuitry is configured to evaluate the signal characteristic by filtering the signal based on one or more of a frequency of the signal or an amplitude of the signal to distinguish signals having signal characteristics indicative of a tire failure from signals from other sources.

[0011] In another example embodiment, a method is provided that includes receiving signals from one or more microphones carried by an autonomous vehicle (AV) and evaluating signal characteristics of the signals to identify a signal having signal characteristics indicative of a tire failure. In the event that a tire failure is identified, the method includes determining a type of tire failure based on the signal characteristics. The method also includes determining a remedial action to be taken based at least in part on the type of tire failure. Different remedial actions are determined for different types of tire failures.

[0012] With respect to determining the type of tire failure, the method of the example embodiment distinguishes between a tire that is experiencing a thermal event and a tire that is bursting. In this example embodiment, the method may determine a remedial action by updating the driving instructions of the AV to cause the AV to steer to the side of the road if the tire is experiencing a thermal event. Additionally or alternatively, the method of this example embodiment may determine a remedial action by determining to contact emergency services if the tire is experiencing a thermal event. The method of this example embodiment may determine a remedial action by instructing the AV that a tire repair is needed if the tire is bursting.

[0013] The method of the example embodiment further determines a remedial action to take based at least in part on one or more of a type of trailer of the AV, a load carried by the AV, a characteristic of a road on which the AV is traveling, or a speed of the AV. In an example embodiment, the method evaluates the signal characteristic by filtering the signal based on one or more of a frequency of the signal or an amplitude of the signal to distinguish signals having signal characteristics indicative of a tire failure from signals from other sources. The method of the example embodiment determines the remedial action by causing an operations server to be alerted of a tire failure that has been identified.

[0014] The one or more microphones of the AV may include one or more microphones symmetrically mounted on opposite sides of the AV. In an example embodiment, the one or more microphones carried by the AV include one or more microphones externally mounted on a tractor of the AV and one or more microphones externally mounted on a trailer of the AV. For microphones mounted on the tractor, one or more microphones may be externally mounted on a lateral surface of the tractor, and one or more microphones may be externally mounted on a rearward surface of the tractor.

[0015] In another example embodiment, a computer program product is provided, the computer program product including at least one computer-readable storage medium having computer executable program code instructions stored therein, the storage medium may be non-transitory, the computer executable program code instructions including program code instructions configured to receive signals from one or more microphones carried by an autonomous vehicle (AV). The computer executable program code instructions also include program code instructions configured to evaluate signal characteristics of the signals to identify signals having signal characteristics indicative of tire failure. The computer executable program code instructions also include program code instructions configured to determine a type of tire failure based on the signal characteristics if a tire failure is identified. The computer executable program code instructions also include program code instructions configured to determine a remedial action to be taken based at least in part on the type of tire failure. Different remedial actions are determined to be taken for different types of tire failures.

[0016] The program code instructions configured to determine the type of tire failure may include program code instructions configured to distinguish between a tire that has experienced a thermal event and a tire that has burst. In the event that the tire is experiencing a thermal event, the program code instructions configured to determine the remedial action to be taken may include program code instructions configured to update the driving instructions of the AV to cause the AV to drive to the side of the road. Additionally or alternatively, in the event that the tire is experiencing a thermal event, the program code instructions configured to determine the remedial action to be taken may include program code instructions configured to determine the need to contact emergency services. In the event of a tire burst, the program code instructions configured to determine the remedial action may include program code instructions configured to indicate to the AV that the tire needs tire repair.

[0017] The program code instructions configured to determine remedial action may include program code instructions configured to determine remedial action based at least in part on one or more of a type of trailer of the AV, a load carried by the AV, characteristics of a road on which the AV is traveling, or a speed of the AV. In an example embodiment, the program code instructions configured to evaluate signal characteristics include program code instructions configured to filter the signal based on one or more of a frequency of the signal or an amplitude of the signal to distinguish signals having signal characteristics indicative of a tire failure from signals from other sources. The program code instructions configured to determine remedial action may include program code instructions configured to cause an operations server to be alerted of an identified tire failure.

[0018] The one or more microphones carried by the AV may include one or more microphones symmetrically mounted on opposite sides of the AV. In an example embodiment, the one or more microphones carried by the AV may include one or more microphones externally mounted on a tractor of the AV and one or more microphones externally mounted on a trailer of the AV. With respect to microphones mounted on the tractor, one or more microphones may be externally mounted on a lateral surface of the tractor, and one or more microphones may be externally mounted on a rearward surface of the tractor. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] For a more complete understanding of the present disclosure, reference is now made to the following brief description taken in conjunction with the accompanying drawings and detailed description, wherein like reference numerals represent like parts.

[0020] Figure 1 is a perspective view of an autonomous vehicle illustrating microphones mounted on both a tractor and a trailer of the autonomous vehicle according to an example embodiment of the present disclosure;

[0021] Figure 2 is a block diagram of a control subsystem of an autonomous vehicle according to an example embodiment of the present disclosure, the control subsystem being configured to identify and determine the type of tire failure and determine remedial action to take;

[0022] Figure 3 is a diagram showing an example embodiment according to the present disclosure such as Figure 2 A flowchart of the operations performed by the control subsystem;

[0023] Figure 4 is a diagram showing an example embodiment according to the present disclosure such as Figure 2 a flow chart of operations performed by a control subsystem of the tire assembly relating to determining appropriate remedial action based on a type of tire fault that has been identified;

[0024] Figure 5 is a schematic diagram illustrating a motion plan of an autonomous vehicle according to an example embodiment of the present disclosure, the motion plan instructing the autonomous vehicle to drive to the side of a road after considering several candidate positions;

[0025] Figure 6 illustrates a schematic diagram of an autonomous vehicle that may be configured to implement autonomous driving operations to define a motion plan that depends in part on the size of an object sensed within a lane, according to an example embodiment of the present disclosure;

[0026] Figure 7 The diagram shows the Figure 6 An example system for providing autonomous driving operation for an autonomous vehicle; and

[0027] Figure 8A diagram of an onboard control computer included in an autonomous driving vehicle according to an example embodiment of the present disclosure is illustrated. DETAILED DESCRIPTION

[0028] Some embodiments of the present invention will be described more fully below with reference to the accompanying drawings, in which some but not all embodiments of the present invention are shown. In fact, various embodiments of the present invention may be embodied in many different forms and should not be construed as limited to the embodiments described herein; on the contrary, these embodiments are provided so that this disclosure will satisfy applicable legal requirements. The same reference numerals refer to the same elements throughout.

[0029] A control subsystem for an autonomous vehicle and an associated method and computer program product are provided for identifying tire failures and determining remedial actions that should be taken. As described below, various types of tire failures can be detected, including thermal events, such as in the case of tire fires and blowouts. "Blowouts" as referred to herein include any tire damage that results in subsequent deflation of the tire. Such damage may be due to a hole, a pressure problem, or any other cause of tire deflation. Based on the type of tire failure, the control subsystem, method, and computer program product of the example embodiments are configured to customize the remedial actions to be taken, thereby providing a safe and appropriate response to the tire failure. By determining remedial actions specific to the type of tire failure, such remedial actions can be taken faster and more efficiently. Therefore, this approach minimizes inefficiencies in the operation of the autonomous vehicle, minimizes downtime, and ensures safe operation.

[0030] The control subsystem, method, and computer program product may be configured to identify tire failures in any of a variety of different types of autonomous vehicles, including motor vehicles such as cars or trucks, and more specifically tractor-trailers configured for autonomous or at least semi-autonomous operation. Figure 1An example of an autonomous vehicle that can be operated in conjunction with the control subsystem, method, and computer program product of the example embodiment is depicted in FIG. As shown, the autonomous vehicle 10 is a tractor trailer configured to operate in an autonomous manner so that the autonomous vehicle does not require a driver on the tractor. The tractor trailer of the example embodiment includes a tractor 12 and a trailer 14, the tractor including an engine for providing power to the tractor trailer, the trailer being towed by the tractor and configured to carry a load. Although an example of an autonomous tractor trailer is depicted, the autonomous tractor trailer can have any of a variety of alternative configurations. For example, trailer types can include dry van trailers, refrigerated trailers, tanker trailers, standard flatbed trailers, lift decks, pickup trucks, and other variations of flatbed trailers. These different types of trailers have different positions and numbers of tires, as well as different shapes and centers of gravity. In addition, for tanker trailers and livestock trailers, the movement of cargo is different from that of dry van trailers and flatbed trailers with cargo containers placed thereon, which may also affect the movement of the tractor and tractor trailer when a tire fails.

