Vehicle control system for vehicle driving behavior detection and automated vehicle avoidance control

Abstract

A vehicle control system for vehicle driving behavior detection and automated vehicle avoidance control is provided. A vehicle control system for driving behavior vehicle detection includes at least one vehicle object detector configured to detect motion of a target vehicle within an object detection range of a host vehicle; a vehicle user interface configured to display a visual indication to a driver of the host vehicle; and a vehicle control module configured to obtain detected motion parameters of the one or more target vehicles via the at least one vehicle object detector, determine a hazard index for each of the one or more target vehicles based on the detected motion parameters, and control the one or more target vehicles based on the hazard index. And in response to the hazard index of at least one of the one or more vehicles exceeding a specified threshold, updating a vehicle user interface to provide a visual notification of the identified driving behavior of the at least one of the one or more target vehicles exceeding the specified threshold.

Description

[0001] introduction

[0002] The information provided in this section is for the purpose of generally presenting the context of the present disclosure. The work of the presently named inventors, to the extent it is described in this section, and aspects of the description that may not otherwise qualify as prior art at the time of filing, are neither explicitly nor implicitly admitted to be prior art against the present disclosure. Technical Field

[0003] The present disclosure generally relates to vehicle control systems for vehicle driving behavior detection, including automated vehicle avoidance control. Background Art

[0004] The current trend in the automotive industry is to introduce safety systems to avoid or mitigate collisions. Some of the introduced safety systems, such as forward collision avoidance systems (FCAS), are intended to avoid or mitigate forward collisions between a vehicle equipped with such a system and an oncoming vehicle. For example, vehicle object detectors such as cameras, lasers, or lidars can be used to monitor vehicles on the road around the host vehicle. Summary of the invention

[0005] A vehicle control system for driving behavior vehicle detection and notification includes: at least one vehicle object detector, configured to detect the movement of one or more target vehicles within an object detection range of a host vehicle; a vehicle user interface, configured to display visual indications to a driver of the host vehicle; and a vehicle control module, configured to: obtain detected motion parameters of the one or more target vehicles via the at least one vehicle object detector, determine a hazard index for each of the one or more target vehicles based on the detected motion parameters, and in response to the hazard index of at least one of the one or more vehicles exceeding a specified threshold, update the vehicle user interface to provide a visual notification of the identified driving behavior of at least one of the one or more target vehicles exceeding the specified threshold.

[0006] In other features, each of the one or more target vehicles is displayed on a vehicle user interface, and the visual notification includes highlighting of the at least one of the one or more target vehicles on the vehicle user interface.

[0007] In other features, the vehicle control module is configured to generate at least one of an audible alert or a haptic seat feedback alert in response to a hazard index of at least one of the one or more target vehicles exceeding a specified threshold.

[0008] In other features, the vehicle control module is configured to: identify at least one of the one or more target vehicles approaching from the rear of the host vehicle in a lane adjacent to the host vehicle via the at least one vehicle object detector, and display a visual hazard indication in the lane adjacent to the host vehicle on a vehicle user interface.

[0009] In other features, the vehicle control module is configured to: identify, via the at least one vehicle object detector, a lane adjacent to the host vehicle that is free of other vehicles, and display, on a vehicle user interface, a visual clear lane indication in the lane adjacent to the host vehicle.

[0010] In other features, the host vehicle includes an advanced driver assistance system configured to control steering of the host vehicle, and the vehicle control module is configured to: in response to identifying that the lane adjacent to the host vehicle is free of other vehicles, automatically perform a steering maneuver to move the host vehicle into a lane adjacent to the host vehicle.

[0011] In other features, the vehicle control module is configured to display a visual indication of a recommended lane change direction on a vehicle user interface in response to identifying that a lane adjacent to the host vehicle is free of other vehicles.

[0012] In other features, the vehicle control module is configured to determine a hazard index for each of the one or more target vehicles based on at least one of a vehicle relative lateral acceleration, a vehicle longitudinal acceleration, a vehicle lane crossing index, a vehicle lane centering index, or a vehicle traffic rule violation index.

[0013] In other features, the vehicle control module is configured to determine a hazard index for each of the one or more target vehicles by combining weighted values ​​of a vehicle relative lateral acceleration, a vehicle longitudinal acceleration, a vehicle lane crossing index, a vehicle lane centering index, and a vehicle traffic rule violation index.

[0014] In other features, the vehicle control module is configured to: determine, for each of the one or more target vehicles, a driving behavior classification based on a weighted combination of the vehicle relative lateral acceleration and the vehicle longitudinal acceleration, and display a vehicle identifier on a vehicle user interface in response to the driving behavior classification exceeding a classification threshold.

[0015] In other features, the vehicle control module is configured to: determine, for each of the one or more target vehicles, a driving classification based on a weighted combination of a vehicle lane crossing index, a vehicle lane centering index, and a vehicle traffic rule violation index, and display a vehicle identifier on a vehicle user interface in response to the driving classification exceeding a classification threshold.

[0016] In other features, the vehicle control system is configured to determine a vehicle relative lateral acceleration by monitoring the lateral acceleration relative to a lane in which the vehicle is traveling, determine a vehicle lane crossing index by counting the number of occurrences of crossing a lane boundary of the lane in which the vehicle is traveling, determine a vehicle lane centering index by measuring an average vehicle distance to the center of the lane in which the vehicle is traveling, and determine a vehicle traffic rule violation index by determining at least the degree to which the vehicle exceeds a speed limit with respect to the lane in which the vehicle is traveling.

