System and method of detecting hazards of leading vehicle

Abstract

To provide a system.SOLUTION: There are provided a system and method to implement detecting a leading vehicle hazard. The system and method visually ascertain if certain driver risk factors are exhibited by a proceeding vehicle (and driver) that indicate the vehicle is potentially hazardous, such as obtaining images of an expired license plate on the vehicle. In response to this action, the system performs a computer-controlled maneuver so as to safely evade the potentially hazardous leading vehicle, thereby substantively lowering the potential of a dangerous collision with the vehicle which can lead to loss, damage, and / or bodily injury. For example, the system can include a vehicle sensor capturing image data of the leading vehicle. The system can also include a controller device that determines whether or not the leading vehicle is a hazard on the basis of the image data, and generates a vehicle command that effectuates a computer-controlled automated driving maneuver or automated driving action to avoid collision with the leading vehicle.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] FIELD OF THE DISCLOSURE This disclosure relates generally to computer controlled vehicle safety technology, and in particular to communication and use of image data associated with at least one nearby vehicle in performing advanced vehicle safety control functions. [Background technology]

[0002] Vehicle accidents (e.g., crashes) are a constant threat to drivers, passengers, pedestrians, and property. Accidents that unfortunately result in injuries may, in some instances, be caused by the driver. For example, a "driver-caused" accident may result from the driver's delayed recognition of a dangerous situation, the driver's ability to react accordingly, and / or unconsciously operating the vehicle in a manner that is highly unsafe for the current conditions of the vehicle, road, and / or surroundings. According to the NHTSA, in 2016, over 7.2 million motor vehicle accidents were reported, many of which were avoidable. Summary of the Invention

[0003] According to embodiments of the disclosed techniques, a system for implementing a leading vehicle danger system and functionality is disclosed herein. The system includes a vehicle sensor that captures image data of a leading vehicle. The image data corresponds to an area of ​​the leading vehicle that displays visible, identifiable information about the leading vehicle. The system also includes a controller that determines whether the leading vehicle is a hazard based on the image data. Furthermore, the controller generates vehicle commands that implement a computer-controlled automated driving maneuver or action to avoid a collision with the leading vehicle in response to determining that the leading vehicle is a hazard.

[0004] According to embodiments of the disclosed techniques, a non-transitory computer readable medium implementing a leading vehicle hazard system and functionality is disclosed herein. The non-transitory computer readable medium comprises instructions to cause a processor to capture image data of a leading vehicle. The image data corresponds to an area of ​​the leading vehicle that displays visible identifiable information related to the leading vehicle. The non-transitory computer readable medium further includes instructions to cause the processor to determine, based on the image data, whether the leading vehicle is a hazard, and in response to determining that the leading vehicle is a hazard, generate vehicle commands that implement a computer-controlled automated driving maneuver or operation to avoid a collision with the leading vehicle.

[0005] Other features and aspects of the disclosed technology will become apparent from the following detailed description, taken in conjunction with the accompanying drawings which illustrate, by way of example, the features according to embodiments of the disclosed technology. The Summary is not intended to limit the scope of any inventions described herein, which are defined solely by the claims appended hereto. [Brief description of the drawings]

[0006] The present disclosure, according to one or more various embodiments, will now be described in detail with reference to the following figures, which are provided for illustrative purposes only and merely depict typical or exemplary embodiments.

[0007] [Figure 1] FIG. 1 is an exemplary road environment including a vehicle implementing leading vehicle hazard detection during an operational mode, for example, according to an embodiment of the technology disclosed herein. [Diagram 2] FIG. 2 is a schematic representation of an exemplary vehicle in which embodiments of the leading vehicle hazard detection system disclosed herein may be implemented. [Diagram 3] FIG. 3 illustrates an exemplary vehicle in which embodiments of the present disclosure may be implemented. [Figure 4] FIG. 4 illustrates an example communication architecture for the vehicle shown in FIG. 1 implementing the preceding vehicle hazard detection of the present disclosure, in accordance with an embodiment of the technology disclosed herein. [Diagram 5] FIG. 5 is an exemplary computing component that can be used to implement various features of the embodiments described in this disclosure.

[0008] The figures are not intended to be exhaustive or to limit the disclosure to the precise forms disclosed. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Some vehicles, such as vehicles with adaptive cruise control modes and autonomous vehicles, include computer-controlled modes of operation, where a computing system is used to navigate and / or steer the vehicle along a travel route. Additionally, vehicles may include safety developments and innovations that help prevent collisions and protect the vehicle and people. For example, some vehicles are equipped with technologies such as computer-controlled vehicle safety and collision avoidance systems designed to support driver awareness, decision-making, and vehicle operation over a wide range of speeds. There are vehicle safety systems that provide features that help address several key areas of accident protection, namely, preventing or mitigating frontal collisions (e.g., crash detection), keeping the driver in his lane (e.g., lane departure alert), and improving road safety during night driving (e.g., automatic high beams). Additionally, embodiments of the present disclosure implement a leading vehicle danger system that is designed to, for example, capture images of expired license plates on the vehicle to visually ascertain whether certain driver risk factors are exhibited by the leading vehicle (and driver) that indicate the vehicle is potentially dangerous. In response, the leading vehicle hazard system may cause the vehicle to perform computer-controlled maneuvers to safely avoid the potentially dangerous vehicle, thereby substantially reducing the likelihood of a dangerous collision with that vehicle that could result in loss, damage, and / or bodily injury.

[0010] Problems surrounding vehicle collisions can be exacerbated in instances where the drivers involved in the event have additional risk factors, such as being uninsured, being unlicensed, or driving an unregistered vehicle. For example, if an accident occurs and one of the drivers is uninsured, a myriad of negative consequences immediately follow, including the need to sue for compensation through an attorney (as the only way to recover damage-related losses). Furthermore, drivers with certain risk factors may be difficult to identify (e.g., not identifiable / contactable if the driver causes an accident, hit-and-run, etc.) and prone to risky and / or erratic behavior that may be potentially dangerous to other drivers on the road. According to a study conducted by the AAA Foundation for Road Safety, drivers without valid licenses are responsible for 20 percent of all automobile accidents. This means that, on average, automobile accidents with unlicensed drivers cause approximately 8,400 deaths each year in the United States. Furthermore, it has been reported that there is a 1 in 7 probability that an uninsured driver will be involved in an accident in the United States. Unregistered vehicles (and vehicles registered out of state or outside the United States) also represent a substantial portion of the vehicle population on the road, increasing the likelihood that drivers will encounter vehicles that are not substantially identifiable for various accident-related purposes (e.g., police reports, insurance claims, etc.). For example, in California (based on an analysis of over 98,000 vehicle records), the average rate of unregistered vehicles operated was found to be approximately 3.38%.

[0011] There are some existing collision avoidance systems that can detect that a nearby vehicle may pose a safety threat by observing the movement and / or maneuvering of the vehicle. For example, existing collision avoidance systems can detect that an oncoming vehicle traveling in an adjacent lane is suddenly swerving into the vehicle's current lane, which may result in an accident. However, conventional collision avoidance systems are limited by monitoring the vehicle's behavior, but are not designed to determine whether the driver of the vehicle may have risk factors that may be dangerous, such as being unregistered, uninsured, and the like. An embodiment of the present disclosure specifically provides a mechanism in the vehicle that can use image data to detect whether a nearby vehicle may be associated with one or more risk factors, and as a result, can automatically maneuver in relation to a vehicle that is deemed to be potentially dangerous in a manner that improves safety (e.g., collision prevention). Thus, embodiments of the present disclosure provide enhanced safety features that may provide protection from harm to drivers, passengers, persons in other vehicles on the roadway, and pedestrians, and further reduce financial losses (e.g., lawsuits, etc.) and property losses (e.g., vehicle damage, etc.) often associated with accidents with high-risk drivers (e.g., uninsured, unlicensed, etc.).