[0031] As shown, both the tractor 12 and the trailer 14 include a plurality of tires 16 mounted on respective axles. Figure 1 The tractor trailer also includes a plurality of microphones 18 carried by the autonomous vehicle and configured to capture audio signals, including audio signals indicative of tire failure. Since the autonomous vehicle includes tires on two opposing sides, such as both the right and left sides, the autonomous vehicle of the example embodiment includes one or more microphones on each opposing side of the autonomous vehicle. In an example embodiment, the autonomous vehicle includes one or more microphones symmetrically mounted on opposing sides of the autonomous vehicle, such as the right and left sides of the autonomous vehicle.

[0032] In the illustrated embodiment, one or more microphones 18 are externally mounted on the tractor 12 of the autonomous tractor trailer 10, and one or more microphones are externally mounted on the trailer 14 of the autonomous tractor trailer. Although the microphones can be mounted in a variety of different locations on the tractor and trailer, the microphones are typically mounted relatively close to the tires 16, but in a location that can at least partially cancel out road noise generated as the autonomous vehicles travel along a road. For example, the microphones can be mounted on a side surface of the tractor and a side surface of the trailer, located outside of the wheel arches and above the tires. Thus, the microphones can capture audible signals generated by a tire failure while maintaining a distance from road noise that might otherwise mask the audio signals generated by the tire failure. Although Figure 1, a microphone is depicted mounted on one side of a tractor trailer, but the tractor trailer may include an additional microphone mounted on the other side of the tractor trailer in a corresponding position so that two opposite sides of the autonomous vehicle have a symmetrical arrangement of microphones.

[0033] like Figure 1 As shown in the illustrated embodiment, one or more microphones 18 may be mounted to the tractor 12 and trailer 14, proximate each tire or each combination of tires 16. In this regard, some trailers or tractors include two or more tires mounted on the same axle and the same side of the tractor trailer, commonly referred to as dual tires or double tires. For example, a single axle may support four tires, two on each side of the trailer. In this example embodiment, one or more microphones may be mounted to the trailer proximate each dual tire, wherein the one or more microphones are mounted on the trailer proximate a corresponding one of the dual tires for capturing audio signals generated by a failure of either of the dual tires.

[0034] In one example embodiment, the microphone 18 may be mounted on the tractor 12 in a manner capable of detecting audible signals indicating tire failure of the tires 16 on the tractor and the tires on the trailer 14. In this regard, one or more microphones may be externally mounted on the lateral surface 12a of the tractor, more typically on two opposing lateral surfaces of the tractor, and one or more microphones may be externally mounted on the rearward surface 12b of the tractor. The one or more microphones externally mounted on the lateral surface(s) of the tractor may be configured to preferentially detect audible signals indicating tire failure of the tires of the tractor. However, the one or more microphones externally mounted on the rearward surface of the tractor may preferably be configured to detect audible signals indicating tire failure of the tires of the trailer. A tractor trailer having microphones externally mounted on both the lateral and rearward surfaces of the tractor may also include one or more microphones mounted on the trailer near the corresponding tires of the trailer, the audio signals captured by the microphone(s) mounted on the rearward surface of the tractor being used to supplement the audio signals captured by the microphone(s) mounted on the trailer. However, other embodiments of tractor trailers having microphones mounted externally on both the lateral and rear-facing surfaces of the tractor do not include microphones mounted on the trailer, at least not to capture audio signals indicative of tire failure of the trailer's tires. Instead, these other embodiments rely more heavily on one or more microphones mounted externally on the rear-facing surface of the tractor to detect audio signals indicative of tire failure of the trailer's tires.

[0035] The one or more microphones 18 are configured to provide signals representing audio signals captured by the microphone(s) to the control subsystem for processing as described below. Although the control subsystem may be remote from the autonomous vehicle 10, in some embodiments it communicates with the autonomous vehicle including one or more microphones mounted thereon, but the autonomous vehicle of other example embodiments may include and carry the control subsystem, such as described below in conjunction with Figure 6 In either case, the control subsystem is embodied by a computing device, such as a computer. In one embodiment, the control subsystem may be a subsystem of an onboard control computer system (see Figure 6 ). The control subsystem may be implemented by one or more computing devices that may be used to determine an object-free driving path for an autonomous vehicle. In an example embodiment, the control subsystem communicates signals with the onboard control computer system 104 (and its components) and an operations server.

[0036] Although the control subsystem can be configured in a variety of different ways, Figure 2 , a control subsystem 20 of an example embodiment is depicted, which includes a processing circuit system 22 and, in some embodiments, a memory 24. The control subsystem of the example embodiment also includes a communication interface 26 and an optional microphone interface 28. In embodiments where the control subsystem is carried by the autonomous vehicle 10, the communication interface may be configured to communicate with any one of one or more of a variety of external systems, including, for example, an operations server, such as a supervisory system, a communication system of an emergency service, e.g., law enforcement, fire department or other traffic safety personnel, a roadside maintenance service communication system, etc. Alternatively, in embodiments where the control subsystem is not on the autonomous vehicle, the communication interface may be configured to communicate not only with the various other external systems, but also with the autonomous vehicle, and more specifically, with the various subsystems of the autonomous vehicle. It should be noted that with respect to Figure 2 The components, devices and elements shown and described are not mandatory and thus some may be omitted in certain embodiments. Furthermore, some embodiments may include, in addition to the Figure 2 Other or different components, devices or elements than those shown and described.

[0037] However, if Figure 2 As shown, the control subsystem 20 of the example embodiment includes a processing circuit system 22 configured to perform actions according to one or more example embodiments disclosed herein. In this regard, according to various example embodiments, the processing circuit system can be configured to perform one or more functions of the control subsystem and / or control its execution. According to one or more example embodiments, the processing circuit system can be configured to perform data processing, application execution, and / or other processing and management services.

[0038] In some example embodiments, processing circuitry 22 may include a processor, and in some embodiments, such as Figure 2 As shown, a memory 24 may also be included. The processing circuit system may communicate with the communication interface 26 or otherwise control the communication interface. The processing circuit system may be embodied in a variety of different ways. For example, the processing circuit system may be embodied as various processing components, such as one or more of the following: a microprocessor or other processing element, a coprocessor, a controller, or various other computing or processing devices including integrated circuits, such as, for example, an ASIC (application specific integrated circuit), an FPGA (field programmable gate array), etc. For example, the processing circuit system of the control subsystem may be embodied as a circuit chip (e.g., an integrated circuit chip) configured (e.g., with hardware, software, or a combination of hardware and software) to perform the operations described herein.

[0039] Although the processing circuit system 22 may include a single processor, it should be understood that the processing circuit system may include multiple processors. Multiple processors may be in operative communication with each other and may be collectively configured to perform one or more functions of the control subsystem 20 described herein. Multiple processors may be embodied on a single computing device, or distributed on multiple computing devices collectively configured to function as a control subsystem. In some example embodiments, the processing circuit system may be configured to execute instructions stored in the memory 24 or otherwise accessible by the processing circuit system. Therefore, whether configured by hardware or by a combination of hardware and software, the processing circuit system may represent an entity (e.g., physically embodied in a circuit system) that is capable of performing operations according to an embodiment of the present invention when configured accordingly. Therefore, for example, when the processing circuit system is embodied as an ASIC, FPGA, etc., the processing circuit system may be a specially configured hardware for performing the operations described herein. Alternatively, as another example, when the processing circuit system is embodied as an executor of a software instruction, the instruction may specifically configure the processing circuit system to perform one or more operations described herein.

[0040] In some example embodiments, the memory 24 may include one or more non-transitory memory devices, such as, for example, volatile and / or non-volatile memory that may be fixed or removable. In this regard, the memory may include a non-transitory computer-readable storage medium. It should be understood that although the memory is illustrated as a single memory, the memory may include multiple memories. Multiple memories may be embodied on a single computing device or distributed on multiple computing devices. The memory may be configured to store information, data, applications, computer program codes, instructions, etc. for enabling the control subsystem to perform various functions according to one or more example embodiments.