[0017] In other features, the vehicle control module is configured to: obtain an average number of determined vehicles exceeding a specified threshold for a road portion during a specified time period, and provide an indication of the vehicle level exceeding the specified threshold for the road portion on a navigation map of a vehicle user interface.

[0018] A method for driving behavior vehicle detection and notification includes: detecting driving motion parameters of one or more target vehicles within an object detection range of a host vehicle via at least one vehicle object detector, determining a hazard index for each of the one or more vehicles based on the detected driving motion parameters, and updating a vehicle user interface in response to the hazard index of at least one of the one or more target vehicles exceeding a specified threshold to provide a visual notification of the identified driving behavior of the at least one of the one or more target vehicles, wherein for each of the one or more target vehicles within the object detection range of the host vehicle, the detected driving motion parameters include a relative lateral acceleration of the target vehicle, a longitudinal acceleration of the target vehicle, a lane crossing index of the target vehicle, a lane centering index of the target vehicle, and a traffic rule violation index of the target vehicle.

[0019] In other features, the method includes displaying the one or more target vehicles on a vehicle user interface and highlighting the at least one of the one or more target vehicles on the vehicle user interface.

[0020] In other features, the method includes generating at least one of an audible alert or a haptic seat feedback alert in response to a hazard index of at least one of the one or more target vehicles exceeding a specified threshold.

[0021] In other features, the method includes identifying, via the at least one vehicle object detector, at least one of the one or more target vehicles approaching from the rear of the host vehicle in a lane adjacent to the host vehicle, and displaying, on a vehicle user interface, a visual hazard indication in the lane adjacent to the host vehicle.

[0022] In other features, the method includes identifying, via the at least one vehicle object detector, a lane adjacent to the host vehicle that is free of other vehicles, and displaying, on a vehicle user interface, a visual clear lane indication in the lane adjacent to the host vehicle.

[0023] In other features, the host vehicle includes an advanced driver assistance system configured to control steering of the host vehicle, and the method includes: in response to identifying that the lane adjacent to the host vehicle is free of other vehicles, automatically performing a steering maneuver to move the host vehicle into a lane adjacent to the host vehicle.

[0024] In other features, the method includes displaying a visual indication of a recommended lane change direction on a vehicle user interface in response to identifying that a lane adjacent to the host vehicle is free of other vehicles.

[0025] This application also includes the following options:

[0026] Solution 1. A vehicle control system for driving behavior vehicle detection and notification, the vehicle control system comprising:

[0027] at least one vehicle object detector configured to detect motion of one or more target vehicles within an object detection range of the host vehicle;

[0028] a vehicle user interface configured to display a visual indication to a driver of the host vehicle; and

[0029] A vehicle control module is configured to:

[0030] obtaining, via the at least one vehicle object detector, detected motion parameters of the one or more target vehicles;

[0031] determining a danger index for each of the one or more target vehicles based on the detected motion parameters; and

[0032] In response to the hazard index of at least one of the one or more vehicles exceeding a specified threshold, updating a vehicle user interface to provide a visual notification of the identified driving behavior of the at least one of the one or more target vehicles that exceeds the specified threshold.

[0033] Solution 2. A vehicle control system according to Solution 1, wherein:

[0034] Each of the one or more target vehicles is displayed on a vehicle user interface; and

[0035] The visual notification includes a highlighted display of the at least one of the one or more target vehicles on a vehicle user interface.

[0036] Option 3. A vehicle control system according to Option 1, wherein the vehicle control module is configured to generate at least one of an auditory alarm or a tactile seat feedback alarm in response to a danger index of at least one of the one or more target vehicles exceeding a specified threshold.

[0037] Option 4. The vehicle control system according to Option 1, wherein the vehicle control module is configured to:

[0038] identifying, via the at least one vehicle object detector, at least one of the one or more target vehicles approaching from the rear of the host vehicle in a lane adjacent to the host vehicle; and

[0039] A visual hazard indication is displayed on a vehicle user interface in a lane adjacent to the host vehicle.

[0040] Solution 5. The vehicle control system according to Solution 1, wherein the vehicle control module is configured to:

[0041] identifying, via the at least one vehicle object detector, a lane adjacent to the host vehicle that is free of other vehicles; and

[0042] A visual clear lane indication is displayed on a vehicle user interface in a lane adjacent to the host vehicle.

[0043] Solution 6. A vehicle control system according to Solution 5, wherein:

[0044] The host vehicle includes an advanced driver assistance system configured to control steering of the host vehicle; and

[0045] The vehicle control module is configured to, in response to identifying that the lane adjacent to the host vehicle is free of other vehicles, automatically perform a steering maneuver to move the host vehicle into the lane adjacent to the host vehicle.

[0046] Option 7. A vehicle control system according to Option 5, wherein the vehicle control module is configured to: in response to identifying that there are no other vehicles in the lane adjacent to the host vehicle, display a visual indication of the recommended lane change direction on the vehicle user interface.

[0047] Option 8. A vehicle control system according to Option 1, wherein the vehicle control module is configured to: for each of the one or more target vehicles, determine a hazard index based on at least one of the vehicle's relative lateral acceleration, the vehicle's longitudinal acceleration, the vehicle's lane crossing index, the vehicle's lane centering index, or the vehicle's traffic rule violation index.

[0048] Option 9. A vehicle control system according to Option 8, wherein the vehicle control module is configured to determine a hazard index for each of the one or more target vehicles by combining weighted values ​​of the vehicle's relative lateral acceleration, the vehicle's longitudinal acceleration, the vehicle's lane crossing index, the vehicle's lane centering index, and the vehicle's traffic rule violation index.

