Avoidance steering threat area determination and control

Abstract

A vehicle system includes an Avoidance Steering (AES) module configured to automatically control a vehicle; and a control module. The control module is configured to: detect whether a first threat is present in front of the vehicle; in response to detecting a first threat in front of the vehicle, determining a path of the vehicle for AES manipulation to avoid the first threat; generating a threat region of interest lateral to the vehicle along a path of the vehicle for the AES maneuver; determining whether a second threat exists in the threat region of interest; and in response to determining that the second threat is present in the threat region of interest, preventing the AES module from initiating control of the vehicle in accordance with the AES manipulation. Other example vehicle systems and methods for evasive steering control in a vehicle are also disclosed.

Description

Background Art

[0001] 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 with respect to what is described in this section and aspects of the description that may not have originally qualified as prior art at the time of filing are neither explicitly nor implicitly admitted to be prior art against the present disclosure.

[0002] The present disclosure relates to avoidance steering threat zone determination and control.

[0003] Vehicles often include driver assistance systems. For example, driver assistance systems may include assisted evasive steering, blind spot detection, adaptive cruise control, lane departure warning, etc. Assisted evasive steering is a driver-initiated collision avoidance steering mechanism. When assisted evasive steering is employed and the driver begins to steer the vehicle around an object (e.g., another vehicle), the system applies additional steering torque to assist the vehicle in steering around the object. In some cases, after the vehicle passes the object, the system applies steering torque in the opposite direction. Summary of the invention

[0004] A vehicle system for evasive steering control in a vehicle includes: an avoidance evasive steering (AES) module configured to automatically control the vehicle; and a control module in communication with the AES module. The control module is configured to: detect whether a first threat exists in front of the vehicle; in response to detecting the first threat in front of the vehicle, determine a path of the vehicle for AES maneuvers to avoid the first threat in front of the vehicle; generate a threat region of interest lateral to the vehicle along the path of the vehicle for the AES maneuver; determine whether a second threat exists in the threat region of interest; and in response to determining that the second threat exists in the threat region of interest, prevent the AES module from initiating control of the vehicle according to the AES maneuver.

[0005] In other features, the control module is configured to, in response to determining that the second threat is not present in the threat zone of interest, transmit a control signal to the AES module to initiate control of the vehicle in accordance with the AES maneuver.

[0006] In other features, the threat region of interest is an irregular polygonal shape defined by boundaries corresponding to the geometry of a road in which the vehicle continues to move.

[0007] In other features, the control module is configured to construct vertices of the boundary based on one or more of a width of a road lane, a trajectory of the vehicle, an area associated with a first threat in front of the vehicle, and a width associated with the vehicle.

[0008] In other features, the control module is configured to: identify a second threat to the side of the vehicle while the vehicle is moving based on data received from one or more sensors; and project a vector to determine whether the second threat is present in the threat region of interest.

[0009] In other features, the control module is configured to: determine kinematic information associated with the second threat; and track the second threat based on the kinematic information.

[0010] In other features, the control module is configured to track the second threat based on one or more previous values ​​of the kinematic information.

[0011] In other features, the control module is configured to: receive vehicle data associated with one or more parameters of the vehicle while the vehicle is moving, the vehicle data indicating the intention of a driver controlling the vehicle; receive non-driver data indicating environmental parameters in front of the vehicle while the vehicle is moving; and detect whether the first threat is present in front of the vehicle based on the vehicle data and the non-driver data.

[0012] In other features, the one or more parameters of the vehicle include at least one of a steering angle received from a steering angle sensor in the vehicle and a brake signal received from a brake sensor in the vehicle.

[0013] In other features, the non-driver data includes data associated with another vehicle ahead of the vehicle.

[0014] In other features, the control module is configured to: determine a confidence value for the driver based on the vehicle data; determine a threat value based on the non-driver data; calculate a score based on the confidence value and the threat value; and detect whether the first threat is present in front of the vehicle based on the score and a threshold.