[0041] The memory 24 may also be configured to buffer input data for processing by the processing circuit system 22. Additionally or alternatively, the memory may be configured to store instructions executed by the processing circuit system. Among the contents of the memory, applications may be stored for execution by the processing circuit system, thereby implementing the functions associated with each respective application. In some cases, the memory may communicate with one or more of the processing circuit system and / or the communication interface 218 for transferring information between components of the control subsystem.

[0042] The communication interface 26, such as a network interface, may include one or more interface mechanisms for enabling communication with other devices and / or networks. In some cases, the communication interface may be any component, such as a device or circuit system embodied in hardware or a combination of hardware and software, that is configured to receive and / or send data from / to a network and / or any other device or module that communicates with the processing circuit system 22. For example, in an embodiment where the control subsystem is carried by an autonomous vehicle, the communication interface may be configured to communicate with any one of one or more various external systems, such as an operating server, an emergency service communication system, such as law enforcement, fire department or other traffic safety personnel, a roadside maintenance service communication system, etc. Alternatively, in an embodiment where the control subsystem is not on an autonomous vehicle, the communication interface may be configured to communicate with the autonomous vehicle, and more specifically with various subsystems of the autonomous vehicle.

[0043] In some example embodiments, the control subsystem 20 may include a microphone interface 28 configured to communicate with one or more microphones 18 mounted on the autonomous vehicle 10. Although the microphone interface may be embodied by the processing circuit system 22 and / or the communication interface 26, the microphone interface of the example embodiment is a discrete component configured to communicate with the (multiple) microphones. In embodiments where the microphone interface is a discrete component, the microphone interface also communicates with the processing circuit system to provide the processing circuit system with at least some of the signals generated by the (multiple) microphones in response to the audio signal captured by the one or more microphones and representing the audio signal. In other embodiments, the control subsystem need not include a microphone interface, instead, the communication interface and / or the processing circuit system may be configured to receive signals provided by one or more microphones.

[0044] Reference now Figure 3, depicting operations such as performed by the control subsystem 20 according to an example embodiment. As shown in box 30, the control subsystem, such as the processing circuit system 22, the communication interface 26 and / or the microphone interface 28, is configured to receive signals from one or more microphones 18 carried by the autonomous vehicle 10. The signal received from the one or more microphones represents the audio signal captured by the one or more microphones, and therefore represents the frequency and amplitude of the audio signal captured by the one or more microphones. The signal is typically provided to the control subsystem by the one or more microphones in real time or near real time. As described below, the signal provided to the control subsystem by the one or more microphones may also include, or be associated with, information identifying the corresponding microphone that captured the audio signal and the time when the audio signal was captured.

[0045] The control subsystem 20, such as the processing circuitry 22, is also configured to evaluate signal characteristics of signals received from the one or more microphones 18 to identify signals having signal characteristics indicative of tire failure. Figure 3 The processing circuitry may be configured to evaluate the various signal characteristics in any number of different ways to identify a signal indicative of a tire failure. However, in an example embodiment, the processing circuitry is configured to filter the signals based on one or more of the frequency of the signal or the amplitude of the signal to distinguish signals having signal characteristics indicative of a tire failure from signals attributable to other sources, such as signals representing road noise, signals representing an alarm generated by an emergency or safety vehicle, etc.

[0046] In this regard, a burst tire 16 generates an audio signal of a first predefined frequency or a first predefined frequency range that is captured by one or more microphones 18 and provided to a control subsystem 20 for evaluation. For a tire experiencing a thermal event, the tire may be mounted on a pressurized axle, the pressurization of the axle being controlled by a valve configured to open in response to elevated temperatures, such as those generated in the event of a tire fire. After the valve opens in response to the elevated temperature, pressurized gas escaping from the axle generates a whistle sound of a second predefined frequency or a second predefined frequency range. An audio signal representative of such a whistle sound is also captured by one or more microphones and provided to a control subsystem for evaluation.

[0047] Thus, the processing circuit system 22 of the example embodiment is configured to filter the signals received from the one or more microphones 18 to identify signals representing a burst tire 16 or a tire experiencing a thermal event, and while distinguishing between them, also distinguish signals representing tire failure from signals generated by another source captured by at least one microphone. The processing circuit system can be configured to filter the signals based on one or more of, for example, the frequency of the signal or the amplitude of the signal, as described below. For example, the processing circuit system can be configured to filter the signals provided by the one or more microphones to identify signals having a first predefined frequency or a first predefined frequency range generated by a burst tire, and separately identify signals having a second predefined frequency or a second predefined frequency range associated with a tire experiencing a thermal event. In some embodiments, before identifying the signal representing a tire failure, the processing circuit system is configured to filter the signals received from the one or more microphones, not only identifying the presence of a signal having a first predefined frequency or a second predefined frequency or a signal within a first predefined frequency range or a second predefined frequency range, but also identifying the situation where the amplitude of the signal having the first predefined frequency or the second predefined frequency or a signal within a first predefined frequency range or a second predefined frequency range meets, such as by exceeding, a predefined threshold. In this regard, a signal having the same frequency as a signal generated in response to a tire failure may also be present in an audio signal generated by other sources, such as road noise or an emergency vehicle alarm, but the tire failure may generate an audio signal having the first predefined frequency or the second predefined frequency or the first predefined frequency range or the second predefined frequency range, which has a much greater amplitude. By comparing the amplitude of the signal having the first predefined frequency or the second predefined frequency or the signal within the first predefined frequency range or the second predefined frequency range to a predefined threshold, the processing circuit system is configured to identify the tire failure with greater accuracy.

[0048] As an alternative to comparing the amplitude of the signal having the first predefined frequency or the second predefined frequency or the signal within the first predefined frequency range or the second predefined frequency range with the predefined threshold, the control subsystem 20 of another example embodiment, such as the processing circuit system 22, may be configured to determine whether the amplitude of the signal having the first predefined frequency or the second predefined frequency or the signal within the first predefined frequency range or the second predefined frequency range is the largest among all signals of various frequencies captured by the one or more microphones 18. In this example embodiment, the control subsystem, such as the processing circuit system, is configured to identify a tire fault only when the amplitude of the signal having the first predefined frequency or the second predefined frequency or the signal within the first predefined frequency range or the second predefined frequency range is the largest among the signals captured by the one or more microphones, thereby improving the accuracy of identifying a tire fault.

[0049] Where a tire fault is identified based on an evaluation of signal characteristics of signals received from one or more microphones 18, control subsystem 20, such as processing circuitry 22, is further configured to determine the type of tire fault based on the signal characteristics. Figure 3 Block 34 of FIG. 10 . As described above, a burst tire 16 may generate an audio signal having a first predefined frequency or a first predefined frequency range, while a tire that is experiencing a thermal event, such as a fire, may generate an audio signal having a second predefined frequency or a second predefined frequency range. Thus, in the event that a tire failure is identified, the control subsystem of the example embodiment, such as a processing circuit system, is configured to determine the type of tire failure by determining whether the tire failure is a burst tire or a tire that is experiencing a thermal event, the determination being accomplished by determining whether the signals received from the one or more microphones include a signal having a first predefined frequency or a first predefined frequency range indicative of a burst tire, or a signal having a second predefined frequency or a second predefined frequency range indicative of a tire that is experiencing a thermal event.

[0050] Since the audio signal represented by the signal captured by the one or more microphones 18 and provided by the one or more microphones to the control subsystem 20 may include a wide frequency spectrum, the signal received from the one or more microphones may include a signal having a first predefined frequency and a second predefined frequency, or a signal within both the first predefined frequency range and the second predefined frequency range. However, the control subsystem of the example embodiment, such as the processing circuit system 22, is configured to determine the type of tire fault based not only on whether the signal has the first predefined frequency or the first predefined frequency range, or whether it has the second predefined frequency or the second predefined frequency range, but also on determining whether the signal having the first predefined frequency or the first predefined frequency range, or the signal having the second predefined frequency or the second predefined frequency range has the largest amplitude. Then, the control subsystem of the example embodiment, such as the processing circuit system, is configured to determine the type of tire fault as the type of tire fault associated with the signal having the largest amplitude in the first predefined frequency and the second predefined frequency, or in the first predefined frequency range and the second predefined frequency range.

[0051] Although various techniques for identifying signals having signal characteristics indicative of tire failure and for determining the type of tire failure that has been identified, including various rule-based techniques, have been described above, the control subsystem 20, such as the processing circuit system 22, can be configured to identify signals indicative of tire failure and determine the type of tire failure in various other ways. For example, the control subsystem of another example embodiment, such as the processing circuit system, can include an artificial intelligence and / or machine learning engine that has been trained to identify signals indicative of tire failure and determine the type of tire failure that has been identified. In addition, the identification of the type of tire failure can involve analysis of more than two predefined frequency ranges associated with more than two types of tire failures. In fact, any number of types of tire failures can be identified depending on the number of different frequency ranges that indicate different types of tire failures.