[0049] Option 10. The vehicle control system according to Option 8, wherein the vehicle control module is configured to:

[0050] For each of the one or more target vehicles, determining a driving behavior classification based on a weighted combination of the vehicle relative lateral acceleration and the vehicle longitudinal acceleration; and

[0051] In response to the driving behavior classification exceeding the classification threshold, a vehicle identifier is displayed on a vehicle user interface.

[0052] Option 11. The vehicle control system according to Option 8, wherein the vehicle control module is configured to:

[0053] For each of the one or more target vehicles, determining a driving classification based on a weighted combination of a vehicle lane crossing index, a vehicle lane centering index, and a vehicle traffic rule violation index; and

[0054] In response to the driving classification exceeding the classification threshold, a vehicle identifier is displayed on a vehicle user interface.

[0055] Solution 12. The vehicle control system according to Solution 8, wherein the vehicle control system is configured to:

[0056] determining a relative lateral acceleration of the vehicle by monitoring the lateral acceleration relative to the lane in which the vehicle is traveling;

[0057] determining a vehicle lane crossing index by counting the number of occurrences of crossing a lane boundary of a lane in which the vehicle is traveling;

[0058] determining a vehicle lane centering index by measuring an average vehicle distance to the center of a vehicle's lane of travel; and

[0059] The vehicle traffic rule violation index is determined by determining at least the degree to which the vehicle exceeds the speed limit with respect to the vehicle travel lane.

[0060] Embodiment 13. The vehicle control system according to embodiment 1, wherein the vehicle control module is configured to:

[0061] obtaining an average number of determined vehicles exceeding a specified threshold for a road portion during a specified time period; and

[0062] An indication of the vehicle level exceeding a specified threshold for the road portion is provided on a navigation map of a vehicle user interface.

[0063] Solution 14. A method for driving behavior vehicle detection and notification, the method comprising:

[0064] detecting, via at least one vehicle object detector, driving motion parameters of one or more target vehicles within an object detection range of the host vehicle;

[0065] determining a hazard index for each of the one or more vehicles based on the detected driving motion parameters; and

[0066] in response to the hazard index of at least one of the one or more target vehicles exceeding a specified threshold, updating a vehicle user interface to provide a visual notification of the identified driving behavior of the at least one of the one or more target vehicles,

[0067] For each of the one or more target vehicles within the object detection range of the main vehicle, the detected driving motion parameters include the relative lateral acceleration of the target vehicle, the longitudinal acceleration of the target vehicle, the lane crossing index of the target vehicle, the lane centering index of the target vehicle and the traffic rule violation index of the target vehicle.

[0068] Scheme 15. The method according to Scheme 14, further comprising:

[0069] displaying the one or more target vehicles on a vehicle user interface; and

[0070] The at least one of the one or more target vehicles is highlighted on a vehicle user interface.

[0071] Option 16. The method according to Option 14 further includes: generating at least one of an auditory alarm or a tactile seat feedback alarm in response to a danger index of at least one of the one or more target vehicles exceeding a specified threshold.

[0072] Scheme 17. The method according to Scheme 14, further comprising:

[0073] identifying, via the at least one vehicle object detector, at least one of the one or more target vehicles approaching from the rear of the host vehicle in a lane adjacent to the host vehicle; and

[0074] A visual hazard indication is displayed on a vehicle user interface in a lane adjacent to the host vehicle.

[0075] Scheme 18. The method according to Scheme 14, further comprising:

[0076] identifying, via the at least one vehicle object detector, a lane adjacent to the host vehicle that is free of other vehicles; and

[0077] A visual clear lane indication is displayed on a vehicle user interface in a lane adjacent to the host vehicle.

[0078] Scheme 19. The method according to Scheme 18, wherein:

[0079] The host vehicle includes an advanced driver assistance system configured to control steering of the host vehicle; and

[0080] The method includes, in response to identifying that a lane adjacent to the host vehicle is free of other vehicles, automatically performing a steering maneuver to move the host vehicle into a lane adjacent to the host vehicle.

[0081] Option 20. The method according to Option 18 further includes: in response to identifying that there are no other vehicles in the lane adjacent to the host vehicle, displaying a visual indication of the recommended lane change direction on the vehicle user interface.

[0082] Further areas of applicability of the present disclosure will become apparent from the detailed description, claims, and drawings.The detailed description and specific examples are intended for purposes of illustration only and are not intended to limit the scope of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0083] The present disclosure will become more fully understood from the detailed description and accompanying drawings, in which:

[0084] Figure 1 is a functional block diagram of an example embodiment of a vehicle including a reckless vehicle detection and notification system.

[0085] Figure 2 yes Figure 1 Block diagram of an example driving behavior classification system.

[0086] Figure 3 It's a picture. Figure 1 Illustration of an example lane crossing determination of a system.

[0087] Figure 4 is a flow chart depicting an example method for reckless vehicle detection and notification.

[0088] Figure 5 is an example human machine interface (HMI) for reckless vehicle detection and notification.

[0089] Figure 6 Pictured Figure 5 An example HMI is shown in which an identified hazardous lane and a recommended avoidance lane are identified.

[0090] Figure 7Pictured Figure 6 An example HMI including displayed turn recommendations and avoidance paths.

[0091] Figure 8 An example navigation map is illustrated depicting routes with high and low reckless vehicle frequencies identified.