[0012] Referring now to FIG. 1, an example road environment is depicted that includes a vehicle 110 traveling on a roadway with the vehicle 120 configured to implement a leading vehicle danger system 130 and functions as disclosed herein. FIG. 1 illustrates that while the vehicle 120 is in operation, e.g., while being driven by a human driver, the vehicle 120 may travel at a particular speed within a lane on the roadway. While the vehicle 120 is being driven along the roadway, FIG. 1 illustrates that another vehicle 110 is also traveling nearby along the same portion of the roadway. In particular, the vehicle 110 is shown traveling within the same lane (e.g., the center lane) and coming directly ahead of the vehicle 120. Thus, for purposes of explanation, the vehicle 110 is referred to as a "leading vehicle" or (adversary (ado) vehicle) in relation to the vehicle 120 and in relation to its location ahead of it. This is a common road environment in several different real-life scenarios, e.g., driving during rush hour, driving in a populated area (e.g., urban area), and the like. Furthermore, with vehicle 120 traveling in such close proximity to vehicle 110 (directly behind in the same lane), the likelihood of a collision between vehicles 110, 120 may increase if, for example, leading vehicle 110 suddenly performs a risky maneuver, such as rapidly slowing down and / or stopping, in front of vehicle 120.

[0013] For illustrative purposes, vehicle 110 is also being operated by a driver who has one or more risk factors that ultimately render vehicle 110 identifiable. For example, the driver of vehicle 110 may not have registered vehicle 110 with its appropriate jurisdiction (e.g., state DMV). As a result, rear license plate 111 of vehicle 110 does not display a visual identifier (e.g., a registration sticker) that indicates vehicle 110 is properly registered with a local and / or authorized DMV. FIG. 1 illustrates that rear license plate 111 does not have a visible registration sticker that can be used to identify the current owner / operator of vehicle 110 or to further determine that vehicle 110 is currently registered and operating lawfully. Thus, in the event of a collision with the vehicle 110, there may be no records associated with the vehicle 110 and / or the records may be inaccurate (e.g., the vehicle is still registered to the previous owner) that a person (e.g., a police officer) at the scene of the accident may have access to in order to contact, locate, or otherwise accurately identify the driver / owner of the vehicle 110. If important driver information, such as the driver / owner's name, address, and phone number, cannot be obtained, identification of the driver / owner and location of the vehicle 110 may not be obtained, thereby effectively rendering the vehicle 110 unidentifiable for necessary post-accident procedures, such as filing an accident report, insurance claims, and the like. To mitigate this dire situation for the driver of the host vehicle 120, the leading vehicle danger system 130 has the ability to identify leading vehicle risk factors from image data acquired about the vehicle 110 and maneuver in a manner to avoid a collision with a high-risk or potentially dangerous vehicle 110, which may be dangerous and exacerbated by a substantially unidentifiable vehicle 110.

[0014] In the example of Fig. 1, vehicle 120 may include at least one imaging device 121 having imaging capabilities and positioned to, among other things, obtain image data of one or more nearby vehicles in the vicinity of vehicle 120. Fig. 1 illustrates imaging device 121 implemented, for example, as an on-board forward-facing camera positioned near the front of vehicle 120 to capture images of leading vehicle 110 traveling in the same lane as vehicle 120 on the roadway, which images may be analyzed to determine whether vehicle 110 is associated with a risk factor or is otherwise dangerous. Imaging device 121 may be implemented as an external digital image system or sensor (e.g., camera, LiDAR, radar, ultrasonic sensor) integrated into (e.g., on-board) the vehicle that may capture image data, images, video, visual data, visual representations, and the like. Additionally, in some embodiments, the imaging device 121 enables additional collision avoidance related functions such as real-time detection of traffic parameters within the vicinity of the vehicle 120 along the route, e.g., the presence of other vehicles, vehicle speed, and vehicle movement, traffic, and the like.

[0015] In operation with the leading vehicle risk system 130, the imaging device 121 is employed to capture images of areas of the leading vehicle 110, such as the license plate, bumper, windshield, etc., that may display visual cues that may be indicative of the vehicle 110 having one or more risk factors, including being unregistered, having expired registration, being an uninsured driver, and the like. FIG. 1 illustrates an example of the imaging device 121 capturing image data 133 of the rear license plate 111 of the leading vehicle 110. However, this example is not intended to be limiting, and the imaging device 121 and system 130 of the present disclosure may obtain and utilize image data from other areas of the leading vehicle 110 as deemed necessary and / or appropriate. For example, in some states in the United States, in addition to the front and rear license plates, there is additional vehicle registration information (e.g., expiration date, state of registration, etc.) that is displayed on the vehicle's front windshield. In an embodiment, the system 130 may capture images from multiple areas of the leading vehicle 110 and compare, for example, whether the rear license plate, windshield, and rear license plate of the leading vehicle 110 all display visual indications of a hazard to validate the analysis and increase the accuracy of the results.

[0016] As can be seen in FIG. 1 , the imaging device 121 captures at least one image 133 (also referred to herein as image data) of the rear license plate 111 attached to the leading vehicle 110. The captured image data 133 conveys that the license plate 111 is severely damaged and does not have a current registration sticker visually displayed. These visual cues captured in the image data 133 may indicate that the leading vehicle 110 has a substantial possibility of being unregistered (e.g., a stolen license plate) and / or having an expired registration (e.g., no valid registration sticker), which may be deemed dangerous by the leading danger system 130. The captured image data 133 of the leading vehicle 110 is then input into the leading vehicle danger system 130. The leading vehicle danger system 130 is configured to perform image analysis on the received image data 133 to determine whether the leading vehicle 120 is dangerous, and ultimately trigger an autonomous action to avoid a collision if the vehicle 110 is deemed to be a high risk.

[0017] In particular, the vehicle 120 is shown to include a leading vehicle hazard system 130. The leading vehicle hazard system 130 may be implemented as a vehicle controller, computing hardware, software, firmware, or combination thereof, programmed to detect visual indications that the vehicle is hazardous and / or associated with a risk factor according to the techniques of this disclosure. In some embodiments, the leading vehicle hazard system 130 may be a stand-alone controller. Alternatively, the leading vehicle hazard system 130 may be implemented by configuring a main vehicle on-board processor or CPU. Furthermore, FIG. 1 shows that the leading vehicle hazard system 130 may include several other components, including, but not limited to, an image-based hazard analysis device 131 and a safety response device 132. In some embodiments, the vehicle 120 may obtain image data from other communicatively connected vehicles within its vicinity on the road (e.g., a V2V network), where this additional image data may also be processed by the leading vehicle hazard system 130. For example, other vehicles in adjacent lanes of the road or traveling ahead of vehicle 110 may capture additional images of leading vehicle 110 from other perspectives, which may be collaboratively compiled to serve as inputs to leading vehicle hazard system 130 for analysis.

[0018] The image-based analysis hazard analysis device 131 may comprise a processor, which is programmed with instructions and data to perform image analysis of image data received with respect to a preceding vehicle, and to determine correlations between visual indicators that may be observed as a result of the image analysis and hazards and / or risk factors that may be determined from the observation of the visual indicators. Thus, the image-based hazard analysis device 131 is configured with image analysis software and / or algorithms that enable various image analysis functions. The image-based hazard analysis device 131 may be programmed to extract meaningful information from images (e.g., digital images) of a vehicle by digital image processing techniques. As an example, the image-based hazard analysis device 131 may perform image analysis tasks, such as noting areas of the vehicle that display relevant information, such as license plates, windshields, etc., and recognizing designated hazard information from those areas of the vehicle that may indicate certain risk factors. Examples of hazard information that may be recognized from the image data (based on image analysis) may include, but are not limited to, damaged license plates / tags, license plate / tag numbers (e.g., missing numbers / letters, unrecognized and / or invalid tag numbers), missing license plates / tags, missing registration stickers, dates associated with tags (e.g., month / year), registration sticker colors (e.g., color corresponds to registration expiration year), license plate / tag state (e.g., in the U.S.), license plate / tag country (e.g., outside the U.S.), diplomatic license plates / tags, and other visual indicators of the aforementioned hazards and driver / vehicle risk factors. In some embodiments, the image-based hazard analysis device 131 may use image analysis to identify characteristics and features related to a human driver of a vehicle and may determine whether the driver of the vehicle may be associated with a particular risk factor, such as uninsured, unlicensed, intoxicated, criminal history, traffic incident records, and the like. Additionally, in some embodiments, the image-based hazard analysis device 131 may have the ability to access databases and / or records of third-party entities. External third parties may have information relevant to accessing risk factors, such as state DMVs, insurance companies, police, and the like.The image-based risk analysis device 131 may contact a third party to receive auxiliary data that contributes to the determination as to whether a vehicle is potentially risky. For example, an insurance company may provide data indicating that there is no current insurance policy associated with a license plate number extracted from an image acquired by the system 130. The image-based risk analysis device 131 may thus use that third party data in addition to its indicated visually acquired risk information to determine that the vehicle has a high risk of, for example, being unregistered and being driven by an uninsured driver.