[0052] like Figure 3 As shown in block 36 of , in response to identifying a tire failure, the control subsystem 20, such as the processing circuit system 22, is further configured to determine a remedial action to be taken based at least in part on the type of tire failure. Thus, different remedial actions are determined to be taken for different types of tire failures. As described below, various different remedial actions may be taken depending on the type of tire failure, and in some embodiments, also based on one or more additional factors. In addition to determining the remedial action to be taken, the control subsystem, such as the processing circuit system, is further configured to cause the remedial action to be taken, as described below. The remedial actions described below are by way of example only and not limitation.

[0053] For example, Figure 4 Depicts a situation where a tire failure is identified such as by Figure 2 The operations performed by the control subsystem 20 are as follows. Figure 4 As shown in block 40 of , the control subsystem of the example environment, such as the processing circuit system 22, is configured to distinguish between a tire 16 experiencing a thermal event and a tire that has burst. As described above, the control subsystem, such as the processing circuit system, is configured to distinguish between a tire experiencing a thermal event and a tire that has burst based on the frequency of the signal provided by the one or more microphones 18, wherein the frequency of the peak amplitude of the audio signal generated by the burst tire is different from the frequency of the signal generated by the tire experiencing the thermal event.

[0054] In the event that the control subsystem 20, such as the processing circuitry 22, determines that the tire failure is attributable to the tire 16 experiencing a thermal event, the processing circuitry may be configured to determine that the remedial action includes updating the driving instructions of the autonomous vehicle to cause the autonomous vehicle to steer to the side of the road. Figure 4Block 42. While the tire is experiencing a thermal event, the control subsystem, such as the processing circuit system, may be configured to evaluate a plurality of upcoming candidate locations on the side of the road where the autonomous vehicle may pull over. In considering the candidate locations, the control subsystem, such as the processing circuit system, may be configured to evaluate the width and surface characteristics (e.g., pavement, gravel, dirt, or grass, etc.) of the shoulder or other surface where the autonomous vehicle may pull over, as well as the surrounding environment near the various candidate locations, so that the autonomous vehicle is directed to pull over only at locations where there is little risk that a fire from the burning tire will spread to the environment near the location beyond the tire, such as potentially burning dry grass along the side of the road in the case of a narrow shoulder. In addition, the control subsystem, such as the processing circuit system, may be configured to evaluate the candidate locations based on the safety of the autonomous vehicle parking at the corresponding location, taking into account any nearby vehicles traveling along the road and the characteristics of the road itself, such as whether the road is straight, winding, steep, flat, etc., with candidate locations along straight and flat portions of the road being preferred over candidate locations along curved, steeply sloped portions of the road.

[0055] As an example, Figure 5 An autonomous vehicle 10 is depicted traveling along a road 50. In response to detecting a tire failure in the form of a thermal event, a control subsystem 20, such as processing circuitry 22, evaluates a plurality of candidate locations 52 at which the autonomous vehicle may pull over. Due to the width of a shoulder 53 at the candidate location 54, the control subsystem, such as processing circuitry, may be configured to update driving instructions to cause the autonomous vehicle to pull over at the candidate location 54. In addition to increasing the safety at which the autonomous vehicle may pull over, the larger shoulder width allows the autonomous vehicle to maintain a safe spacing from the travel lane 56 and surrounding environment 58 of the road, thereby reducing the risk that a thermal event experienced by the tire 16 may cause the surrounding environment, such as hay, to catch fire.

[0056] In addition to or in lieu of updating the driving instructions to cause the automated vehicle 10 to steer to the side of the road, the control subsystem 20, such as the processing circuit system 22, may be configured to determine to contact emergency services if it is determined that the tire failure was caused by the tire 16 experiencing a thermal event. Figure 443 in. For example, the processing circuit system can be configured to cause the communication interface 26 to contact the local fire department and / or the local police department to indicate that the autonomous vehicle is driving to the side of the road at a particular location and that at least one tire of the autonomous vehicle is experiencing a thermal event, such as a fire. Thus, emergency services can dispatch one or more emergency vehicles to assist the autonomous vehicle and ensure that thermal events, such as tire fires, do not spread to the surrounding environment after the autonomous vehicle drives to the side of the road. In some embodiments, the control subsystem, such as the processing circuit system, is also configured to indicate that the autonomous vehicle requires tire repair, such as by causing the communication interface to contact a roadside repair service. See box 44. The repair service can then dispatch a repair vehicle to assist in repairing or replacing the tire that experienced the thermal event, and in some embodiments, repair any additional damage to the autonomous vehicle caused by the thermal event.

[0057] In contrast, Figure 4 As shown in block 46 of , in the event that the tire failure is determined to be a blown tire 16, the control subsystem 20, such as the processing circuit system 22, may also be configured to update the driving instructions of the autonomous vehicle 10 to cause the autonomous vehicle to steer toward the side of the road. Unlike the updated driving instructions created in response to a tire experiencing a thermal event, the updated driving instructions created in response to determining that a tire has blown do not take into account whether the surrounding environment along the side of the road is at risk of fire in a manner evaluated in response to the tire experiencing a thermal event. Instead, the control subsystem, such as the processing circuit system, may be configured to evaluate multiple candidate locations along the side of the road based on safety, and the autonomous vehicle may be directed to pull over at the corresponding location, taking into account any nearby vehicles traveling along the road and the characteristics of the road itself.

[0058] In the event that the burst tire 16 is one of two or more tires mounted adjacent to each other on the same axle, i.e., one of a dual tire or a double tire, the autonomous vehicle 10 can continue to travel along the road for at least a period of time while the tire remains burst. Therefore, in the event that a tire burst is determined and the control subsystem 20, such as the processing circuit system 22, has determined that the burst tire is one of a dual tire or a double tire (such as based on predefined information related to the characteristics of the autonomous vehicle, including the identification of the dual tire accessible to the processing circuit system), the control subsystem, such as the processing circuit system, can be configured to consider candidate locations along the side of the road that are farther from the current position of the autonomous vehicle than in the event that the tire is experiencing a thermal event and should be driven to the side of the road in a more timely manner. In this regard, the control subsystem, such as the processing circuit system of this example embodiment is configured to determine remedial measures based not only on the type of tire failure, but also at least in part on one or more of the type of trailer 14 of the autonomous vehicle, the load carried by the autonomous vehicle, the characteristics of the road on which the autonomous vehicle is traveling, or the speed of the autonomous vehicle, as these parameters at least partially define the distance that the autonomous vehicle can safely travel in the event of a burst. In this regard, the distance that an autonomous vehicle can travel after one of the dual tires blows out can be inversely proportional to the weight of the load being carried, the roughness of the road, and the speed of the autonomous vehicle. For example, an autonomous vehicle carrying a heavier load should generally move to one side of the road faster than the same autonomous vehicle carrying a lighter load. An autonomous vehicle traveling along a rough road should generally move to one side of the road faster than the same autonomous vehicle traveling along a smooth road. An autonomous vehicle traveling at a higher speed should generally move to one side of the road faster than the same autonomous vehicle traveling at a slower speed.

[0059] Unlike tire 16 experiencing a thermal event, in the event that a tire failure is determined to be attributable to a blowout, there is generally no need to contact emergency services. However, in the event of a blowout, control subsystem 20, such as processing circuitry 22, may additionally or alternatively be configured to indicate that autonomous vehicle 10 requires tire repair, such as by causing communication interface 26 to contact a roadside repair service. Such contact may be an automatic contact in response to an indication that autonomous vehicle 10 requires tire repair. See box 47. The repair service may then dispatch a repair vehicle to assist in repairing or replacing the blown tire.

[0060] Regardless of the type of tire failure, the control subsystem 20 of the example embodiment, such as the processing circuit system 22, the communication interface 26, etc., can also be configured to cause the operation server to receive an alert regarding the identified tire failure, and in some embodiments, include information regarding the type of tire failure that has been identified. Figure 4The operations server is described below and interacts with the autonomous vehicle to provide supervision and in some cases updated instructions and information by monitoring the travel of the autonomous vehicle 10. By alerting the operations server, the operations server can be configured to update the expected travel time and expected arrival time of the autonomous vehicle at its destination based on the expected length of time to repair the faulty tire.