[0092] In the drawings, reference numerals may be repeated to identify similar and / or identical elements. DETAILED DESCRIPTION

[0093] Some example embodiments include a vehicle control system and method for classifying the driving behaviors of vehicles surrounding a host vehicle based on detected driving motions of the surrounding vehicles in order to determine the associated reckless driving risk levels of the surrounding vehicles and perform recommended evasive driving actions to avoid collisions. For example, a hazard index may be quantified for each surrounding vehicle, which systematically classifies identified vehicles having a hazard index exceeding a specified threshold to increase the safety of the host vehicle.

[0094] The driver of the host vehicle may be notified about detected vehicles exceeding a specified threshold of danger index using, for example, augmented reality, a vehicle user interface of the dashboard, warnings associated with each identified target surrounding vehicle based on the danger index, etc. In addition, a collective danger index may be determined and assigned to areas or roads with a high frequency of reckless vehicle detections (e.g., a high frequency of vehicles with a danger index exceeding a specified threshold). This new index may be displayed or implemented, for example, in a vehicle navigation system to facilitate selection of the safest driving route, thereby avoiding those higher risk areas of encountering vehicles with a danger index exceeding a threshold.

[0095] In some example embodiments, the vehicle control module may detect the driving behavior of neighboring vehicles and classify the neighboring vehicles into different types, such as an identified aggressive driving vehicle, an identified distracted driving vehicle, etc. For example, the host vehicle's object detection sensors (such as cameras, lasers, lidar, etc.) may monitor the driving motion parameters of each surrounding vehicle to identify the surrounding vehicles' violent lateral and / or longitudinal acceleration / deceleration, lane contact or crossing, non-compliance with traffic rules and regulations, etc., to determine the driving behavior. The vehicle control module may utilize these categories and / or an overall risky driving index to plan an appropriate evasive driving response.

[0096] In various implementations, once a reckless vehicle (e.g., a vehicle with a danger index above a specified threshold) is detected, the vehicle control module can warn the driver, which may occur when the ADAS feature is not enabled. To inform the driver, the identified vehicle can be labeled, colored, highlighted, etc., such as using augmented reality or displaying a visual indication on a vehicle user interface to help the driver identify the identified vehicle on the road. In addition, the recommended driving maneuver can be suggested based on the vehicle control module's assessment of road and traffic conditions (such as identifying a lane adjacent to the host vehicle that is free of other vehicles).

[0097] When the ADAS feature is enabled, the driver may be notified of the identified vehicle. In this case, the driver may be notified of the planned maneuver that the ADAS feature will take in order to avoid the identified vehicle, such as by showing a visual indication of the planned driving maneuver using augmented reality or a visual notification on a vehicle user interface.

[0098] In some example embodiments, avoidance lanes may be highlighted (e.g., in green) and suggested to the driver, and lanes that are occupied (e.g., due to another vehicle in the lane) may be highlighted to warn the driver with another color (such as a red lane identifier).

[0099] In various implementations, an index may be assigned to areas or roads with a high frequency of detected recklessly driven vehicles collected over time. For example, vehicles with a higher level exceeding a hazard index threshold may be detected for roads that are currently undergoing road construction, have inappropriate lane markings, etc. The index may be embedded into a car navigation system to select a planned driving path to a destination with increased or maximum safety.

[0100] Reference now Figure 1 , the vehicle 10 includes front wheels 12 and rear wheels 13. Figure 1 , the drive unit 14 selectively outputs torque to the front wheels 12 and / or the rear wheels 13 via the transmissions 16 and 18, respectively. The vehicle 10 may include different types of drive units. For example, the vehicle may be an electric vehicle, such as a battery electric vehicle (BEV), a hybrid vehicle or a fuel cell vehicle, a vehicle including an internal combustion engine (ICE), or other types of vehicles.

[0101] Some examples of drive unit 14 may include any suitable electric motor, a power inverter, and a motor controller configured to control a power switch within the power inverter to adjust motor speed and torque during propulsion and / or regeneration. The battery system provides power to or receives power from the electric motor of drive unit 14 via the power inverter during propulsion or regeneration.

[0102] Although in Figure 1 The vehicle 10 includes one drive unit 14, but the vehicle 10 may have other configurations. For example, two separate drive units may drive the front wheels 12 and the rear wheels 13, one or more individual drive units may drive individual wheels, etc. As can be appreciated, other vehicle configurations and / or drive units may be used.

[0103] The vehicle control module 20 may be configured to control the operation of one or more vehicle components, such as the drive unit 14 (e.g., by commanding a torque setting of an electric motor of the drive unit 14). The vehicle control module 20 may receive inputs for controlling vehicle components, such as signals received from a steering wheel, an accelerator pedal, etc. The vehicle control module 20 may monitor vehicle telematics for safety purposes, such as vehicle speed, vehicle position, vehicle braking and acceleration, etc.

[0104] The vehicle control module 20 may receive signals from any suitable component for monitoring one or more aspects of the vehicle, including one or more vehicle sensors (such as cameras, microphones, pressure sensors, wheel position sensors, position sensors such as global positioning system (GPS) antennas, etc.).

[0105] like Figure 1 As shown in FIG. 1 , the vehicle 10 includes an optional rear object detector 24, an optional front object detector 26, and an optional side object detector 28. In various implementations, the vehicle 10 may include more or less (or not include) any of these optional sensors. Each object sensor may include any suitable camera, laser, lidar sensor, etc., which is used to detect objects around the vehicle 10, such as other target vehicles within the object detection range of the vehicle 10. The object detection range may include a threshold accuracy range of the laser or lidar sensor, an accuracy range of the camera field of view, etc. In some example embodiments, the vehicle object detector may be configured to detect a closest in-path vehicle (CIPV) (e.g., another vehicle in front of the current driving path of the vehicle 10), a vulnerable road user (VRU) (e.g., a pedestrian or a cyclist), etc.