[0019] The image-based risk analysis device 131 is further configured to process the results of the image analysis to detect whether the vehicle is potentially dangerous. The image-based risk analysis device 131 may be programmed to determine a correlation between the recognized risk information (based on the image analysis) and one or more risk factors used to consider the vehicle as dangerous. As an example, the image-based risk analysis device 131 may be programmed to correlate a missing license plate (recognized by the analysis of the image data) with some risk factors determined by the system 130 to be dangerous, such as the vehicle being unregistered, having an expired registration, or being a stolen vehicle. Examples of correlations defined between risk factors that serve as a detection of hazards may include, but are not limited to, damaged license plates / tags correlated to unregistered vehicles, missing license plates / tags correlated to unregistered, stolen, unrecognizable or invalid license plate / tag numbers correlated to unregistered, stolen, missing registration stickers correlated to unregistered, expired registration, past dates (e.g., month / year) of license / tags correlated to expired registration, unused / past color of registration stickers correlated to expired registration, out-of-state license plates / tags correlated to potential unregistered, foreign license plates / tags correlated to potential unregistered, diplomatic license plates / tags correlated to potential unregistered, and other visual indicators that may be correlated to one or more of the foregoing hazards and driver / vehicle risk factors.

[0020] Referring back to the example of FIG. 1 , the image-based risk analysis device 131 may perform image analysis on the received image data 133 and extract essential information from the image to determine whether the leading vehicle 110 is a potential risk to the vehicle 120. For example, by analyzing the image 133, the image-based risk analysis device 131 may recognize that the rear license plate 111 is damaged and missing a current registration sticker. By extracting this important risk information from the analysis image, the image-based risk analysis device 131 may visually detect that the leading vehicle 110 may have certain risk factors associated with it. In this case, the image-based risk analysis device 131 applies the defined correlation to determine that the leading vehicle 110 has a high risk of being an unregistered vehicle based on the observations regarding the damaged tag and missing registration.

[0021] In response to the image-based hazard analysis device 131 making a determination that the vehicle is potentially hazardous, the image-based hazard analysis device 131 sends an output to the safety response device 132. When the safety response device 132 recognizes that a nearby vehicle has been detected as hazardous by the image-based hazard analysis device 131, the safety response device 132 may generate an appropriate safety maneuver (e.g., autonomous) to avoid a collision with the hazardous vehicle.

[0022] According to an embodiment, the vehicle 120 may be an autonomous vehicle. As used herein, "autonomous vehicle" refers to a vehicle configured to operate in an autonomous operating mode. "Autonomous operating mode" refers to one or more computing systems of the vehicle 120 being used to navigate and / or steer the vehicle along a travel route with a level of input from a human driver that varies with the operating mode. Thus, the vehicle 120 may have multiple autonomous operating modes, where, further accordingly, each responds to the leading vehicle hazard system 130 with a varying level of automated response. In some embodiments, the vehicle 120 may have an unsupervised autonomous operating mode. "Unsupervised autonomous operating mode" refers to one or more computing systems being used to steer the vehicle along a travel route fully autonomously without requiring any necessary input or supervision from a human driver. Thus, as an unsupervised autonomous vehicle 120, the leading vehicle hazard techniques and responses may be highly or fully automated. For example, the leading vehicle hazard system 130 may be configured to communicate control to operate the vehicle 120 autonomously and safely. For example, after the safety response device 132 communicates a safety command 134 to the vehicle 120 operating as an autonomous vehicle, the vehicle 120 may automatically make the necessary adjustments (e.g., accelerate or decelerate) without human driver interaction. Thus, the vehicle 120 may act on the safety command or control in response to detection of a dangerous preceding vehicle in a fully autonomous manner.

[0023] Alternatively or in addition to the modes described above, the vehicle 120 may have one or more semi-autonomous operating modes. A "semi-autonomous operating mode" means that the navigation and / or steering of the vehicle 120 along the travel route is performed in part by one or more computing systems, and the navigation and / or steering of the vehicle 120 along the travel route is performed in part by a human driver. An example of a semi-autonomous operating mode is when an adaptive cruise control system is enabled. In such a case, the speed of the vehicle 120 may be automatically adjusted to maintain a safe distance from the vehicle in front based on data received from on-board sensors, but the vehicle 120 is otherwise operated manually by a human driver. Upon receiving a driver input to change the vehicle's speed (e.g., by pressing the brake pedal to reduce the vehicle's speed), the adaptive cruise control system is disabled and the vehicle's speed is reduced. Thus, when the vehicle 120 is operating as a semi-autonomous vehicle, leading vehicle hazard techniques and responses may be partially automated. In one example, the safety response device 132 communicates the newly generated (or updated) control to the vehicle 120 operating as a semi-autonomous vehicle under the adaptive cruise control function. The vehicle 120 may automatically make some of the necessary adjustments (e.g., acceleration) without human driver interaction. Alternatively, the vehicle 120 may notify the driver that driver input is required in response to the new (or updated) safety command 134. For example, upon detecting that the leading vehicle is potentially dangerous and a potential collision (e.g., proximity) with the vehicle 110 is imminent, the vehicle 120 may receive a safety command from the safety response device 132 and automatically control (e.g., reduce) the speed of the vehicle 120 to ensure the driver's careful driving. In response, the vehicle 120 may also present a notification on its dashboard display that a speed reduction is necessary due to safety constraints. The notification gives the driver an opportunity to press the brake pedal to slow down the vehicle 120 to travel at a safe speed.

[0024] As mentioned above, the vehicle 120 in the environment 100 has the capability to drive autonomously. In this case, one or more safety commands 134 may be defined and generated by a safety response device 132 designed to achieve a desired safety factor (e.g., collision avoidance) for the vehicle 120 during autonomous operation. The safety response device 132 may comprise a processor programmed with instructions and data to generate one or more safety commands 134 to control the vehicle in a manner to avoid a collision with (or otherwise safely steer away from) a dangerous preceding vehicle. In this example, upon receiving a determination from the image-based hazard analysis device 131 that the preceding vehicle is dangerous, the safety response device 132 generates an automatic (or semi-autonomous) safety maneuver that is communicated to the vehicle 120 via the safety command 134, which enables autonomous driving control of the vehicle 120 in a manner governed by one or more safety constraints (e.g., target leading / following distances, target speeds, etc.) that are primarily focused on “collision avoidance” with the dangerous vehicle during the vehicle's 120's current operation in the environment 100. The safety commands 134 generated by the safety response devices 132 may implement semi-autonomous (e.g., partially computer controlled) or fully autonomous operation for the vehicle. Examples of safety maneuvers communicated in the safety commands 134 may include, but are not limited to, increasing speed, decreasing speed, changing direction, changing lanes, and the like.