[0015] In other features, a vehicle includes a vehicle system configured to control an evasive turn of the vehicle.

[0016] A method for controlling evasive steering in a vehicle includes: detecting whether a first threat exists in front of the vehicle; in response to detecting the first threat in front of the vehicle, determining a path of the vehicle for an AES maneuver to avoid the first threat in front of the vehicle; generating a threat region of interest lateral to the vehicle along the path of the vehicle for the AES maneuver; determining whether a second threat exists in the threat region of interest; and in response to determining that the second threat exists in the threat region of interest, preventing an AES module from initiating control of the vehicle based on the AES maneuver.

[0017] In other features, the threat region of interest is an irregular polygonal shape defined by boundaries corresponding to the geometry of a road in which the vehicle continues to move.

[0018] In other features, the method further comprises constructing vertices of the boundary based on one or more of a width of a road lane, a trajectory of the vehicle, an area associated with a first threat in front of the vehicle, and a width associated with the vehicle.

[0019] In other features, determining whether the second threat is present in the threat region of interest includes: identifying a second threat to the side of the vehicle while the vehicle is moving based on data received from one or more sensors; and projecting a vector to determine whether the second threat is present in the threat region of interest.

[0020] In other features, the method further comprises determining kinematic information associated with the second threat; and tracking the second threat based on the kinematic information.

[0021] In other features, tracking the second threat includes tracking the second threat based on one or more previous values ​​of the kinematic information.

[0022] In other features, the method further includes: receiving vehicle data associated with one or more parameters of the vehicle while the vehicle is moving, the vehicle data indicating the intention of a driver controlling the vehicle; and receiving non-driver data indicating environmental parameters in front of the vehicle while the vehicle is moving.

[0023] In other features, detecting whether the first threat is present in front of the vehicle includes detecting whether the first threat is present in front of the vehicle based on the vehicle data and the non-driver data.

[0024] In other features, the method further comprises determining a confidence value for the driver based on the vehicle data; determining a threat value based on the non-driver data; and calculating a score based on the confidence value and the threat value.

[0025] In other features, detecting whether the first threat is present in front of the vehicle includes detecting whether the first threat is present in front of the vehicle based on the score and a threshold.

[0026] 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

[0027] The present disclosure will become more fully understood from the detailed description and accompanying drawings, in which: Figure 1 is a functional block diagram of an example vehicle system for evasive steering control in a vehicle according to the present disclosure; Figure 2 According to the present disclosure, Figure 1 A means of transport that is part of a transport system; Figure 3 According to the present disclosure Figure 2 a map of the vehicle, the threat vehicle ahead, and the threat areas of interest to the left and right of the vehicle; Figure 4 A means of transport according to the present disclosure and Figure 3 a map of one of the threat regions of interest having identified targets inside and outside the threat region of interest; Figure 5 According to the present disclosure Figure 4 a map of the threat region of interest having vectors of the identified targets projected inside and outside the threat region of interest; Figure 6 According to the present disclosure, a vehicle and Figure 4 a diagram of one of the threat regions of interest having a target path where AES manipulation is prevented; and Figure 7-11 is a flow chart of an example control process for evasive steering control in a vehicle according to the present disclosure.

[0028] In the drawings, reference numbers may be reused to identify similar and / or identical elements. DETAILED DESCRIPTION

[0029] The vehicle may implement assisted evasive steering (AES) for assisting the driver in steering around an object (such as another vehicle on the road). In this example, AES is a driver-initiated collision avoidance steering mechanism that applies additional steering torque to assist the vehicle in steering around an object. This helps the driver reach the maximum steering angle more quickly and thus avoid a collision with the object. Traditionally, AES is activated based on vehicle dynamics (e.g., changes in the forward movement of the vehicle in response to driver input) and the primary threat detected in front of the vehicle. Thus, traditional AES activation does not take into account various other threats around the vehicle (e.g., side threats). As a result, traditional AES may avoid potential threats and / or encounter false positive activations, each of which may result in an increased likelihood of a vehicle accident.

