Patent Application
20190248364
The technical field generally relates to vehicles, and more particularly to methods and systems for detecting potholes and/or other road hazards and controlling the vehicle and the sharing of information based thereon.
A road surface in some cases includes one or more road hazards such as, but no limited to, potholes, speed bumps, debris, or other objects. Hitting such road hazards when traveling along the road may be unpleasant to a vehicle occupant and may even cause damage to the vehicle.
Vehicle sensors have been used to detect potholes and other road hazards. Such detection typically does not occur in time to prevent the vehicle from hitting the hazard rather, provides information useful in preventing other vehicles from hitting the hazard through, for example, crowd sourcing. Such information does not always include an accurate location of the road hazard. Such information is not always shared with the correct vehicles.
Accordingly, it is desirable to provide improved methods and systems for detecting upcoming hazards in the road and controlling the vehicle based thereon. It is further desirable to provide improved methods and systems for sharing information about the detecting upcoming hazards with other vehicles. Furthermore, other desirable features and characteristics will become apparent from the subsequent detailed description and the appended claims, taken in conjunction with the accompanying drawings and the foregoing technical field and background.
Methods and systems are provided for controlling a vehicle. In one embodiment, the method includes: receiving, by a processor, sensor data indicative of conditions of a roadway in a path of a first vehicle; determining, by a processor, road hazard information based on the presence of a road hazard within the roadway; assigning, by a processor, a category to the road hazard information; selectively communicating, by a processor, the road hazard information to a second vehicle based on vehicle information associated with the second vehicle and the category; and selectively controlling, by a processor, the second vehicle based on the vehicle information.
In various embodiments, the selectively controlling the second vehicle includes controlling the vehicle autonomously or with user input based on at least one of the hazard level category and the road hazard information. In various embodiments, the selectively communicating is based on a lane location of the road hazard and a lane location of the second vehicle. In various embodiments, the category is a vehicle category.
In various embodiments, the assigning the vehicle category is based on an evaluation of a hazard level. In various embodiments, the vehicle category is defined based on at least one of a tire size, a tire profile, vehicle weight, a ground clearance, and a vehicle speed.
In various embodiments, the method further includes receiving the vehicle information from the second vehicle, and wherein the vehicle information includes at least one of a tire size, a tire profile, vehicle weight, a ground clearance, and a vehicle speed.
In various embodiments, the second vehicle includes different wheels; the vehicle information is based on a smallest size (in terms of tire height or profile which essentially is the amount of rubber that can absorb the energy due to impact) of the different wheels.
In another embodiment, a system includes: at least one sensor that generates sensor signals based on conditions of a roadway in a path of the vehicle; and at least one non-transitory computer module that, by at least one processor, receives the sensor signals, determines road hazard information based on the presence of a road hazard within the roadway, assigns a category to the road hazard information, selectively communicates the road hazard information to a second vehicle based on vehicle information associated with the second vehicle and the category, and selectively controls the second vehicle based on the vehicle information.
In various embodiments, the category is a hazard level category. In various embodiments, the at least one non-transitory computer module assigns the hazard level category based an evaluation of at least one of a depth, an angle of an exiting wall, a height, a length, and a width of the road hazard.
In various embodiments, the at least one non-transitory computer module controls the second vehicle by controlling the vehicle autonomously or with user input based on at least one of the hazard level category and the road hazard information.
In various embodiments, the at least one non-transitory computer module selectively communicates based on a lane location of the road hazard and a lane location of the second vehicle. In various embodiments, the category is a vehicle category.
In various embodiments, the at least one non-transitory computer module assigns the vehicle category based on an evaluation of a hazard level.
In various embodiments, the vehicle category is defined based on at least one of a tire size, a tire profile, vehicle weight, a ground clearance, and a vehicle speed.
In various embodiments, the at least one non-transitory computer module receives the vehicle information from the second vehicle, and wherein the vehicle information includes at least one of a tire size, a tire profile, vehicle weight, a ground clearance, and a vehicle speed.
In various embodiments, when the second vehicle includes different wheels, the vehicle information is based on a smallest size of the different wheels.