[0025] Referring back to the example of FIG. 1 , the safety response device 132 may receive an output from the image-based risk analysis device 131 indicating that the leading vehicle 110 is determined to be risky, i.e., has a risk factor of being unregistered, based on a visual observation that the rear license plate 111 of the leading vehicle 110 is severely damaged and is missing a current registration sticker. As mentioned above, having an accident with a vehicle having a risk factor such as being unregistered can be a significant problem. For example, if the vehicle 110 causes a collision with the vehicle 120 and the driver of the vehicle 110 decides to flee the scene of the accident (e.g., to avoid financial responsibility, criminal responsibility, etc.), since the vehicle 110 is likely unregistered (from the visually acquired risk information), the car and driver cannot be identified at a later date, and the driver of the vehicle 120 may not have all of the information necessary to fully complete accident-related tasks such as filling out an insurance claim, contacting the driver, filing a police report, and the like. Furthermore, as disclosed herein, the leading vehicle danger system 130 implements a separate form of danger detection that is not limited to how the vehicle is being driven. As previously mentioned, many conventional collision avoidance systems rely solely on observing when a vehicle performs dangerous maneuvers, such as reaching dangerous speeds, erratic movements, swerving, improper lane changes, and the like, to determine that the vehicle is a danger and / or safety threat. In contrast, even if the leading vehicle 110 is nominally being driven and is not otherwise detected as dangerous by conventional collision avoidance systems, the leading vehicle danger system 130 can still use other visible indications (e.g., license plates) that the vehicle 110 is potentially dangerous and should be avoided.

[0026] Thus, the safety response device 132 may determine that the vehicle 120 should maneuver away from the vehicle 110 by changing lanes after the system 130 considers the vehicle 110 to be potentially dangerous. For example, the safety response device 132 may detect that an adjacent lane (e.g., the leftmost lane) is clear, and thus generate a safety command 134 to implement an autonomous lane-change maneuver that controls the movement of the vehicle 120 into the left lane to safely avoid the proximity of the dangerous vehicle 110 and mitigate any issues that may result from not being able to identify the vehicle 110. The safety response device 132 may trigger other functions that may supplement the safety maneuver, such as the generation of notifications, warnings, alerts, and other visual, audio, and haptic outputs that enable the driver to operate more safely during operation of the vehicle 120, providing additional reaction time. Additionally, the safety response device 132 may generate notifications, warnings, or alerts to operators of other vehicles, which may be traveling on the road behind the vehicle 120 and thus approaching the section of road on which the dangerous vehicle 110 is currently traveling. The drivers of the approaching vehicles, which may for example be communicatively connected to the vehicle 120, are also notified regarding the dangerous vehicle 110 currently traveling along the road (and other changes related to traffic conditions) so that they have additional time to modify their operations or route accordingly to avoid a collision and / or proximity with the vehicle 110.

[0027] As a result, as disclosed herein, the leading vehicle danger system 130 provides advanced vehicle safety functionality that may visually identify (e.g., with image data and image analysis) that a vehicle may be associated with risk factors and / or be potentially dangerous. In particular, embodiments of the present disclosure capture and analyze images of specific areas of the vehicle, such as license plates, to detect high-risk visual indications related to the vehicle in a manner that is independent of and does not require observing how the vehicle is maneuvering.

[0028] 2 illustrates a vehicle 200, e.g., an autonomous vehicle, configured to implement the preceding vehicle hazard detection capabilities of the present disclosure. In particular, FIG. 2 depicts the vehicle 200 including a preceding vehicle hazard detection component 214. According to an embodiment of the present disclosure, the preceding vehicle hazard component 214 is configured to perform several advanced vehicle safety capabilities, including capturing one or more images of a designated area of ​​another vehicle located nearby, such as a rear license plate, analyzing the images to extract hazard information that may indicate that the vehicle is associated with a risk factor and / or is hazardous, analyzing the images to identify the driver of the vehicle and / or access the associated driving record, determining whether the vehicle is potentially hazardous based on the hazard information extracted from the images, and performing an autonomous safety maneuver to safely avoid the vehicle determined to be hazardous.

[0029] In some implementations, vehicle 200 may also include sensors 208, electronic storage 232, a processor 234, and / or other components. Vehicle 200 may be configured to communicate with one or more client computing platforms 204 according to a client / server architecture and / or other architecture. In some implementations, a user may access vehicle 200 via client computing platform 204.

[0030] The sensors 208 may be configured to generate output signals that convey operational information about the vehicle. The operational information may include values ​​of operational parameters of the vehicle. The operating parameters of vehicle 200 may include yaw rate, side slip speed, slip angle, percent slip, friction, degree of steering, heading, trajectory, forward slip angle corresponding to full tire saturation, rear slip angle corresponding to full tire saturation, maximum stable steering angle taking speed / friction into account, gravity constant, coefficient of friction between the tires of vehicle 200 and the roadway, distance from the center of gravity of vehicle 200 to the front axles, distance from the center of gravity of vehicle 200 to the rear axles, total mass of vehicle 200, total longitudinal force, rear longitudinal force, front longitudinal force, total lateral force, rear lateral force, front lateral force, longitudinal velocity, lateral velocity, longitudinal acceleration, brake engagement, steering wheel position, time derivative of steering wheel position, throttle, time derivative of throttle, gear, exhaust, revolutions per minute, miles per minute, emissions, and / or other operating parameters. In some implementations, at least one of the sensors 208 may be a vehicle system sensor included in an engine control module (ECM) system or an electronic control module (ECM) system of the vehicle 200. In some implementations, at least one of the sensors 208 may be a vehicle system sensor separate from the vehicle's ECM system, whether or not in communication with the ECM system. Combinations and derivations of information (or parameters reflective of information) are contemplated within the scope of this disclosure. For example, in some implementations, the current operating information may include a yaw rate and / or a derivative thereof for a particular user in the vehicle 100.

[0031] In some implementations, the sensors 208 may include, for example, one or more of an altimeter (e.g., an acoustic altimeter, a radar altimeter, and / or other type of altimeter), a barometer, a magnetometer, a pressure sensor (e.g., a static pressure sensor, a dynamic pressure sensor, a pitot sensor, etc.), a thermometer, an accelerometer, a gyroscope, an inertial measurement sensor, a proximity sensor, a global positioning system (or other position) sensor, a tilt sensor, a motion sensor, a vibration sensor, an image sensor, a camera, a depth sensor, a distance sensor, an ultrasonic sensor, an infrared sensor, a light sensor, a microphone, an airspeed sensor, a ground speed sensor, an altitude sensor, a medical sensor (including a blood pressure sensor, a pulse oximeter, a heart rate sensor, a driver alert sensor, an ECG sensor, etc.), a degree of freedom sensor (e.g., a 6DOF and / or a 9DOF sensor), a compass, and / or other sensors. As used herein, the term "sensor" may include one or more sensors configured to generate an output that conveys information related to position, location, distance, motion, movement, acceleration, and / or other motion-based parameters. The output signals generated by (and / or information based thereon) the individual sensors may be stored in electronic files and / or transferred. In some implementations, the output signals generated by (and / or information based thereon) the individual sensors may be streamed to one or more other components of vehicle 200. In some implementations, the sensors may also include sensors in nearby vehicles (e.g., communicating with the target vehicle via a V2V or other communication interface) and / or infrastructure sensors (e.g., communicating with the target vehicle via a V2I or other communication interface).

[0032] The sensor 208 may be configured to generate output signals that convey visual information and / or contextual information. The contextual information may characterize a contextual environment around the vehicle. The contextual environment may be defined by parameter values ​​for one or more context parameters. The context parameters may include one or more characteristics of fixed or moving obstacles (e.g., size, relative position, motion, class of object (e.g., automobile, bicycle, pedestrian, etc.), etc.), the number of lanes on the roadway, the direction of traffic in adjacent lanes, associated traffic signs and signals, one or more characteristics of the vehicle (e.g., size, relative position, motion, class of object (e.g., automobile, bicycle, pedestrian, etc.)), the direction of travel of the vehicle, the lane position of the vehicle on the roadway, the date and time, ambient conditions, the topography of the roadway, obstacles in the roadway, and / or others. The roadway may include city roads, urban roads, highways, on-ramps, and / or off-ramps. The roadway may also include a surface type, e.g., asphalt pavement, concrete, mud, gravel, slush, etc., or a surface condition, e.g., wet, icy, slippery, dry, etc. The lane position of the vehicle on the roadway may illustratively be that the vehicle is in the left-most lane of a four-lane highway, or that the vehicle is straddling two lanes. The topography may include changes in elevation and / or slope of the roadway. The obstacles may include one or more of other vehicles, pedestrians, bicyclists, motorcyclists, tire debris from a previous vehicle accident, and / or other obstacles that the vehicle needs to avoid. The traffic conditions may include a reduction in speed on the roadway, an increase in speed on the roadway, a reduction in the number of lanes on the roadway, an increase in the number of lanes on the roadway, an increase in the number of vehicles on the roadway, and / or others. The ambient conditions may include external temperature, rain, hail, snow, fog, and / or other naturally occurring conditions.