[0030] Vehicle systems and methods according to the present disclosure utilize a created threat zone adjacent to a vehicle that is shaped to fit the road geometry and a target path for the vehicle to determine whether a threat is present in the threat zone, and then prevent or enable an AES maneuver for the vehicle based on whether the threat is present in the threat zone. For example and as further explained herein, when another threat (e.g., a side threat) is not present in the created threat zone, the vehicle system and method trigger an AES maneuver to avoid a threat in front of the vehicle (e.g., a primary front threat). In doing so, the vehicle system and method provide a robust and accurate assisted steering avoidance solution while utilizing a low-power computer hardware platform and low-cost sensors.

[0031] Reference now Figure 1 , a block diagram of an example vehicle system 100 is presented for evasive steering control in a vehicle. Figure 1 As shown in FIG. 1 , the vehicle system 100 generally includes a control module 102, an AES control module 104, a detection module 106, and various sensors. Figure 1 In the example of , the sensors may include a steering sensor 108 and a brake sensor 110, as shown. Additionally, the detection module 106 may include one or more sensors 112 and / or one or more cameras 114, as further explained below.

[0032] although Figure 1 The vehicle system 100 is illustrated as including specific modules, but it should be appreciated that one or more other modules may be employed when desired. In addition, although the vehicle system 100 is illustrated as including a plurality of separate modules, any combination of modules (e.g., control module 102, AES control module 104, etc.) and / or their functionality may be integrated into one or more modules. Further, although the vehicle system 100 is illustrated as including a plurality of separate modules, any combination of modules (e.g., control module 102, AES control module 104, etc.) and / or their functionality may be integrated into one or more modules. Figure 1The vehicle system 100 is shown as including particular sensors, but it should be appreciated that the system 100 and / or other systems may include more or fewer sensors, sensors with different functionality, etc.

[0033] In various embodiments, the modules and sensors of the vehicle system 100 may communicate with each other and may share parameters via a network 116, such as a controller (or car) area network (CAN). In such an example, the parameters may be shared via one or more data buses of the network 116. Thus, various parameters may be made available to other modules and / or sensors by a given module and / or sensor via the network 116.

[0034] Figure 1 The system 100 may be employed in any suitable vehicle, such as an electric vehicle (e.g., a pure electric vehicle, a plug-in hybrid electric vehicle, etc.), an internal combustion engine vehicle, etc. In addition, the system 100 may be applicable to autonomous vehicles, semi-autonomous vehicles, etc. For example, Figure 2 A vehicle (eg, a host vehicle) 200 is depicted, including Figure 1 The control module 102 and the AES control module 104 and one or more sensors 250 (eg, steering sensor 108, brake sensor 110, sensor / camera of the detection module 106, etc.) in communication with the control module 102 and / or the AES control module 104.

[0035] Continue to refer Figure 1 , the steering sensor 108 can generally monitor the torque associated with a steering wheel in a vehicle. For example, the steering sensor 108 can monitor or otherwise sense the torque applied to the steering wheel by the driver when the driver steers the vehicle in a left or right direction (e.g., evasive steering). The steering sensor 108 can then transmit a signal indicating the torque to the control module 102 via the network 116. In other examples, the steering sensor 108 can monitor or otherwise sense the torque associated with a torsion bar in a vehicle.

[0036] The brake sensor 110 may generally monitor the position of a brake pedal in a vehicle. For example, the brake sensor 110 may monitor or otherwise sense a change in the brake pedal position when a driver presses a brake pedal in a vehicle. The brake sensor 110 may then transmit a signal indicating the brake pedal position, application of the brakes, etc. to the control module 102 via the network 116.

[0037] The detection module 106 may generally receive data related to components in the vehicle and / or the environment external to the vehicle. For example, the detection module 106 may collect data indicating detected objects, road conditions, weather conditions, braking, etc. for use in controlling various driver assistance systems (e.g., AES systems, etc.). In various embodiments, the detection module 106 may transmit the data indicating detected objects, road conditions, weather conditions, etc. to the AES control module 104 and / or the control module 102 via the network 116 for use in controlling vehicle steering, as further explained herein.