The exemplary embodiments will hereinafter be described in conjunction with the following drawing figures, wherein like numerals denote like elements, and wherein:
The following detailed description is merely exemplary in nature and is not intended to limit the application and uses. Furthermore, there is no intention to be bound by any expressed or implied theory presented in the preceding technical field, background, brief summary or the following detailed description. It should be understood that throughout the drawings, corresponding reference numerals indicate like or corresponding parts and features. As used herein, the term module refers to any hardware, software, firmware, electronic control component, processing logic, and/or processor device, individually or in any combination, including without limitation: application specific integrated circuit (ASIC), an electronic circuit, a processor (shared, dedicated, or group) and memory that executes one or more software or firmware programs, a combinational logic circuit, and/or other suitable components that provide the described functionality.
Exemplary embodiments may be described herein in terms of functional and/or logical block components and various processing steps. It should be appreciated that such block components may be realized by any number of hardware, software, and/or firmware components configured to perform the specified functions. For example, an embodiment may employ various integrated circuit components, e.g., memory elements, digital signal processing elements, logic elements, look-up tables, or the like, which may carry out a variety of functions under the control of one or more microprocessors or other control devices. In addition, those skilled in the art will appreciate that exemplary embodiments may be practiced in conjunction with any number of control systems, and that the vehicle system described herein is merely one example embodiment.
For the sake of brevity, techniques related to signal processing, data transmission, signaling, control, and other functional aspects of the systems (and the individual operating components of the systems) may not be described in detail herein. Furthermore, the connecting lines shown in the various figures contained herein are intended to represent example functional relationships and/or physical couplings between the various elements. It should be noted that many alternative or additional functional relationships or physical connections may be present in an exemplary embodiment.
With reference to
In various embodiments, one or more of the vehicles 100 is an autonomous vehicle. In various embodiments, the vehicle 100a is an autonomous vehicle and the system 10 is incorporated in part or in full into the autonomous vehicle 100a. The autonomous vehicle 100a is, for example, a vehicle that is automatically controlled to carry passengers from one location to another. The vehicle 100a is depicted in the illustrated embodiment as a passenger car, but it should be appreciated that any other vehicle including motorcycles, trucks, sport utility vehicles (SUVs), recreational vehicles (RVs), etc., can also be used. In an exemplary embodiment, the autonomous vehicle 100a is a so-called Level Four or Level Five automation system. A Level Four system indicates “high automation”, referring to the driving mode-specific performance by an automated driving system of all aspects of the dynamic driving task, even if a human driver does not respond appropriately to a request to intervene. A Level Five system indicates “full automation”, referring to the full-time performance by an automated driving system of all aspects of the dynamic driving task under all roadway and environmental conditions that can be managed by a human driver.
As shown in more detail in
The actuator system 30 includes one or more actuator devices 42a-42n that control one or more vehicle features such as, but not limited to, the propulsion system 20, the transmission system 22, the steering system 24, and the brake system 26. In various embodiments, the vehicle features can further include interior and/or exterior vehicle features such as, but are not limited to, doors, a trunk, and cabin features such as air, music, lighting, etc. (not numbered).
The communication system 36 is configured to wirelessly communicate information to and from other entities 48, such as but not limited to, other vehicles (“V2V” communication,) infrastructure (“V2I” communication), remote computing systems, and/or personal devices (described in more detail with regard to
The data storage device 32 stores data for use in automatically controlling the autonomous vehicle 10. In various embodiments, the data storage device 32 stores defined maps of the navigable environment. In various embodiments, the defined maps may be predefined by and obtained from a remote system (described in further detail with regard to
The sensor system 28 includes one or more sensing devices 40a-40n that sense observable conditions of the exterior environment and/or the interior environment of the autonomous vehicle 10, and/or other vehicle conditions. In various embodiments, the sensing devices 40a-40n that sense the environment can include, but are not limited to, radars, lidars, global positioning systems, optical cameras, thermal cameras, ultrasonic sensors, and/or other sensors. For example, as shown in more detail in
In various embodiments, the sensing devices 40a-40n of
With reference back to
The controller 34 includes at least one processor 44 and a computer readable storage device or media 46. The processor 44 can be any custom made or commercially available processor, a central processing unit (CPU), a graphics processing unit (GPU), an auxiliary processor among several processors associated with the controller 34, a semiconductor based microprocessor (in the form of a microchip or chip set), a macroprocessor, any combination thereof, or generally any device for executing instructions. The computer readable storage device or media 46 may include volatile and nonvolatile storage in read-only memory (ROM), random-access memory (RAM), and keep-alive memory (KAM), for example. KAM is a persistent or non-volatile memory that may be used to store various operating variables while the processor 44 is powered down. The computer-readable storage device or media 46 may be implemented using any of a number of memory devices such as PROMs (programmable read-only memory), EPROMs (electrically PROM), EEPROMs (electrically erasable PROM), flash memory, or any other electric, magnetic, optical, or combination memory devices capable of storing data, some of which represent executable instructions, used by the controller 34 in controlling the autonomous vehicle 100a.