[0033] In some implementations, the sensor 208 may include a virtual sensor, an imaging sensor, a depth sensor, a camera, and / or other sensors. As used herein, the terms “camera”, “sensor”, and / or “image sensor”, and / or “imaging device” may include any device that captures an image, including, but not limited to, a single lens-based camera, a calibrated camera, a camera array, a solid-state camera, a mechanical camera, a digital camera, an image sensor, a depth sensor, a remote sensor, a LiDAR, an infrared sensor, a (monochrome) complementary metal oxide semiconductor (CMOS) sensor, an active pixel sensor, and / or other sensors. Each sensor may be configured to capture information, including, but not limited to, visual information, video information, audio information, geolocation information, orientation and / or motion information, depth information, and / or other information. The visual information captured by the sensor 208 may be in the form of a digital image and / or video including red, green, blue (RGB) color values ​​representing the image. Information captured by one or more sensors may be marked, time-stamped, annotated, and / or otherwise processed so that information captured by other sensors may be synchronized with, aligned with, annotated with, and / or otherwise associated with it. For example, contextual information captured by an image sensor may be synchronized with information captured by an accelerometer or other sensor. Output signals generated by (and / or information based thereon) each image sensor may be stored in an electronic file and / or transferred.

[0034] In some implementations, the image sensor may be integrated into electronic storage, such as electronic storage 232, such that the captured information may be stored, at least initially, in embedded storage integrated into a particular vehicle, such as vehicle 200. In some implementations, the one or more components of an individual vehicle may include one or more cameras. For example, the cameras may include one or more image sensors and electronic storage media. In some implementations, the image sensor may be configured to transfer the captured information to one or more components of the system, including, but not limited to, remote electronic storage media, for example, through the "cloud."

[0035] Vehicle 200 may be configured with machine-readable instructions 206. Machine-readable instructions 206 may include one or more instruction components. The instruction components may include computer program components. The instruction components may include one or more of a leading vehicle hazard component 212, a controller 216, and / or other instruction components.

[0036] As a general description, the illustrated components in the machine-readable instructions 206 include a leading vehicle danger component 212. As described above with reference to FIG. 1, the leading vehicle danger component 212 is configured to perform image capture and analysis to detect, for example, that the other vehicle has at least one visible indication of a risk factor, such as a missing or obstructed license plate. The leading vehicle danger component 212 may utilize one or more vehicle sensors 208 (e.g., cameras) to capture image data of the other vehicle. In response to a determination by analysis of the image that the other vehicle is dangerous (e.g., a missing license plate indicates that the vehicle may be unregistered), the leading vehicle danger component 212 may implement an autonomous safety maneuver that enables the host vehicle to avoid a collision and / or proximity with the dangerous other vehicle. The leading vehicle danger component 212 generates safety commands to control the operation of the vehicle 200 according to the functioning automation level of the vehicle 200. For example, the commands generated may be specific to one or more of Level 0 (no driving automation), Level 1 (driving assistance), Level 2 (partial driving automation), Level 3 (conditional driving automation), Level 4 (high driving automation), and Level 5 (full driving automation). In this manner, leading vehicle hazard component 212 may perform varying levels of automation operations that control vehicle 200 to avoid potential hazards associated with unidentified vehicles, unverified owners, and the like.

[0037] Figure 3 illustrates a drive system of a vehicle 320 that may include the preceding vehicle hazard detection system disclosed herein. As can be seen in Figure 3, the vehicle 320 may include an internal combustion engine 14 and one or more electric motors 22 (which may also function as generators) as a power source. The drive force generated by the internal combustion engine 14 and the motor 22 may be transmitted to one or more wheels 34 via a torque converter 16, a transmission 18, a differential gear device 28, and a pair of axles 30.

[0038] The vehicle 320 may be driven / powered by either or both of the engine 14 and the motor 22 as a driving source for traveling. For example, a first driving mode may be an engine-only driving mode that uses only the internal combustion engine 14 as a driving source. A second driving mode may be an EV driving mode that uses only the motor 22 as a driving source. A third driving mode may be a hybrid electric vehicle (HEV) driving mode that uses the engine 14 and the motor 22 as a driving source. In the engine-only driving mode and the HEV driving mode, the vehicle 320 relies on power generated by at least the internal combustion engine 14, and the clutch 15 may be included to engage the engine 14. In the EV driving mode, the vehicle 2 may be powered by power generated by the motor 22, while the engine 14 is stopped and the clutch 15 is disengaged.

[0039] The engine 14 may be an internal combustion engine, such as a gasoline engine, diesel engine, or similar power supply engine, where fuel is injected into a combustion chamber and burned. The cooling system 12 may be provided to cool the engine 14, such as by removing excess heat from the engine 14. For example, the cooling system 12 may be implemented to include a radiator, a water pump, and a series of cooling channels. In operation, the water pump circulates coolant through the engine 14 to absorb excess heat from the engine. The heated coolant is circulated through the radiator to remove heat from the coolant, and the cold coolant may then be recirculated through the engine. A fan may also be included to increase the cooling capacity of the radiator. The water pump, and in some examples the fan, may operate via a direct or indirect connection to a drive shaft of the engine 14. In other applications, either or both of the water pump and fan may be operated by current, such as from a battery 44.

[0040] The power control circuit 14A may be provided to control the drive (output torque) of the engine 14. The power control circuit 14A may include a throttle actuator for controlling an electronic throttle valve to control fuel injection, an ignition device to control ignition timing, and the like. The power control circuit 14A may perform power control of the engine 14 according to command control signals provided from an electronic control unit 50, described below. The power control may include, for example, throttle control, fuel injection control, and ignition timing control.

[0041] The motor 22 may also be used to provide power in the vehicle 320 and is electrically powered via a battery 44. The battery 44 may be implemented as one or more batteries or other power storage devices, including, for example, lead acid batteries, lithium ion batteries, capacitive storage devices, etc. The battery 44 may be charged by a battery charger 45 that receives energy from the internal combustion engine 14. For example, an alternator or generator may be directly or indirectly connected to a drive shaft of the internal combustion engine 14 to generate current as a result of operation of the internal combustion engine 14. A clutch may be included to engage / disengage the battery charger 45. The battery 44 may also be charged by the motor 22, for example, by regenerative braking or coasting, during which time the motor 22 operates as a generator.

[0042] The motor 22 may be powered by a battery 44 to generate power to move the vehicle and regulate vehicle speed. The motor 22 may also function as a generator to generate power, such as when coasting or braking. The battery 44 may also be used to power other electrical or electronic systems in the vehicle. The motor 22 may be connected to the battery 44 via an inverter 42. The battery 44 may include, for example, one or more batteries, capacitive storage units, or other storage suitable for storing electrical energy that may be used to power the motor 22. When the battery 44 is implemented using one or more batteries, the batteries may include, for example, nickel metal hydride batteries, lithium ion batteries, lead acid batteries, nickel cadmium batteries, lithium ion polymer batteries, and other types of batteries.

[0043] An electronic control unit 50 (described below) may be included and may control the vehicle's electric drive components and other vehicle components. For example, electronic control unit 50 may control inverter 42 to regulate the drive current provided to motor 22 and regulate the current received from motor 22 during regenerative coasting and braking. As a more specific example, the output torque of motor 22 may be increased or decreased by electronic control unit 50 through inverter 42.