[0061] In response to a notification from the autonomous vehicle 10 that it has experienced a tire failure, the operating server may be configured to alert one or more additional autonomous vehicles traveling along the same road and located a distance behind the autonomous vehicle 10 that has experienced the tire failure. In this regard, the operating server may notify one or more other autonomous vehicles of the autonomous vehicle that has experienced the tire failure and provide an indication of where the autonomous vehicle that has experienced the tire failure has moved to the side of the road. The operating server may additionally or alternatively send a signal to the one or more other autonomous vehicles to automatically update their navigation instructions to reduce any risk posed by the autonomous vehicle 10. Thus, if necessary, one or more other autonomous vehicles may automatically update their respective driving instructions to ensure that sufficient clearance is provided when passing the autonomous vehicle that has experienced the tire failure, such as by moving one or more other autonomous vehicles to a lane that is further away from the side of the road on which the autonomous vehicle 10 that has experienced the tire failure is traveling.

[0062] Although information about the autonomous vehicle 10 that experienced a tire failure and the location where the autonomous vehicle that experienced a tire failure was pulled over can be provided in a variety of ways, the operation server of an example embodiment can be configured to provide updated map information to one or more other autonomous vehicles. The updated map information may include an indication of the location where the autonomous vehicle that experienced a tire failure has driven to the side of the road. In some embodiments, the operation server is also configured to contact emergency services and / or roadside repair services to assist the autonomous vehicle that experienced a tire failure if the autonomous vehicle has not already contacted emergency services or repair services.

[0063] In one example embodiment, the control subsystem 20, such as the processing circuit system 22, is configured not only to identify whether a tire 16 of the autonomous vehicle 10 has experienced a tire failure and the type of tire failure, but the control subsystem, such as the processing circuit system, is configured to determine which tire has experienced the tire failure. In one embodiment where one or more microphones 18 are mounted near each tire 16 of the autonomous vehicle, the control subsystem, such as the processing circuit system, may be configured to determine the tire that has experienced the tire failure based on a particular microphone(s) capturing an audio signal having a signal characteristic indicative of a tire failure, such as an audio signal having a first predefined frequency or a second predefined frequency with a maximum amplitude. For example, each tire 16 may have at least one microphone 18 associated therewith, and each microphone 18 may be associated with one or more tires 16. Each microphone 18 may have a primary tire 16 associated therewith, the primary tire 16 being the tire 16 closest to the microphone 18. Therefore, the particular microphone 18 that captures the first predefined frequency or the second predefined frequency with a maximum amplitude may be considered the microphone 18 closest to the affected tire 16. Therefore, the primary tire 16 associated with the particular microphone 18 may be determined to be the affected tire 16. Alternatively, the microphone 18 may be associated with a plurality of tires 16, thereby identifying at least one of the plurality of tires 16 as an affected tire 16. By associating the microphone 18 with a plurality of tires 16, the total number of microphones 18 is reduced. This arrangement is beneficial when the failure of any tire 16 in a group of a plurality of tires will result in the need for the same remedial action. Conversely, associating the microphone 18 with each tire 16 may improve the accuracy of the detection, which may beneficially indicate that any remedial action is more appropriate because it may be customized based on the specific tire 16 that is affected. For example, depending on the configuration of the autonomous vehicle 10, certain tires 16 may be more or less critical to the safe operation of the autonomous vehicle 10. In such a configuration, it is beneficial to know which specific tire 16 is affected so that the remedial action may be optimized based on the importance and / or failure type of the specific tire 16. For example, the failure of a critical tire 16 may require a more urgent or different remedial action than a redundant or less critical tire 16.

[0064] In other embodiments where one or more microphones 18 are not mounted to the autonomous vehicle 10 proximate each tire 16 of the autonomous vehicle, such as where microphones are mounted only on the tractor 12 of the autonomous tractor trailer, the control subsystem 20, such as the processing circuit system 22, may be configured to determine the tire that has experienced a tire failure based on further processing of the signals provided by the microphone(s). In this example embodiment where one or more microphones are mounted on each opposing lateral surface 12a of the tractor and one or more microphones are mounted on the rearward surface 12b of the tractor, the control subsystem, such as the processing circuit system, is configured to identify whether a particular tire of the tractor has experienced a tire failure in a situation where one or more microphones mounted on the lateral surface of the tractor proximate the tire failure experience captures an audio signal having a signal characteristic indicative of a tire failure. However, in the situation where the rearward facing microphone captures an audio signal having a signal characteristic indicative of a tire failure, the control subsystem, such as the processing circuit system, is configured to determine that a tire of the trailer has experienced a tire failure. In the case where multiple microphones are mounted on the tractor at different distances from various tires of the trailer, the control subsystem, such as the processing circuit system, is configured to determine the trailer tire that has experienced tire failure or at least is most likely to experience tire failure, such as by triangulation based on predetermined positions of the microphones and the multiple tires and the time differences at which the different microphones captured audio signals having signal characteristics indicative of tire failure. As described above, the signal provided to the control subsystem by one or more microphones includes not only a signal representing the signal characteristics of the audio signal captured by the corresponding microphone, but also an indication of the specific microphone that captured the audio signal and the time at which the audio signal was captured by the corresponding microphone to allow identification of the tire that has experienced tire failure or is most likely to experience tire failure.

[0065] As described above, the control subsystem 20 may be provided by an autonomous vehicle, such as Figure 6 The autonomous vehicle shown carries or at least communicates with, Figure 6 A block diagram of an example vehicle ecosystem 100 is shown in which autonomous driving operations may be determined. Figure 6 As shown, the autonomous vehicle 102 can be a semi-trailer truck. The vehicle ecosystem includes several systems and components that can generate and / or deliver one or more information / data sources and related services to an onboard control computer 104 that can be located in the autonomous vehicle. The onboard control computer can communicate data with multiple vehicle subsystems 106, all of which can reside in the autonomous vehicle. A vehicle subsystem interface 108 is provided to facilitate data communication between the onboard control computer and multiple vehicle subsystems. In some embodiments, the vehicle subsystem interface may include a controller area network (CAN) controller to communicate with devices in the vehicle subsystem.

[0066] The autonomous vehicle 102 may include various vehicle subsystems that support the operation of the autonomous vehicle. The vehicle subsystems may include a control subsystem 20, a vehicle drive subsystem 110, a vehicle sensor subsystem 112, and / or a vehicle control subsystem 114. Figure 6 The components or devices of the vehicle drive subsystem, vehicle sensor subsystem, and vehicle control subsystem shown are examples. The vehicle drive subsystem may include components operable to provide powered motion for an autonomous vehicle. In an example embodiment, the vehicle drive subsystem may include an engine / motor 110a, wheels / tires 110b, a transmission 110c, an electrical subsystem 110d, and a power source 110e.

[0067] The vehicle sensor subsystem 112 may include a plurality of sensors 116 configured to sense information about the environment or condition of the autonomous vehicle 102. The vehicle sensor subsystem may include one or more cameras 116a or image capture devices, a radar unit 116b, one or more temperature sensors 116c, a wireless communication unit 116d (e.g., a cellular communication transceiver), an inertial measurement unit (IMU) 116e, a laser rangefinder / LiDAR unit 116f, a global positioning system (GPS) transceiver 116g, and / or a wiper control system 116h. The vehicle sensor subsystem may also include sensors configured to monitor the internal systems of the autonomous vehicle (e.g., an O2 monitor, a fuel gauge, an engine oil temperature, etc.).

[0068] The IMU 116e may include any combination of sensors (e.g., accelerometers and gyroscopes) configured to sense changes in the position and orientation of the autonomous vehicle 102 based on inertial acceleration. The GPS transceiver 116g may be any sensor configured to estimate the geographic location of the autonomous vehicle. To this end, the GPS transceiver may include a receiver / transmitter operable to provide information about the position of the autonomous vehicle relative to the earth. The radar unit 116b may represent a system that uses radio signals to sense objects within the local environment of the autonomous vehicle. In some embodiments, in addition to sensing objects, the radar unit may also be configured to sense the speed and heading of objects close to the autonomous vehicle. The laser rangefinder or LiDAR unit 116f may be any sensor configured to use lasers to sense objects in the environment in which the autonomous vehicle is located. The camera 116a may include one or more devices configured to capture multiple images of the environment of the autonomous vehicle. The camera may be a still image camera or a motion video camera.