[0106] The vehicle control module 20 can communicate with another device via a wireless communication interface, which may include one or more wireless antennas for transmitting and / or receiving wireless communication signals. For example, the wireless communication interface can communicate via any suitable wireless communication protocol, including but not limited to vehicle-to-everything (V2X) communication, Wi-Fi communication, wireless area network (WAN) communication, cellular communication, personal area network (PAN) communication, short-range wireless communication (e.g., Bluetooth), etc. The wireless communication interface can communicate with a remote computing device via one or more wireless and / or wired networks.

[0107] Figure 2 yes Figure 1 A block diagram of an example driving behavior classification system 200 is shown. Figure 2 As shown in , the driving behavior classification 200 can be composed of, for example Figure 1 The host vehicle may be a vehicle that includes a vehicle control module and a vehicle object detector for sensing the motion of other target vehicles on the same road as the host vehicle.

[0108] The driving behavior classifier 200 can be used to determine a reckless driving index for a target vehicle. For example, the driving behavior classifier 200 can receive driving motion parameters of another target vehicle from a vehicle object detector and calculate separate driving behavior indices, which are combined by the classifier 211 to determine an overall danger index (e.g., a reckless driving index) for the target vehicle.

[0109] like Figure 2 As shown in FIG. 2 , the driving behavior classification 200 may include a lane contact / crossing index 201, a longitudinal acceleration index 203, a relative lateral acceleration index 205, a lane centering index 207, and a traffic rule violation index 209. The classifier 211 may calculate a weighted combination of the lane contact / crossing index 201, the longitudinal acceleration index 203, the relative lateral acceleration index 205, the lane centering index 207, and the traffic rule violation index 209. Other example embodiments may use more or fewer (or different) driving motion parameters in order to classify reckless driving behavior.

[0110] The weighted combination may be compared to a specified threshold to determine whether the target vehicle should be identified as exhibiting reckless driving behavior. The classifier 211 may transmit the reckless driving determination to a driver human machine interface (HMI) of the vehicle 10 to display a visual notification highlighting the identified vehicle based on the transmitted reckless driving determination according to the risk index.

[0111] In some example embodiments, lane contact / crossing index 201 may be calculated by detecting lane contact / crossing occurrences of a target vehicle via an object detector and maintaining a count of the number of occurrences within a specified time period (e.g., within one minute, within five minutes, within an hour, etc.).

[0112] Figure 3 It's a picture. Figure 1 Schematic diagram of an example lane crossing determination by a system. Figure 3 , host vehicle 302 includes one or more object detectors to determine lane contact / crossing events for target vehicle 304. Object detectors of host vehicle 302 may be configured to determine whether target vehicle 304 contacts or crosses lane line 306 (or any other suitable road centerline or lane line).

[0113] The vehicle control module 20 may process the object detector data to perform Figure 3 For example, the vehicle control module may be configured to execute the following lane contact / crossing equation:

[0114]

[0115]

[0116]

[0117]

[0118] Where n is the buffer size, w obj is the vehicle width, is the lane width, ε is the slack variable, T(k) is the threshold, and N LC is the count of lane contact / crossing events.

[0119] The longitudinal acceleration index 203 may be calculated using any suitable longitudinal acceleration algorithm. An example algorithm includes the following equation:

[0120]

[0121]

[0122]

[0123] Where m is the moving average window size, is the maximum longitudinal acceleration, and dt is the sampling time.

[0124] The relative lateral acceleration index 205 may be calculated using any suitable lateral acceleration algorithm for determining the lateral acceleration of the target vehicle, such as the lateral acceleration relative to the lane of the target vehicle. An example algorithm includes the following equation:

[0125]

[0126]

[0127]

[0128] in is the maximum lateral acceleration.

[0129] Lane centering index 207 may be calculated using any suitable algorithm for determining, for example, the average distance of a target vehicle from the center of its driving lane. An example algorithm includes the following equation:

[0130]

[0131] The traffic rule violation index 209 may be calculated using any suitable longitudinal acceleration algorithm for determining the lateral acceleration of the target vehicle, such as the lateral acceleration relative to the lane of the target vehicle. An example algorithm includes the following equation:

[0132]

[0133] In some example embodiments, various indices may be combined to generate an overall hazard index (e.g., a reckless driving index) that may include different weights for the parameters. Example hazard index equations include:

[0134]

[0135] Where K LC , K ay , K ax , K D and K T is a set of weights based on the impact of each index. If the hazard index is above a specified threshold indicating reckless driving behavior, the vehicle control model may determine to classify the target vehicle as a recklessly driven vehicle (which may then be displayed on a vehicle user interface, etc.).

[0136] Figure 4 is a flow chart depicting an example method for reckless vehicle detection and notification. The process may be performed by, for example Figure 1The process begins at 404 by obtaining driving characteristic parameters of other target vehicles near the host vehicle (e.g., within the vehicle object detection range of the host vehicle, etc.). The target vehicle driving characteristic parameters may be obtained via one or more vehicle object detectors of the host vehicle.

[0137] At 408 , the vehicle control module is configured to generate a driving behavior classification index for each vehicle in the vicinity. Then, at 412 , control determines whether any of the target vehicles in the vicinity have a driving behavior index above a specified threshold.