[0038] In various embodiments, the detection module 106 may include one or more detection devices. For example, the detection module 106 may include (one or more) sensors 112 and / or (one or more) cameras 114 mounted outside and / or inside the vehicle. In this example, (one or more) sensors 112 may include any suitable type of sensor, such as a radar sensor, a lidar sensor, an ultrasonic sensor, a 3D sensor, etc. The sensor may be a short-range sensor (e.g., a short-range radar (SRR) sensor, etc.) and / or a long-range sensor (e.g., a radar (LRR) sensor, etc.). In some examples, (one or more) cameras 114 may include a front view camera, a left view camera, and a right view camera (relative to the vehicle).

[0039] The AES control module 104 controls the vehicle to assist the driver in steering around an object, such as another vehicle on the road. In such an example, the AES control module 104 may analyze data received from the detection module 106, the steering sensor 108, the brake sensor 110, etc., and then provide a signal 118 for automatically controlling evasive steering in the vehicle, if applicable. In various embodiments, the AES control module 104 may be prevented from providing the signal 118 and thus controlling the vehicle based on actions from the control module 102, as further explained herein.

[0040] Continue to refer Figure 1 , the control module 102 initially detects whether a threat is generally present in front of a vehicle (e.g., a host vehicle). In such an example, the threat may be another vehicle traveling at a slower speed than the host vehicle, stopped in front of the moving host vehicle, etc. In various embodiments, the control module 102 detects a front threat based on received data (such as vehicle data and / or non-driver data).

[0041] For example, control module 102 may receive non-driver data indicating environmental parameters in front of the host vehicle. In such an example, the non-driver data may include data associated with other vehicles generally in front of the host vehicle. Such data may be provided by detection module 106 (e.g., sensor(s) 112 and / or camera(s) 114).

[0042] In addition, the control module 102 may receive vehicle data associated with one or more parameters of the host vehicle. In such an example, the vehicle data may indicate the intention of the driver controlling the host vehicle. For example, the host vehicle parameters may include, for example, a steering angle received from a steering sensor 108 and / or a brake signal (e.g., indicating a brake pedal position) received from a brake sensor 110. Then, based on the received vehicle data, the control module 102 determines the driver's intention. For example, if the steering angle (e.g., representative torque, etc.) indicates that the driver is pulling the steering wheel to the left aggressively, quickly, etc., the control module 102 may determine the driver's intention to evade steering to the left.

[0043] The control module 102 can then detect the presence of a forward threat based on the vehicle data and the non-driver data. For example, the control module 102 can determine a threat value associated with the forward threat based on the non-driver data. In such an example, the threat value can take into account various parameters, such as attributes associated with the threat / target (e.g., velocity, acceleration, lateral position, longitudinal position, heading, etc. of the threat / target), the type of threat / target, the driver's intent, etc., as further explained below. For example, with respect to the attributes of the threat / target, the control module 102 can determine the forward threat based on the relative longitudinal distance L between the host vehicle and the threat. Xrel The relative speed V of the threat Xrel To determine the estimated time to collision (TTC) between the host vehicle and the threat, as shown in equation (1) below. In this example, the longitudinal distance L Xrel and speed V Xrel may be calculated or otherwise determined based on data from the detection module 106

[0044] The control module 102 may also determine or classify a threat type associated with the threat when determining the threat value. For example, a forward threat may be classified as a stop or stationary object threat type (e.g., never seen moving), a sudden braking threat type (e.g., the host vehicle is following a target / threat in adaptive cruise control and the target / threat suddenly brakes), a sudden braking threat type with additional actors (e.g., similar to the sudden braking threat type, but where the other vehicle ahead performs an evasive steering maneuver), and a cut-in target threat type (e.g., the target / threat moves into an area ahead of the host vehicle). Although specific examples of threat types are described, it should be appreciated that more or fewer threat types and / or different threat types may be employed when desired. Regardless, each threat type may be associated with a value that may be used when determining a threat value.