[0069] The vehicle control subsystem 114 may be configured to control the operation of the autonomous vehicle 102 and its components. Thus, the vehicle control subsystem may include various elements, such as a throttle and gear 114a, a brake unit 114b, a navigation unit 114c, a steering system 114d, and / or an autonomous control unit 114e. The throttle may be configured to control, for example, the operating speed of the engine, and in turn control the speed of the autonomous vehicle. The gear may be configured to control the gear selection of the transmission. The brake unit may include any combination of mechanisms configured to decelerate the autonomous vehicle. The brake unit may use friction to decelerate the wheels in a standard manner. The brake unit may include an anti-lock braking system (ABS) that prevents the brakes from locking when the brakes are applied. The navigation unit may be any system configured to determine the driving path or route of the autonomous vehicle. The navigation unit may also be configured to dynamically update the driving path when the autonomous vehicle is operating. In some embodiments, the navigation unit may be configured to merge data from the GPS transceiver 116g and one or more predetermined maps to determine the driving path of the autonomous vehicle. A steering system may represent any combination of mechanisms that may be operable to adjust the heading of an autonomous vehicle in either an autonomous mode or a driver-controlled mode.

[0070] The autonomous control unit 114e may represent a control system that is configured to identify, evaluate, and avoid or otherwise negotiate potential obstacles or obstructions in the environment of the autonomous vehicle 102. In general, the autonomous control unit may be configured to control the autonomous vehicle to operate without a driver, or to provide driver assistance in controlling the autonomous vehicle. In some embodiments, the autonomous control unit may be configured to incorporate data from the GPS transceiver 116g, radar 116b, LiDAR unit 116f, camera 116a, and / or other vehicle subsystems to determine a path or trajectory for the autonomous vehicle.

[0071] Many or all of the functions of the autonomous vehicle 102 may be controlled by an onboard control computer 104. The onboard control computer may include at least one data processor 118 (which may include at least one microprocessor) that executes processing instructions 120 stored in a non-transitory computer-readable medium, such as a data storage device 122 or a memory. The onboard control computer may also represent a plurality of computing devices that may be used to control individual components or subsystems of the autonomous vehicle in a distributed manner. In some embodiments, the data storage device may contain processing instructions (e.g., program logic) executable by the data processor to perform various methods and / or functions of the autonomous vehicle, including those described above with respect to Figure 3 and Figure 5 And the following about Figure 7 and Figure 8 Those methods and functions described.

[0072] The data storage device 122 may also contain additional instructions, including instructions for transmitting data to, receiving data from, interacting with, or controlling one or more of the vehicle drive subsystem 110, the vehicle sensor subsystem 112, and the vehicle control subsystem 114. The onboard control computer 104 may be configured to include a data processor 118 and a data storage device 122. The onboard control computer may control functions of the autonomous vehicle 102 based on input received from various vehicle subsystems (e.g., the vehicle drive subsystem, the vehicle sensor subsystem, and the vehicle control subsystem).

[0073] Figure 7 An exemplary system 130 for providing precise autonomous driving operation is shown. The system includes several modules that can operate in the onboard control computer 104, such as in combination with Figure 6 The vehicle control computer includes Figure 7 , wherein the sensor fusion module 132 can perform at least four image or signal processing operations. The sensor fusion module can obtain images from a camera located on the autonomous vehicle 10 to perform image segmentation 134 to detect the presence of moving objects (e.g., other vehicles, pedestrians, etc.) and / or static obstacles (e.g., stop signs, speed bumps, terrain, etc.) located around the autonomous vehicle. The sensor fusion module 132 can obtain LiDAR point cloud data items from a LiDAR sensor located on the autonomous vehicle to perform LiDAR segmentation 136 to detect the presence of objects and / or obstacles located around the autonomous vehicle.

[0074] The sensor fusion module 132 may perform instance segmentation 138 on the images and / or point cloud data items to identify contours (e.g., boxes) around objects and / or obstacles located around the autonomous vehicle 10. The sensor fusion module may perform temporal fusion 140, in which objects and / or obstacles from one image and / or frame of point cloud data items are associated with objects or obstacles from one or more images or frames received subsequently in time.

[0075] The sensor fusion module 132 can fuse objects and / or obstacles from vehicle sensors, such as images acquired from cameras and / or point cloud data items acquired from LiDAR sensors. For example, the sensor fusion module can determine that an image from one of the cameras that includes half of the vehicle located in front of the autonomous driving vehicle 10 is the same as the vehicle captured by the other camera based on the positions of the two cameras. The sensor fusion module sends the fused object information to the interference module 142 and sends the fused obstacle information to the occupancy grid module 144. The onboard control computer includes an occupancy grid module that can retrieve landmarks from a map database 146 stored in the onboard control computer. The occupancy grid module can determine the drivable area and / or obstacles based on the fused obstacles acquired from the sensor fusion module and the landmarks stored in the map database. For example, the occupancy grid module can determine that the drivable area may include a speed bump obstacle.

[0076] Below the sensor fusion module 132, the onboard control computer 104 includes a LiDAR-based object detection module 148, which can perform object detection 150 based on point cloud data items acquired from a LiDAR sensor 152 located on the autonomous vehicle 10. The object detection technology can provide the location of the object (e.g., in 3D world coordinates) from the point cloud data items. Below the LiDAR-based object detection module, the onboard control computer includes an image-based object detection module 154, which can perform object detection 156 based on images acquired from a camera 158 located on the autonomous vehicle. The object detection technology can employ deep machine learning techniques to provide the location of the object (e.g., in 3D world coordinates) from the image provided by the camera.

[0077] Radar 160 on the autonomous vehicle can scan the area in front of the autonomous vehicle 10 or the area the autonomous vehicle is heading towards. The radar data is sent to the sensor fusion module 132, which can use the radar data to associate objects and / or obstacles detected by the radar with objects and / or obstacles detected from both the LiDAR point cloud data items and the camera images. The radar data is also sent to the reasoning module 142, which can perform data processing on the radar data to track the object 162, as further described below.

[0078] The onboard control computer 104 includes an interference module 142 that receives the location of the object from the point cloud and the object from the image, and receives the fused object from the sensor fusion module 132. The interference module also receives radar data, through which the interference module can track the object 162 from one point cloud data item and one image acquired at one time to another (or next) point cloud data item and another image acquired at another subsequent time.

[0079] The interference module 142 may perform object attribute estimation 164 to estimate one or more attributes of an object detected in an image or point cloud data item. The one or more attributes of the object may include the type of the object (e.g., a pedestrian, a car, or a truck, etc.). The interference module may perform behavior prediction 166 to estimate or predict the motion pattern of an object detected in an image and / or point cloud. Behavior prediction may be performed to detect the position of an object in a set of images (e.g., consecutive images) received at different time points or in a set of point cloud data items (e.g., sequential point cloud data items) received at different time points. In some embodiments, behavior prediction may be performed for each image received from a camera and / or each point cloud data item received from a LiDAR sensor. In some embodiments, the interference module may be executed to reduce the computational load by performing behavior prediction for every other or every predetermined number of images received from a camera or point cloud data items received from a LiDAR sensor (e.g., after every two images or after every three point cloud data items).

[0080] The behavior prediction 166 feature can determine the speed and direction of objects around the autonomous vehicle 10 based on the radar data, where the speed and direction information can be used to predict or determine the object's motion pattern. The motion pattern may include predicted trajectory information of the object within a predetermined length of time in the future after receiving an image from the camera. Based on the predicted motion pattern, the interference module 142 can assign a motion pattern context label to the object (e.g., "located at coordinates (x, y)", "stopped", "traveling at a speed of 50 mph", "accelerating", or "decelerating"). The context label can describe the object's motion pattern. The interference module sends one or more object attributes (e.g., the type of object) and the motion pattern context label to the planning module 170. The interference module can use any information obtained by the system 130 and any number and combination of components thereof to perform environmental analysis 168.

[0081] The onboard control computer 104 includes a planning module 170 that receives object attributes and motion pattern context labels from the interference module 142, and receives drivable areas and / or obstacles, as well as vehicle position and pose information from a fused localization module 172 (described further below).