[0138] If so, control proceeds to 416 to identify the vehicle in an HMI display (e.g., a vehicle user interface, a dashboard display, a windshield overlay, etc.) The identification may include a visual notification, a highlight of the identified vehicle (such as via a bounding box added to the display), an audible alert, a haptic seat vibration alert, etc.

[0139] At 420 , control identifies whether any other vehicle is approaching the host vehicle from behind in an adjacent lane. If any vehicle is approaching from behind at 424 , control displays a hazardous lane indicator at 428 .

[0140] After displaying the hazardous lane indicator at 428, or if the vehicle control module determines at 424 that no vehicle is approaching from behind, control proceeds to 432 to determine a recommended avoidance path. For example, the recommended avoidance path may include an adjacent lane in which no other vehicles are currently detected.

[0141] At 436, control displays the recommended avoidance path on the vehicle HMI. At 440, the vehicle control module is configured to determine whether the vehicle is equipped with an advanced driver assistance system (ADAS). If so, control initiates an automated steering maneuver to the recommended adjacent lane at 444. Once the identified vehicle has been avoided at 448 (e.g., when the identified reckless vehicle is no longer detected as being within a specified distance of the host vehicle), control returns to 404 to obtain new driving characteristic parameters of other target vehicles in the vicinity of the host vehicle.

[0142] Figure 5 is an example human machine interface (HMI) 500 for reckless vehicle detection and notification. Figure 5 As shown in , HMI 500 shows the current driving path of the host vehicle, wherein the lanes of the road are displayed. HMI 500 can be implemented, for example, in the dashboard of the host vehicle, projected onto the windshield of the vehicle, etc.

[0143] HMI 500 displays identified vehicles 502 having hazard index values ​​exceeding a specified threshold, and identified vehicles 504 having hazard index values ​​below a specified threshold. For example, vehicle 502 may have a hazard index value above a specified threshold indicating reckless driving behavior (e.g., as determined by sensing driving movement parameters of vehicle 502 by an object detector of the host vehicle). In some example embodiments, the specified threshold may be normalized to 1 based on monitored vehicle parameters as described herein, may be set at a specific value based on measured and tested values ​​of various vehicle parameters relative to driving behavior interpreted as normal vehicle operation or operation exceeding an identified safe driving boundary.

[0144] In contrast, vehicle 504 may have a hazard index value below a specified threshold indicating reckless driving behavior. HMI 500 may highlight identified vehicle 502 via any suitable visual notification, such as bounding box 506 .

[0145] For example, when ADAS features are not enabled, a reckless vehicle alert (RVA) may alert the driver when a vehicle having a hazard index value above a specified threshold is identified around the host vehicle. Figure 5 An example of how to use augmented reality to highlight the identified vehicle on the screen is illustrated. The vehicle can be highlighted by, for example, a red water drop symbol, a dotted square bounding box 506, etc. In addition, if the chime alarm system is enabled, a chime sound with an optional tactile alarm can assist the driver in identifying potential safety issues. A counter can be used to indicate the total number of reckless vehicles identified (e.g., the total number of vehicles that exceed a specified threshold of the danger index).

[0146] Figure 6 Pictured Figure 5 500, wherein an identified hazardous lane 508 and a recommended avoidance motorway 510 are identified. For example, if the vehicle control module identifies that another vehicle is approaching the host vehicle from behind in an adjacent lane, the HMI 500 may identify the hazardous lane 508 via, for example, red highlighting, a no-entry box displayed on the lane, etc.

[0147] If the vehicle control module identifies an adjacent lane with no other vehicles (e.g., based on the vehicle's object detection sensors, etc.), a recommended avoidance lane 510 may be identified on the HMI 500, such as by green highlighting, a free entry box displayed on the lane, etc.

[0148] In some example embodiments, if the identified vehicle is behind the host vehicle, then based on the identified vehicle's location and its predicted maneuvers, safe and unsafe areas on the road (e.g., areas with vehicles exceeding or falling below a specified threshold of the hazard index) are highlighted in green and red, respectively, to let the driver know the best possible actions that can be taken to avoid the reckless vehicle.

[0149] Figure 7 Pictured Figure 6 500, including displayed turn recommendation 514 and avoidance path 512. For example, if the vehicle control module identifies an adjacent lane with no other vehicles (e.g., based on the vehicle's object detection sensors, etc.), the HMI 500 can display an arrow for the turn recommendation 514 to show the driver the direction to turn to avoid the detected vehicle 502.

[0150] The HMI 500 may also display an avoidance path 512 to avoid the determined vehicle 502. The avoidance path 512 may illustrate directions for the host vehicle to move into the recommended avoidance maneuver lane 510.

[0151] For example, when the ADAS feature is enabled, the RVA can provide warning information and navigate the host vehicle to a safer operating area (e.g., a recommended unoccupied lane 510). Figure 7 As shown in , when two reckless vehicles are identified around the host vehicle (e.g., 1 in front of the host vehicle and 1 behind), a planned trajectory can be generated to navigate the host vehicle to an unoccupied area, as shown by the arrows. In this case, a lane change command can be executed using a chime and a haptic alert.

[0152] Figure 8 An example navigation map 800 is illustrated that depicts routes with identified high and low reckless vehicle frequencies. For example, the navigation map 800 can be a navigation feature of a host vehicle, can be displayed on a vehicle user interface, can be used for GPS navigation or automated driving control, etc.