The instructions may include one or more separate programs, each of which comprises an ordered listing of executable instructions for implementing logical functions. The instructions, when executed by the processor 44, receive and process signals from the sensor system 28, perform logic, calculations, methods and/or algorithms for automatically controlling the components of the autonomous vehicle 10, and generate control signals to the actuator system 30 to automatically control the components of the autonomous vehicle 100a based on the logic, calculations, methods, and/or algorithms. Although only one controller 34 is shown in
In various embodiments, one or more instructions of the controller 34 are embodied in the system 10 and, when executed by the processor 44, are configured to receive the signals and/or the processed data from the sensing devices 40a-40n and processes the signals and/or data to determine whether a road hazard is present along the path of the vehicle 100a and if so, determine road hazard information. When a road hazard is determined to be present, the instructions are further configured to process additional data such as GPS data and image data to localize the road hazard, and then selectively control the vehicle 100a based on the location of the road hazard and the location of the vehicle 100a. For example, the controller 34 controls the suspension system 27, for example, by adjusting ride stiffness, height, and active air dams based on the location of the road hazard. In another example, controller 34 generates notifications to a driver based on the road hazard.
In various embodiments, the road hazard vehicle control system 10 further includes a cloud computing system 140. The cloud computing system 140 can be remote from the vehicles 100, such as, but not limited to, a server system or other system as shown and/or may be incorporated into the vehicles 100. In various embodiments, the controller 34 communicates road hazard information including the identified road hazard and the location to the cloud computing system 140 via, for example the communication system 36 (
The data management module 150 further receives vehicle information from other vehicles 100b and selectively communicates the stored, categorized road hazard information to the other vehicles 100b based on the received vehicle information. For example, the data management module 150 selectively communicates the road hazard information to other vehicles 100b associated with an immediate or near immediate threat of the road hazard. In another example, the data management module 150 selectively communicates the road hazard information to other vehicles 100b based on a determined impact of the road hazard on the other vehicle 100b.
With reference now to
With initial reference to
A hazard category is then selected from a plurality of defined hazard categories based on the received road hazard information at 320. For example, as illustrated in
A vehicle category is then assigned from a plurality of vehicle categories based on the hazard category at 330. For example, as illustrated in
With reference now to
The stored data in the datastore 160 is processed along with the current location and road map data to select road hazards that have a location that fall within the lane of travel of the vehicle 100 at 420. The current vehicle category is determined based on the received tire size, tire profile, weight, ground clearance, and speed at 430. The road hazards selected based on location and then filtered based on the current vehicle category at 440. The filtered road hazard and the corresponding information are then communicated back to the vehicle at 450.
With reference now to
While at least one exemplary embodiment has been presented in the foregoing detailed description, it should be appreciated that a vast number of variations exist. It should also be appreciated that exemplary embodiments are only examples, and are not intended to limit the scope, applicability, or configuration of the disclosure in any way. Rather, the foregoing detailed description will provide those skilled in the art with a convenient road map for implementing the exemplary embodiments. It should be understood that various changes can be made in the function and arrangement of elements without departing from the scope of the disclosure as set forth in the appended claims and the legal equivalents thereof.