[0082] The planning module 170 may perform navigation planning 174 to determine a set of trajectories on which the autonomous vehicle 10 may travel. The set of trajectories may be determined based on drivable area information, one or more object attributes of an object, a motion mode context label of an object, the location of obstacles, and drivable area information. In some embodiments, navigation planning may include determining an area next to a road where the autonomous vehicle can be safely parked in an emergency. The planning module may include a behavioral decision 176 to determine a driving action (e.g., steering, braking, throttle) in response to determining a changing condition on the road (e.g., a traffic light turns yellow, or the autonomous vehicle is in an unsafe driving condition because another vehicle is traveling in front of the autonomous vehicle and in an area within a predetermined safety distance of the location of the autonomous vehicle). The planning module performs trajectory generation 178 and selects a trajectory from the set of trajectories determined by the navigation planning operation. The selected trajectory information is sent by the planning module to the control module 180.

[0083] The onboard control computer 104 includes a control module 180 that receives the proposed trajectory from the planning module 170 and receives the position and attitude of the autonomous vehicle from the fused positioning module 172. The control module includes a system identifier 182. The control module can perform model-based trajectory refinement 184 to refine the proposed trajectory. For example, the control module can apply filtering (e.g., a Kalman filter) to smooth the proposed trajectory data and / or minimize noise. The control module can perform robust control 186 by determining the amount of brake pressure to be applied, the steering angle, the throttle amount for controlling the vehicle speed, and / or the transmission gear based on the information of the refined proposed trajectory and the current position and / or attitude of the autonomous vehicle. The control module can send the determined brake pressure, steering angle, throttle amount, and / or transmission gear to one or more devices in the autonomous vehicle to control and facilitate the precise driving operation of the autonomous vehicle 10.

[0084] The depth image-based object detection 156 performed by the image-based object detection module 154 can also be used to detect landmarks on the road (e.g., stop signs, speed bumps, etc.). The onboard control computer 104 includes a fused localization module 172 that takes the landmarks detected from the images, the landmarks obtained from the map database 188 stored on the onboard control computer, the landmarks detected from the point cloud data items by the LiDAR-based object detection module 148, the speed and displacement from the odometer sensor 190, and the estimated position of the autonomous vehicle 10 from the GPS / IMU sensors 194 (i.e., GPS sensor 196 and IMU sensor 198) located on or in the autonomous vehicle. Based on this information, the fused localization module can perform a localization operation 192 to determine the position of the autonomous vehicle, which can be sent to the planning module 170 and the control module 180.

[0085] The fused positioning module 172 can estimate the pose 200 of the autonomous vehicle 10 based on the GPS and / or IMU sensors 194. The pose of the autonomous vehicle can be sent to the planning module 170 and the control module 180. The fused positioning module can also estimate the state (e.g., position, possible movement angle) of the trailer unit 202 based on information (e.g., angular rate and / or linear velocity) provided by the IMU sensor 198, for example. The fused positioning module can also check the map content 204.

[0086] Figure 8 An exemplary block diagram of an onboard control computer 104 included in an autonomous vehicle 10 is shown. The onboard control computer includes a processing circuit system, such as at least one processor 210 and a memory 212 on which instructions are stored. When executed by the processor, the instructions configure the onboard control computer and / or the various modules of the onboard control computer to perform the above-mentioned operations. The transmitter 214 transmits or sends information or data to one or more devices in the autonomous vehicle. For example, the transmitter can send instructions to one or more motors of the steering wheel to turn the autonomous vehicle. The receiver 216 receives information or data transmitted or sent by one or more devices. For example, the receiver receives the state of the current speed from the odometer sensor, or receives the current transmission gear from the transmission. The transmitter and receiver are also configured to communicate with the above-mentioned control subsystem 20.

[0087] Figure 3 and Figure 4The operation of the control subsystem 20, the method, and the computer program product according to some example embodiments are illustrated. It should be understood that each operation of the flowchart and the combination of operations in the flowchart can be implemented in various ways, such as hardware and / or a computer program product including one or more computer-readable media having computer-readable program instructions stored thereon. For example, one or more processes described herein can be implemented by computer program instructions of a computer program product. In this regard, the (multiple) computer program products embodying the processes described herein can include one or more memory devices of the control subsystem (e.g., memory 24) for storing instructions executable by a processor in the control subsystem (e.g., by the processing circuit system 22). In some example embodiments, the computer program instructions of the (multiple) computer program products embodying the above-mentioned processes can be stored by memory devices of multiple computing devices. As will be understood, any such computer program product can be loaded onto a computer or other programmable device (e.g., control subsystem 20) to produce a machine, so that the computer program product including instructions that can be executed on a computer or other programmable device creates a component for implementing the functions specified in the (multiple) flowchart blocks. In addition, the computer program product may include one or more computer-readable memories on which computer program instructions may be stored, so that the one or more computer-readable memories can direct a computer or other programmable device to operate in a specific manner, so that the computer program product may include an article of manufacture that implements the functions specified in the (multiple) flowchart blocks. The computer program instructions of the one or more computer program products may also be loaded onto a computer or other programmable device (e.g., the control subsystem 20 and / or other devices) to cause a series of operations to be performed on the computer or other available device, thereby producing a computer-implemented process, so that the instructions executed on the computer or other programmable device implement the functions specified in the (multiple) flowchart blocks.

[0088] Therefore, the blocks of the flowchart support the combination of components for performing the specified functions and the combination of operations for performing the specified functions. It will also be understood that one or more blocks of the flowchart and the combination of blocks in the flowchart can be implemented by a computer system based on special-purpose hardware or a combination of special-purpose hardware and computer instructions that performs the specified functions.

[0089] As used herein, where the control subsystem 20 is described as receiving data or other information from another device, it is understood that the data or other information may be received directly from the other device and / or may be received indirectly via one or more intermediate devices, such as, for example, one or more servers, relays, routers, network access points, etc. Similarly, where the control subsystem described herein transmits data or other information to another device, it is understood that the data or other information may be sent directly to the other device or may be sent to the other device via one or more interconnected devices, such as, for example, one or more servers, relays, routers, network access points, etc.

[0090] In this regard, devices (including control subsystem 20 or components thereof) shown or discussed as coupled or directly coupled or communicating with each other may be indirectly coupled or communicating through some interface, device or intermediate component, whether electrically, mechanically or otherwise. In addition, the techniques, systems, subsystems and methods described and illustrated as discrete or separate in various embodiments may be combined or integrated with other systems, modules, techniques or methods without departing from the scope of the present disclosure.

[0091] With the benefit of the teachings presented in the above description and the associated drawings, those skilled in the art will be able to think of many modifications and other embodiments of the invention described herein. Therefore, it should be understood that the present invention is not limited to the specific embodiments disclosed, and modifications and other embodiments are intended to be included within the scope of the appended claims. In addition, although the above description and the associated drawings describe example embodiments in the context of certain example combinations of elements and / or functions, it should be understood that alternative embodiments may provide different combinations of elements and / or functions without departing from the scope of the appended claims. In this regard, for example, as described in some of the appended claims, it is also possible to consider elements and functional combinations different from the elements and / or functions explicitly described above. Although specific terms are used herein, they are used only in a general and descriptive sense, and not for the purpose of limitation.

[0092] The following numbered sections are also disclosed herein:

[0093] 1. A control subsystem for an autonomous vehicle (AV), the control subsystem comprising a processing circuit system, the processing circuit system being configured to:

[0094] receiving signals from one or more microphones carried by the AV;

[0095] evaluating signal characteristics of the signals to identify signals having signal characteristics indicative of tire failure;

[0096] If a tire fault is identified, determining a type of the tire fault based on the signal characteristics; and

[0097] A remedial action to be taken is determined based at least in part on the type of the tire failure, wherein different remedial actions are determined to be taken for different types of tire failures.

[0098] 2. The control subsystem of section 1, wherein the processing circuit system is configured to determine the type of tire failure by distinguishing between a tire experiencing a thermal event and a tire that has burst.

[0099] 3. The control subsystem of section 2, wherein the processing circuit system is configured to determine the remedial action by updating driving instructions for the AV to cause the AV to steer to a side of a road if the tire is experiencing a thermal event.

[0100] 4. A control subsystem according to sections 2 or 3, wherein the processing circuit system is configured to determine the remedial action by indicating to the AV that tire service is required in the event of a tire blowout.

[0101] 5. A control subsystem according to any of the preceding sections, wherein the processing circuit system is configured to determine the remedial action by causing an operations server to receive an alert regarding the tire failure that has been identified.