[0044] A torque converter 16 may be included to control the application of power from the engine 14 and motor 22 to the transmission 18. The torque converter 16 may include a viscous fluid coupling that transfers rotational power from a power source to a drive shaft through the transmission. The torque converter 16 may include a conventional torque converter or a lock-up torque converter. In other embodiments, a mechanical clutch may be used in place of the torque converter 16.

[0045] A clutch 15 may be included to couple and disengage the engine 14 from the vehicle drive train. In the illustrated example, a crankshaft 32, which is an output member of the engine 14, may be selectively coupled to the motor 22 and the torque converter 16 via the clutch 15. The clutch 15 may be implemented, for example, as a multiple disk type hydraulic friction coupling device, and its coupling is controlled by an actuator, such as a hydraulic actuator. The clutch 15 may be controlled such that its coupling state is fully coupled, slipping coupled, and fully disengaged, depending on the pressure applied to the clutch. For example, the torque capacity of the clutch 15 may be controlled according to hydraulic pressure provided from a hydraulic control circuit (not shown). When the clutch 15 is coupled, power transmission is provided in the power transmission path between the crankshaft 32 and the torque converter 16. On the other hand, when the clutch 15 is disengaged, power from the engine 14 is not transmitted to the torque converter 16. In the slipping coupled state, the clutch 15 is coupled and power is provided to the torque converter 16 according to the torque capacity (transmitted torque) of the clutch 15.

[0046] As mentioned above, the vehicle 320 may include an electronic control unit 50. The electronic control unit 50 may include circuitry for controlling various aspects of the vehicle operation. The electronic control unit 50 may include, for example, a microcomputer including one or more processing units (e.g., a microprocessor), memory storage (e.g., RAM, ROM, etc.), and I / O devices. The processing unit of the electronic control unit 50 executes instructions stored in the memory to control one or more electrical systems or subsystems in the vehicle. The electronic control unit 50 may include multiple electronic control units, such as an electronic engine control module, a powertrain control module, a transmission control module, a suspension control module, a body control module, etc. As a further example, electronic control units may be included to control systems and functions, such as doors and door locks, lighting, human-machine interfaces, cruise control, telematics, braking systems (e.g., ABS, ESC, or regenerative braking systems), battery management systems, etc. These various control units may be implemented using two or more separate electronic control units or using a single electronic control unit.

[0047] In the example shown in FIG. 3, the electronic control unit 50 receives information from a number of sensors included in the vehicle 320. For example, the electronic control unit 50 may receive signals indicative of a vehicle operating state or characteristic, or signals that can be used to derive a vehicle operating state or characteristic. These may include, but are not limited to, ACC for an accelerometer operating amount, NE (engine RPM) for the rotational speed of the internal combustion engine 14, NMG (motor RPM) for the rotational speed of the motor 22, and NV for the vehicle speed. These may also include NT for the output of the torque converter 16 (e.g., output amperes indicative of motor power), B for the brake operating amount / pressure, and battery SOC (i.e., the amount of charge for the battery 44 as detected by the SOC sensor). Thus, the vehicle 320 may include a number of sensors 52 that can be used to detect various conditions inside or outside the vehicle and provide the sensed conditions to the engine control unit 50 (which may again be implemented as one or more individual control circuits). In one embodiment, sensors 52 may be included to directly or indirectly detect one or more conditions, such as, for example, fuel efficiency, EE, motor efficiency, EMG, hybrid (internal combustion engine 14 + MG 12) efficiency, acceleration, ACC, etc.

[0048] Further, the one or more sensors 52 may be configured to detect and / or sense changes in the position and orientation of the vehicle 320, for example, based on inertial acceleration, etc. In one or more arrangements, the electronic control unit 50 may obtain signals from vehicle sensors including an accelerometer, one or more gyroscopes, an inertial measurement unit (IMU), a dead reckoning system, a global navigation satellite system (GNSS), a global positioning system (GPS), a navigation system, and / or other suitable sensors. In one or more arrangements, the electronic control unit 50 receives a signal from a speedometer to determine the current speed of the vehicle 320.

[0049] In some implementations, one or more of the sensors 52 may include their own processing capabilities to calculate results for additional information that may be provided to the electronic control unit 50. In other embodiments, one or more of the sensors may be data collection only sensors that provide only raw data to the electronic control unit 50. Further embodiments may include hybrid sensors that provide a combination of raw and processed data to the electronic control unit 50. The sensors 52 may provide analog or digital outputs. Additionally, as mentioned above, one or more of the sensors 52 may be configured to detect and / or sense in real-time. As used herein, the term "real-time" refers to a level of processing responsiveness that allows a user or system to sense quickly enough about a particular process or decision being made or for the processor to follow some external process.

[0050] The sensors 52 may be included to detect not only vehicle conditions but also external conditions as well. Sensors that may be used to detect external conditions may include, for example, sonar sensors, radar sensors, LiDAR sensors, or other vehicle proximity sensors, and cameras or other image sensors. In some embodiments, the cameras may be high dynamic range (HDR) cameras or infrared (IR) cameras. Image sensors may be used to detect traffic signs indicating, for example, current speed limits, road curvature, obstacles, etc. Still other sensors may include those that may detect road gradients. Some sensors may be used to actively detect passive environmental objects, while other sensors may be included and used to detect active objects, such as objects used to implement smart roadways that may actively transmit and / or receive data or other information. Thus, one or more sensors 52 may be configured to obtain and / or detect driving environment data. For example, the environmental sensors may be configured to detect, quantify, and / or detect objects in at least a portion of the vehicle 320's external environment, and / or information / data about the objects. The objects may be stationary objects and / or dynamic objects. Additionally, the sensors may be configured to detect, measure, quantify, and / or sense other things in the environment external to the vehicle 320, such as, for example, lane markers, signs, traffic lights, traffic signs, lanes, crosswalks, curbs near the vehicle 320, off-road objects, etc.

[0051] The sensors 52 may be included to detect not only vehicle conditions but also external conditions as well. Sensors that may be used to detect external conditions may include, for example, sonar sensors, radar sensors, LiDAR sensors, or other vehicle proximity sensors, and cameras or other image sensors. In some embodiments, the cameras may be high dynamic range (HDR) cameras or infrared (IR) cameras. Image sensors may be used to detect traffic signs indicating, for example, current speed limits, road curvature, obstacles, etc. Still other sensors may include those that may detect road gradients. Some sensors may be used to actively detect passive environmental objects, while other sensors may be included and used to detect active objects, such as objects used to implement smart roadways that may actively transmit and / or receive data or other information. Thus, one or more sensors 52 may be configured to obtain and / or detect driving environment data. For example, the environmental sensors may be configured to detect, quantify, and / or detect objects in at least a portion of the vehicle 320's external environment, and / or information / data about the objects. The objects may be stationary objects and / or dynamic objects. Additionally, the sensors may be configured to detect, measure, quantify, and / or sense other things in the environment external to the vehicle 320, such as, for example, lane markers, signs, traffic lights, traffic signs, lanes, crosswalks, curbs near the vehicle 320, off-road objects, etc.

[0052] 4 is shown using a processor and memory circuitry, as described below with reference to the circuitry disclosed herein, the leading vehicle hazard system 430 may be implemented utilizing any form of circuitry including, for example, hardware, software, or a combination thereof. By way of further example, one or more processors, controllers, ASICs, PLAs, PALs, CPLDs, FPGAs, logic components, software routines, or other mechanisms may be implemented to comprise the leading vehicle hazard system 430.