[0153] like Figure 8 As shown in , the low reckless driver route 802 is illustrated as a solid line, while the high reckless driver route 804 is illustrated as a dashed line. For example, the vehicle control module can obtain data indicating the average number of recklessly driven vehicles detected on various roads over a specified time period.

[0154] This information can be used to highlight to drivers which road sections in the area present a higher risk of encountering more identified reckless driving vehicles. Figure 8In the example of FIG. 8 , the navigation map 800 may warn the driver that taking a diagonal route 804 may have a higher risk of encountering a recklessly driven vehicle than taking a different route 802 that has a lower frequency of recklessly driven vehicles.

[0155] In some example embodiments, a regional danger index (RHI) may be calculated to make the driver aware of roads with a high frequency of identified reckless driving vehicles and optionally route the navigation system around roads with a high threshold level of reckless driving in a particular area. The RHI may be calculated based on the number of recklessness triggers within a certain time period. The following example equation shows how the RHI may be calculated:

[0156]

[0157] In the above equation, R_tr is the reckless hazard trigger, and i represents the number of reckless driving occurrences detected during time T (eg, reckless driving occurrences that may be detected by other vehicles and transmitted to a central monitoring server, etc.).

[0158] Depending on the destination selected by the driver, if the RHI is high in an area or for a particular road, a warning may be given to the driver and the vehicle control module may be configured to prepare possible evasive driving maneuvers or recommendations if a detected recklessly driven vehicle is encountered. The RHI may also be sent to a route guidance system to avoid areas with high RHI when planning a driving route to a target destination for the host vehicle.

[0159] The foregoing description is merely illustrative in nature and is by no means intended to limit the present disclosure, its application or use. The broad teachings of the present disclosure can be implemented in a variety of forms. Therefore, although the present disclosure includes specific examples, the true scope of the present disclosure should not be so limited, because other modifications will become apparent after studying the drawings, the specification and the following claims. It should be understood that, without changing the principles of the present disclosure, one or more steps in the method can be performed in different orders (or simultaneously). In addition, although each embodiment is described above as having certain features, any one or more of those features described with respect to any embodiment of the present disclosure can be implemented in any other embodiment and / or combined with the features of any other embodiment, even if the combination is not explicitly described. In other words, the described embodiments are not mutually exclusive, and the arrangement of one or more embodiments with each other is still within the scope of the present disclosure.

[0160] Spatial and functional relationships between elements (e.g., between modules, circuit elements, semiconductor layers, etc.) are described using various terms, including "connected," "engaged," "coupled," "adjacent," "immediately adjacent," "on," "above," "below," and "disposed." Unless explicitly described as "direct," when describing a relationship between a first and a second element in the above disclosure, the relationship may be a direct relationship in which no other intervening elements exist between the first and second elements, but may also be an indirect relationship in which one or more intervening elements (either spatially or functionally) exist between the first and second elements. As used herein, the phrase "at least one of A, B, and C" should be interpreted to mean a logical (A or B or C) using a non-exclusive logical "or," and should not be interpreted to mean "at least one of A, at least one of B, and at least one of C."

[0161] In the various figures, the direction of the arrows, as indicated by the arrow heads, generally indicates the flow of information (such as data or instructions) of interest to the illustration. For example, when element A and element B exchange various information, but the information transmitted from element A to element B is relevant to the illustration, the arrow may be directed from element A to element B. The unidirectional arrow does not imply that no other information is transmitted from element B to element A. In addition, for information sent from element A to element B, element B may send a request or receipt confirmation of the information to element A.

[0162] In this application, including the definitions below, the term "module" or the term "controller" may be replaced with the term "circuit". The term "module" may refer to, be part of, or include: an application specific integrated circuit (ASIC); a digital, analog, or mixed analog / digital discrete circuit; a digital, analog, or mixed analog / digital integrated circuit; a combinational logic circuit; a field programmable gate array (FPGA); a processor circuit (shared, dedicated, or grouped) that executes code; a memory circuit (shared, dedicated, or grouped) that stores code executed by the processor circuit; other suitable hardware components that provide the described functionality; or a combination of some or all of the above, such as in a system on a chip.

[0163] The module may include one or more interface circuits. In some examples, the interface circuit may include a wired or wireless interface connected to a local area network (LAN), the Internet, a wide area network (WAN), or a combination thereof. The functionality of any given module of the present disclosure may be distributed among multiple modules connected via the interface circuit. For example, multiple modules may allow load balancing. In a further example, a server (also referred to as a remote or cloud) module may implement some functionality on behalf of a client module.

[0164] The term "code" as used above may include software, firmware, and / or microcode, and may refer to a program, a routine, a function, a class, a data structure, and / or an object. The term "shared processor circuit" covers a single processor circuit that executes some or all code from multiple modules. The term "group processor circuit" covers a processor circuit that executes some or all code from one or more modules in conjunction with an additional processor circuit. References to multiple processor circuits cover multiple processor circuits on discrete dies, multiple processor circuits on a single die, multiple cores of a single processor circuit, multiple threads of a single processor circuit, or a combination of the above. The term "shared memory circuit" covers a single memory circuit that stores some or all code from multiple modules. The term "group memory circuit" covers a memory circuit that stores some or all code from one or more modules in conjunction with additional memory.