[0102] 6. A control subsystem according to any of the preceding sections, wherein the one or more microphones carried by the AV include one or more microphones externally mounted on a tractor of the AV and one or more microphones externally mounted on a trailer of the AV.

[0103] 7. A control subsystem according to any of Chapters 1 to 5, wherein the one or more microphones carried by the AV include one or more microphones mounted externally on both lateral and rearward surfaces of a towing vehicle of the AV.

[0104] 8. A method comprising:

[0105] receiving a signal from one or more microphones carried by an autonomous vehicle (AV);

[0106] evaluating signal characteristics of the signals to identify signals having signal characteristics indicative of tire failure;

[0107] If a tire fault is identified, determining a type of the tire fault based on the signal characteristics; and

[0108] A remedial action to be taken is determined based at least in part on the type of the tire failure, wherein different remedial actions are determined to be taken for different types of tire failures.

[0109] 9. The method of claim 8, wherein determining the remedial action comprises determining the remedial action based at least in part on one or more of: a type of trailer for the AV, a load carried by the AV, characteristics of a road on which the AV is traveling, or a speed of the AV.

[0110] 10. A method according to chapter 8 or 9, wherein evaluating the signal characteristics includes filtering the signal based on one or more of the frequency of the signal or the amplitude of the signal to distinguish signals having signal characteristics indicative of the tire failure from signals from other sources.

[0111] 11. A method according to any of Chapters 8 to 10, wherein the one or more microphones carried by the AV include one or more microphones symmetrically mounted on opposite sides of the AV.

[0112] 12. The method of any of Chapters 8 to 11, wherein determining the type of tire failure comprises distinguishing between a tire that experienced a thermal event and a tire that burst.

[0113] 13. The method of section 12, wherein determining the remedial action includes updating driving instructions for the AV to cause the AV to steer to a side of a road if the tire is experiencing a thermal event.

[0114] 14. The method of chapters 12 or 13, wherein determining the remedial action includes determining to contact emergency services if the tire is experiencing a thermal event.

[0115] 15. A computer program product comprising at least one non-transitory computer-readable storage medium having computer-executable program code instructions stored therein, the computer-executable program code instructions comprising program code instructions configured to:

[0116] receiving a signal from one or more microphones carried by an autonomous vehicle (AV);

[0117] evaluating signal characteristics of the signals to identify signals having signal characteristics indicative of tire failure;

[0118] If a tire fault is identified, determining a type of the tire fault based on the signal characteristics; and

[0119] A remedial action to be taken is determined based at least in part on the type of the tire failure, wherein different remedial actions are determined to be taken for different types of tire failures.

[0120] 16. The computer program product of Chapter 15, wherein the program code instructions configured to determine the type of tire failure include program code instructions configured to distinguish between a tire that experienced a thermal event and a tire that burst.

[0121] 17. A computer program product as described in Chapter 16, wherein the program code instructions configured to determine the remedial action include program code instructions configured to update driving instructions for the AV to cause the AV to steer to a side of a road if the tire is experiencing a thermal event.

[0122] 18. The computer program product of Chapter 16 or 17, wherein the program code instructions configured to determine the remedial action include program code instructions configured to indicate to the AV that tire service is required in the event of a tire blowout.

[0123] 19. A computer program product according to any of Chapters 15 to 18, wherein the program code instructions configured to determine the remedial action include program code instructions configured to determine the remedial action based at least in part on one or more of: the type of trailer of the AV, the load carried by the AV, the characteristics of the road on which the AV is traveling, or the speed of the AV.

[0124] 20. A computer program product according to any of Chapters 15 to 19, wherein the program code instructions configured to evaluate the signal characteristics include program code instructions configured to filter the signal based on one or more of the frequency of the signal or the amplitude of the signal to distinguish signals having signal characteristics indicative of the tire failure from signals from other sources.

Claims

1. A control subsystem for an autonomous vehicle (AV), the control subsystem comprising a processing circuit system, the processing circuit system being configured to: receiving signals from one or more microphones carried by the AV; evaluating signal characteristics of the signals to identify signals having signal characteristics indicative of tire failure; In the event that a tire fault is identified, determining a type of the tire fault based on the signal characteristic; as well as A remedial action to be taken is determined based at least in part on the type of the tire failure, wherein different remedial actions are determined to be taken for different types of tire failures. 2 . The control subsystem of claim 1 , wherein the processing circuitry is configured to determine the type of the tire failure by distinguishing between a tire experiencing a thermal event and a tire that has burst.

3. The control subsystem of claim 2, wherein the processing circuitry is configured to determine the remedial action by updating driving instructions for the AV to cause the AV to steer to a side of a road if the tire is experiencing a thermal event.

4. The control subsystem of claim 2 or 3, wherein the processing circuitry is configured to determine the remedial action by indicating to the AV that tire service is required in the event of a tire blowout.

5. A control subsystem according to any preceding claim, wherein the processing circuitry is configured to determine the remedial action by alerting an operations server of the tire fault that has been identified.

6. A control subsystem according to any of the preceding claims, wherein the one or more microphones carried by the AV include one or more microphones mounted externally on a tractor of the AV and one or more microphones mounted externally on a trailer of the AV.

7. The control subsystem of any one of claims 1 to 6, wherein the one or more microphones carried by the AV include one or more microphones mounted externally on both lateral and rearward facing surfaces of a towing vehicle of the AV.

8. A method comprising: receiving a signal from one or more microphones carried by an autonomous vehicle (AV); evaluating signal characteristics of the signals to identify signals having signal characteristics indicative of tire failure; In the event that a tire fault is identified, determining a type of the tire fault based on the signal characteristic; as well as A remedial action to be taken is determined based at least in part on the type of the tire failure, wherein different remedial actions are determined to be taken for different types of tire failures.

9. The method of claim 8, wherein determining the remedial action comprises determining the remedial action based at least in part on one or more of: a type of trailer of the AV, a load carried by the AV, characteristics of a road on which the AV is traveling, or a speed of the AV.

10. The method of claim 8 or 9, wherein evaluating the signal characteristic comprises filtering the signal based on one or more of the frequency of the signal or the amplitude of the signal to distinguish signals having signal characteristics indicative of the tire failure from signals from other sources.

11. The method of any one of claims 8 to 10, wherein the one or more microphones carried by the AV include one or more microphones symmetrically mounted on opposite sides of the AV.

12. The method of any one of claims 8 to 11, wherein determining the type of the tire failure comprises distinguishing between a tire that experienced a thermal event and a tire that burst.

13. The method of claim 12, wherein determining the remedial action comprises updating driving instructions for the AV to cause the AV to steer to a side of a road if the tire is experiencing a thermal event.

14. The method of claim 12 or 13, wherein determining the remedial action comprises determining that emergency services are to be contacted if the tyre is experiencing a thermal event.

15. A computer program product comprising at least one non-transitory computer-readable storage medium having computer-executable program code instructions stored therein, the computer-executable program code instructions comprising program code instructions configured to: receiving a signal from one or more microphones carried by an autonomous vehicle (AV); evaluating signal characteristics of the signals to identify signals having signal characteristics indicative of tire failure; In the event that a tire fault is identified, determining a type of the tire fault based on the signal characteristic; as well as A remedial action to be taken is determined based at least in part on the type of the tire failure, wherein different remedial actions are determined to be taken for different types of tire failures.

16. The computer program product of claim 15, wherein the program code instructions configured to determine the type of the tire failure include program code instructions configured to distinguish between a tire that experienced a thermal event and a tire that burst.

17. The computer program product of claim 16, wherein the program code instructions configured to determine the remedial action include program code instructions configured to update driving instructions for the AV to cause the AV to steer to a side of a road if the tire is experiencing a thermal event.

18. The computer program product of claim 16 or 17, wherein the program code instructions configured to determine the remedial action include program code instructions configured to indicate to the AV that tire service is required in the event of a tire blowout.

19. The computer program product of any one of claims 15 to 18, wherein the program code instructions configured to determine the remedial action include program code instructions configured to determine the remedial action based at least in part on one or more of: a type of trailer of the AV, a load carried by the AV, characteristics of a road on which the AV is traveling, or a speed of the AV.

20. The computer program product of any one of claims 15 to 19, wherein the program code instructions configured to evaluate the signal characteristic include program code instructions configured to filter the signal based on one or more of the frequency of the signal or the amplitude of the signal to distinguish signals having signal characteristics indicative of the tire failure from signals from other sources.

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