[0053] The communication circuitry 401 is either or both of a wireless transceiver circuitry 402 with an associated antenna 414 and a wired I / O interface 404 with an associated hardwired data port (not shown). As this example illustrates, communication with the leading vehicle hazard system 430 may include either or both of a wired and wireless communication circuitry 401. In some embodiments, the communication circuitry 401 may implement IR wireless communication from the vehicle to the hydrogen fuel station. The wireless transceiver circuitry 402 may include a transmitter and receiver (not shown) to enable wireless communication via any of a number of communication protocols, whether standardized, proprietary, open, point-to-point, networked, or otherwise, such as, for example, WiFi, Bluetooth, Near Field Communication (NFC), Zigbee, IrDA, and any of a number of other wireless communication protocols. The antenna 414 is connected to the wireless transceiver circuitry 402 and is used by the wireless transceiver circuitry 402 to wirelessly transmit radio signals to wireless devices to which it is connected, as well as to receive radio signals. These RF signals may include nearly any type of information transmitted by leading vehicle hazard system 430 to and / or received from other entities, such as sensors 452 and vehicle systems 458 .

[0054] Wired I / O interface 404 may include a transmitter and receiver (not shown) for hardwired communication with other devices. For example, wired I / O interface 404 may provide a hardwired interface to sensors 452 and other components including vehicle systems 458. Wired I / O interface 404 may communicate with other devices using Ethernet or any of a number of other wired communication protocols, whether standardized, proprietary, open, point-to-point, networked, or otherwise.

[0055] The power supply 412 may include one or more of a battery or batteries (whether rechargeable or primary, such as lithium ion, lithium polymer, NiMH, NiCd, NiZn, and NiH2, to name a few), a power connector (e.g., for connecting to vehicle supplied power), an energy harvester (e.g., solar cell, piezoelectric system, etc.), or any other suitable power supply.

[0056] The sensors 452 may include sensors 52, such as those described above with reference to the example of FIG. 3. The sensors 452 may include additional sensors that may or may not be included in a standard vehicle 420 in which the leading vehicle hazard system is implemented. In the example shown, the sensors 452 include a vehicle acceleration sensor 412, a vehicle speed sensor 414, a wheel spin sensor 416 (e.g., one for each wheel), a tire pressure monitoring system (TPMS) 420, an accelerometer such as a three-axis accelerometer 422 for detecting vehicle roll, pitch, and yaw, a vehicle clearance sensor 424, a side-to-side and front-to-rear slip ratio sensor 426, and an environmental sensor 428 (e.g., for detecting salinity or other environmental conditions). Additional sensors 432 may also be included as may be appropriate for a given implementation.

[0057] Vehicle systems 458 may include any of a number of different vehicle components or subsystems used to control or monitor various aspects of the vehicle and its performance. In this example, vehicle systems 458 include a GPS or other vehicle positioning system 472, a torque splitter 474 that may control the distribution of power between the wheels of the vehicle, such as by controlling front / rear and left / right torque splits, an engine control circuit 476 for controlling the operation of an engine (e.g., internal combustion engine 14), a cooling system 478 for providing cooling to the motor, power electronics, engine, or other vehicle systems, a suspension system 480, such as, for example, a height adjustable air suspension system, and other vehicle systems.

[0058] During operation, the leading vehicle hazard system 430 may receive information from various vehicle sensors 452. Also, the driver may manually enable the cruise control mode by operating the switch 405. The communication circuitry 401 may be used to transmit and receive information between the leading vehicle hazard system 430 and the sensors 452, and between the leading vehicle hazard system 430 and the vehicle systems 458. Also, the sensors 452 may communicate directly or indirectly with the vehicle systems 458 (e.g., via the communication circuitry 401 or otherwise).

[0059] The terms circuitry and components as used herein may describe a given unit of functionality that may be performed according to one or more embodiments of the present application. Components as used herein may be implemented utilizing any form of hardware, software, or combination thereof. For example, one or more processors, controllers, ASICs, PLAs, PALs, CPLDs, FPGAs, logic components, software routines, or other mechanisms may be implemented to constitute a component. Various components described herein may be implemented as separate components, or the described functions and features may be shared, in part or in whole, among one or more components. In other words, as will become apparent to one of ordinary skill in the art after reading this description, various features and functions described herein may be implemented in any given application. They may be implemented in one or more separate or shared components in various combinations and permutations. Although various features or functional elements may be individually described or claimed as separate components, it should be understood that such features / functions may be shared among one or more common software and hardware elements. The description does not require or imply that separate hardware or software components are used to implement such features or functions.

[0060] Where a component is implemented in whole or in part using software, the software element may be implemented to operate with a computational or processing component that can perform the preceding vehicle hazard detection functionality described with respect thereto. One exemplary such computational component is shown in FIG. 5. Various embodiments are described in terms of this exemplary computational component 500. After reading this description, it will be apparent to one of ordinary skill in the art how to implement applications using other computational components or architectures.

[0061] Referring now to FIG. 5, the computing components 500 may represent, for example, computing or processing capabilities found in auto-adjusting display, desktop, laptop, notebook, and tablet computers. They may be found in handheld computing devices (tablets, PDAs, smart phones, cell phones, palmtops, etc.). They may be found in workstations or other devices with displays, servers, or any other type of dedicated or general-purpose computing device as may be desirable or appropriate for a given application or environment. The computing components 500 may also represent computing capabilities that are embedded within or otherwise available to a given device. For example, the computing components may be found in other electronic devices, such as, for example, portable computing devices, and other electronic devices that may include some form of processing capabilities.

[0062] Computational components 500 may include, for example, one or more processors, controllers, control components, or other processing devices. This may include a processor 504. Processor 504 may be implemented using a general-purpose or special-purpose processing engine, such as, for example, a microprocessor, controller, or other control logic. Processor 504 may be connected to a bus 502. However, any communication medium may be used to facilitate interaction with other components of computational components 500 or to communicate with the outside world.

[0063] The computing component 500 may also include one or more memory components, referred to herein simply as main memory 508. For example, a random access memory (RAM) or other dynamic memory may be used to store information and instructions executed by the processor 504. The main memory 508 may also be used to store temporary variables or other intermediate information during execution of instructions to be executed by the processor 504. Similarly, the computing component 500 may include a read-only memory ("ROM") or other static storage device coupled to the bus 502 for storing static information and instructions for the processor 504.

[0064] The computing component 500 may also include one or more various forms of information storage mechanism 510, which may include, for example, a media drive 512 and a storage unit interface 520. The media drive 512 may include a drive or other mechanism to support a fixed or removable storage medium 514. For example, a hard disk drive, a solid state drive, a magnetic tape drive, an optical drive, a compact disk (CD) or a digital video disk (DVD) drive (R or RW), or other removable or fixed media drive may be provided. The storage medium 514 may include, for example, a hard disk, an integrated circuit assembly, a magnetic tape, a cartridge, an optical disk, a CD, or a DVD. The storage medium 514 may be any other fixed or removable medium that is read, written to, or accessed by the media drive 512. As these examples show, the storage medium 514 may include a computer usable storage medium having computer software or data stored therein.

[0065] In alternative embodiments, information storage mechanism 510 may include other similar means for allowing computer programs or other instructions or data to be loaded into computing component 500. Such means may include, for example, fixed or removable storage units 522 and interfaces 520. Examples of such storage units 522 and interfaces 520 may include program cartridges and cartridge interfaces, removable memory (e.g., flash memory or other removable memory components), and memory slots. Other examples may include PCMCIA slots and cards, and other fixed or removable storage units 522 and interfaces 520 that allow software and data to be transferred from storage unit 522 to computing component 500.

[0066] The computing component 500 may also include a communications interface 524. The communications interface 524 may be used to allow software and data to be transferred between the computing component 500 and external devices. Examples of the communications interface 524 may include a modem or soft modem, a network interface (such as an Ethernet, network interface card, IEEE802.XX, or other interface). Other examples include a communications port (such as a USB port, an IR port, an RS232 port, a Bluetooth interface, or other port), or other communications interface. The software / data transferred through the communications interface 524 may be carried on signals that may be electronic signals, electromagnetic signals (including optical signals), or other signals that may be exchanged by a given communications interface 524. These signals may be provided to the communications interface 524 through a channel 528. The channel 528 may carry signals and may be implemented using a wired or wireless communications medium. Some examples of channels may include a telephone line, a cellular link, an RF link, an optical link, a network interface, a local or wide area network, and other wired or wireless communications channels.