[0165] The term "memory circuit" is a subset of the term "computer-readable medium". The term "computer-readable medium" as used herein does not encompass transient electrical or electromagnetic signals propagated through a medium (such as on a carrier wave); therefore, the term "computer-readable medium" may be considered to be tangible and non-transitory. Non-limiting examples of non-transitory tangible computer-readable media are non-volatile memory circuits (such as flash memory circuits, erasable programmable read-only memory circuits, or mask read-only memory circuits), volatile memory circuits (such as static random access memory circuits or dynamic random access memory circuits), magnetic storage media (such as analog or digital magnetic tape or hard drives), and optical storage media (such as CDs, DVDs, or Blu-ray discs).

[0166] The apparatus and method described in the present application can be implemented in part or in whole by a special-purpose computer, which is created by configuring a general-purpose computer to perform one or more specific functions embodied in a computer program. The functional blocks, flow chart components and other elements described above serve as software specifications, which can be converted into computer programs through the routine work of skilled technicians or programmers.

[0167] The computer program includes processor executable instructions stored on at least one non-transitory tangible computer readable medium. The computer program may also include or rely on stored data. The computer program may include a basic input / output system (BIOS) that interacts with the hardware of the special-purpose computer, device drivers that interact with specific devices of the special-purpose computer, one or more operating systems, user applications, background services, background applications, etc.

[0168] A computer program may include: (i) descriptive text to be parsed, such as HTML (Hypertext Markup Language), XML (Extensible Markup Language), or JSON (JavaScript Object Notation), (ii) assembly code, (iii) target code generated by a compiler from source code, (iv) source code for execution by an interpreter, (v) source code for compilation and execution by a just-in-time compiler, etc. By way of example only, source code may be written using syntax from languages ​​including: C, C++, C#, Objective-C, Swift, Haskell, Go, SQL, R, Lisp, Fortran, Perl, Pascal, Curl, OCaml, HTML5 (Hypertext Markup Language Version 5), Ada, ASP (Active Server Pages), PHP (PHP: Hypertext Preprocessor), Scala, Eiffel, Smalltalk, Erlang, Ruby, Visual Lua, MATLAB, SIMULINK, and

Claims

1. A vehicle control system for driving behavior vehicle detection and notification, the vehicle control system comprising: at least one vehicle object detector configured to detect motion of one or more target vehicles within an object detection range of the host vehicle; a vehicle user interface configured to display a visual indication to a driver of the host vehicle; as well as A vehicle control module is configured to: obtaining, via the at least one vehicle object detector, detected motion parameters of the one or more target vehicles; determining a danger index for each of the one or more target vehicles based on the detected motion parameters; as well as In response to the hazard index of at least one of the one or more vehicles exceeding a specified threshold, updating a vehicle user interface to provide a visual notification of the identified driving behavior of the at least one of the one or more target vehicles that exceeds the specified threshold.

2. The vehicle control system according to claim 1, wherein: Each of the one or more target vehicles is displayed on a vehicle user interface; and The visual notification includes a highlighted display of the at least one of the one or more target vehicles on a vehicle user interface.

3. The vehicle control system of claim 1 , wherein the vehicle control module is configured to generate at least one of an audible alarm or a haptic seat feedback alarm in response to a hazard index of at least one of the one or more target vehicles exceeding a specified threshold.

4. The vehicle control system of claim 1 , wherein the vehicle control module is configured to: identifying, via the at least one vehicle object detector, at least one of the one or more target vehicles approaching from the rear of the host vehicle in a lane adjacent to the host vehicle; and A visual hazard indication is displayed on a vehicle user interface in a lane adjacent to the host vehicle.

5. The vehicle control system of claim 1 , wherein the vehicle control module is configured to: identifying, via the at least one vehicle object detector, a lane adjacent to the host vehicle that is free of other vehicles; and A visual clear lane indication is displayed on a vehicle user interface in a lane adjacent to the host vehicle.

6. The vehicle control system according to claim 5, wherein: The host vehicle includes an advanced driver assistance system configured to control steering of the host vehicle; and The vehicle control module is configured to, in response to identifying that the lane adjacent to the host vehicle is free of other vehicles, automatically perform a steering maneuver to move the host vehicle into the lane adjacent to the host vehicle. 7 . The vehicle control system of claim 5 , wherein the vehicle control module is configured to display a visual indication of the recommended lane change direction on a vehicle user interface in response to identifying that the lane adjacent to the host vehicle is free of other vehicles.

8. A vehicle control system according to claim 1, wherein the vehicle control module is configured to: for each of the one or more target vehicles, determine a hazard index based on at least one of a vehicle relative lateral acceleration, a vehicle longitudinal acceleration, a vehicle lane crossing index, a vehicle lane centering index, or a vehicle traffic rule violation index.

9. A vehicle control system according to claim 8, wherein the vehicle control module is configured to: for each of the one or more target vehicles, determine a hazard index by combining weighted values ​​of vehicle relative lateral acceleration, vehicle longitudinal acceleration, vehicle lane crossing index, vehicle lane centering index and vehicle traffic rule violation index.

10. A method for driving behavior vehicle detection and notification, the method comprising: detecting, via at least one vehicle object detector, driving motion parameters of one or more target vehicles within an object detection range of the host vehicle; determining a hazard index for each of the one or more vehicles based on the detected driving motion parameter; as well as in response to the hazard index of at least one of the one or more target vehicles exceeding a specified threshold, updating a vehicle user interface to provide a visual notification of the identified driving behavior of the at least one of the one or more target vehicles, For each of the one or more target vehicles within the object detection range of the main vehicle, the detected driving motion parameters include the relative lateral acceleration of the target vehicle, the longitudinal acceleration of the target vehicle, the lane crossing index of the target vehicle, the lane centering index of the target vehicle and the traffic rule violation index of the target vehicle.

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