[0067] As used herein, the terms "computer program medium" and "computer usable medium" are generally used to refer to a transitory or non-transitory medium. Such medium may be, for example, memory 508, storage unit 520, medium 514, and channel 528. These and other various forms of computer program medium or computer usable medium may be involved in carrying one or more sequences of one or more instructions to a processing device for execution. The instructions embodied on the medium are generally referred to as "computer program code" or a "computer program product" (which may be grouped in the form of a computer program or other groupings). The instructions, when executed, may enable the computing component 500 to perform the features or functions of the present application as described herein.

[0068] It should be understood that the various features, aspects, and functions described in one or more of the individual embodiments are not limited in their applicability to the particular embodiment for which they are described. Instead, they may be applied alone or in various combinations to one or more other embodiments, regardless of whether the embodiment is described and whether the feature is presented as being part of the described embodiment. Thus, the breadth and scope of the present application should not be limited to any of the preferred embodiments described above.

[0069] Terms and phrases used herein, and variations thereof, unless expressly stated otherwise, should be construed as open ended, as opposed to limiting. As examples above, the term "including" should be read to mean "including but not limited to" or the like. The term "examples" is used to provide preferred examples of items in the description, rather than an exhaustive or limiting list of the items. The terms "a" or "an" should be read to mean "at least one," "one or more," or the like, and adjectives such as "conventional," "traditional," "usual," "standard," "known," and the like. Terms of similar meaning should not be construed as limiting the items described to items available during a given period or at a given time. Instead, they should be read to encompass conventional, traditional, ordinary, or standard technology that may be available or known at any time now or in the future. When the present specification refers to technology that is apparent or known to one of ordinary skill in the art, the technology encompasses what is apparent or known to one of ordinary skill in the art at any time now or in the future.

[0070] The presence in some instances of broader words and phrases such as "one or more," "at least," "but not limited to," or other similar phrases should not be read to imply that a narrower case is intended or required in instances where the broader phrase may not be present. Use of the term "component" does not imply that all aspects or functionality described or claimed as part of a component are configured in a common package. Indeed, any or all of the various aspects of a component, whether a control logic component or other component, may be combined in a single package or maintained separately, and may even be distributed in multiple groupings or packages, or across multiple locations.

[0071] Furthermore, the various embodiments described herein are described in terms of preferred block diagrams, flow charts, and other diagrams. As will be apparent to one of ordinary skill in the art after reading this specification, the illustrated embodiments and various alternatives thereof may be implemented without being limited to the illustrated examples. For example, the block diagrams and their accompanying description should not be construed as mandating a particular architecture or configuration.

[0072] Ex1 a vehicle sensor that captures image data of a leading vehicle, the image data corresponding to an area of ​​the leading vehicle that displays visible, identifiable information about the leading vehicle; A control device; The control device determines whether the preceding vehicle is dangerous based on the image data, In response to determining that the leading vehicle is a hazard, the system generates vehicle commands that implement computer-controlled automated driving maneuvers or actions to avoid a collision with the leading vehicle. Ex2. The system of Ex1, wherein the area of ​​the leading vehicle that displays visible identifiable information about the vehicle includes at least one of a rear license plate, a front license plate, a front windshield, and a rear windshield. Ex3. The system of Ex2, wherein the control device analyzes the image data of the leading vehicle to extract hazard information associated with the visible identifiable information regarding the leading vehicle. Ex4. The system of Ex3, wherein the risk information comprises at least one of: missing license plate number, missing license plate, damaged license plate, out-of-state license plate, foreign license plate, missing registration sticker, invalid registration sticker, and uninsured driver. Ex5. The system described in Ex4, wherein the control device determines that the preceding vehicle is dangerous by detecting the presence of extracted danger information based on an analysis of the image data of the preceding vehicle. Ex6. The system described in Ex5, wherein the control device determines that the preceding vehicle is dangerous by matching the extracted danger information to a defined risk factor or danger. Ex7. The system described in Ex1, wherein the control device generates the vehicle command based on an effective level of automation. Ex8. The system of Ex3, wherein the control device generates a notification in response to a determination that the leading vehicle is dangerous. Ex9. The system of Ex8, wherein the notification is communicated to a plurality of communicatively connected vehicles via a network. Ex10. The system of Ex9, wherein the network comprises vehicle-to-vehicle (V2V) communication. Ex11. The system of Ex2, wherein a license plate number is extracted from image data corresponding to the rear license plate of the leading vehicle. Ex12. The system of Ex11, wherein the license plate number is communicated to a third party entity to obtain additional data related to the preceding vehicle or a driver of the preceding vehicle. Ex13. The system of Ex9, wherein the notification is communicated to the connected vehicles as a warning that the leading vehicle has been detected as a danger. Ex14. The system of Ex1, wherein the computer-controlled automated driving maneuvers or actions include one or more of lane change maneuvers, acceleration, and deceleration. Ex15. A non-transitory computer-readable medium comprising instructions that, when read by a processor, cause the processor to: receiving image data of a leading vehicle, the image data corresponding to an area of ​​the leading vehicle displaying visible, identifiable information regarding the leading vehicle; determining whether the leading vehicle is a danger based on the image data; and In response to determining that the preceding vehicle is a hazard, generating vehicle commands to implement a computer-controlled automated driving maneuver or operation to avoid a collision with the preceding vehicle; A non-transitory computer-readable medium for causing Ex16. The non-transitory computer-readable medium of Ex15, wherein the received image is captured via a vehicle sensor. Ex17. The non-transitory computer-readable medium of Ex15, wherein the received image data is communicated over a network from a plurality of communicatively connected vehicles that capture image data of the preceding vehicle. Ex18. The processor further comprises: A non-transitory computer-readable medium as described in Ex16, comprising instructions for performing image analysis of the image data to extract hazard information related to the visible identifiable information regarding the leading vehicle. Ex19. The processor further comprises: A non-transitory computer-readable medium as described in Ex18, comprising instructions for determining that the leading vehicle is dangerous by detecting extracted danger information based on the image analysis. Ex20. The non-transitory computer-readable medium of Ex19, wherein detecting the extracted hazard includes determining that a license plate number extracted from the image data corresponding to a license plate behind the leading vehicle is invalid.

Claims

1. a vehicle sensor that captures image data of a leading vehicle, the image data corresponding to an area of ​​the leading vehicle that displays visible, identifiable information about the leading vehicle; A control device; The control device determines whether the preceding vehicle is dangerous based on the image data, In response to determining that the leading vehicle is a hazard, the system generates vehicle commands that implement computer-controlled automated driving maneuvers or actions to avoid a collision with the leading vehicle.

2. 2. The system of claim 1, wherein the area of ​​the leading vehicle that displays visible identifiable information about the vehicle comprises at least one of a rear license plate, a front license plate, a front windshield, and a rear windshield.

3. The system of claim 2 , wherein the controller analyzes the image data of the leading vehicle to extract hazard information associated with the visually identifiable information about the leading vehicle.

4. 4. The system of claim 3, wherein the hazard information comprises at least one or more of missing license plate numbers, missing license plates, damaged license plates, out-of-state license plates, foreign license plates, missing registration stickers, invalid registration stickers, and uninsured drivers.

5. The system of claim 4 , wherein the controller determines that the leading vehicle is a hazard by detecting the presence of extracted hazard information based on an analysis of the image data of the leading vehicle.

6. The system according to claim 5 , wherein the control device determines that the preceding vehicle is dangerous by correlating the extracted danger information with a defined risk factor or danger.

7. The system of claim 1 , wherein the controller generates the vehicle commands based on an effective level of automation, comprising one or more of a lane change maneuver, acceleration, and deceleration.

8. The system of claim 3 , wherein the controller generates a notification in response to determining that the leading vehicle is a hazard.

9. The system of claim 8 , wherein the notification is communicated over a network to a plurality of communicatively connected vehicles.

10. 10. The system of claim 9, wherein the network comprises vehicle-to-vehicle (V2V) communications.

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