[0045] Additionally, when the presence of a forward threat is detected, the control module 102 may determine a confidence value associated with the driver based on the driver data. In such an example, the confidence value may be a value generated based on the driver's intent (e.g., the amount of torque applied to the steering wheel, the torque rate, the amount of displacement of the brake pedal, etc.).

[0046] The determined confidence and threat values ​​can then be used to score the forward target / threat in general. For example, the following equation (2) provides an example relationship for generating a forward threat score (S). In equation (2), K ttc , K v , K tt and K dc denote the determined values ​​for the time to collision (TTC), the speed of the host vehicle, the threat type, and the driver's confidence value, respectively. In addition, in equation (2), K ttc {TTC}, K v {V Xrel}, K tt {ThreatType} and K dc {DriverConf} represents the lookup values ​​for the time to collision (TTC), the speed of the host vehicle, the threat type, and the confidence value of the driver, respectively.

[0047] The control module 102 may then detect whether the target / threat is an actual threat in front of the vehicle based on the front threat score (S) and the threshold. For example, the control module 102 may compare the front threat score (S) to a defined threshold. If the front threat score (S) is greater than or equal to the defined threshold, the control module 102 may determine that the threat is present in front of the vehicle. In various embodiments, the score (S) may fall within any suitable range, such as between 0 and 1. In such an example, the defined threshold may be any suitable value within the range, such as 0.5, 0.6, 0.7, etc.

[0048] Then, in response to detecting a threat in front of the host vehicle, the control module 102 can determine a path for the host vehicle for the AES maneuver to avoid the threat. In various embodiments, the determined path (e.g., a target path) for the AES maneuver can include a heading (left or right) of the host vehicle based on, for example, the driver's intent, the kinematics of the threat / target, etc.

[0049] In various embodiments, the control module 102 then generates a threat zone of interest lateral to the host vehicle along the determined path of the host vehicle for the AES maneuver. For example, if the determined path is to the left of the preceding threat, the control module 102 may generate a threat zone along the left side of the host vehicle (e.g., a left threat zone). Alternatively, if the determined path is to the right of the preceding threat, the control module 102 may generate a threat zone along the right side of the host vehicle (e.g., a right threat zone).

[0050] The left and / or right threat regions may be any suitable shape. For example, the threat region of interest may be generated as an irregular polygonal shape. In such an example, the irregular polygonal shape may generally be defined by a boundary corresponding to the geometry of the road in which the host vehicle continues to move. Such road geometry data may be obtained, for example, by the detection module 106, a mapping application, or the like.

[0051] For example, Figure 3 Depicted include Figure 2 FIG. 200 and a front threat vehicle 300 traveling along a road 302. Figure 3 In the example of , road 302 includes a middle lane 304 defined by lane lines 306, 308 and opposite lanes 310, 312 on the left and right sides of middle lane 304. Left lane 310 is defined by lane line 314 and lane line 306, and right lane 312 is defined by lane line 316 and lane line 308.

[0052] In this example, the host vehicle 200 includes Figure 1The control module 102 detects the vehicle 300 as a threat (as explained above). The control module 102 then determines a path for the host vehicle 200 for AES maneuvers to avoid a threat zone 318 associated with the vehicle 300. If the target path is on the left, the control module 102 creates a threat zone of interest 320 on the left side of the host vehicle 200 and the vehicle 300 (e.g., along the target path of the host vehicle 200), as explained below. However, if the target path is on the right, the control module 102 creates a threat zone of interest 330 on the right side of the host vehicle 200 and the vehicle 300 in a manner similar to the left threat zone 320.

[0053] like Figure 3 As shown in , the left threat zone 320 is generally an irregular polygonal shape defined by a boundary corresponding to the geometry of the road 302 (e.g., the left lane 310). Figure 3 In the example of FIG. 5 , the boundary of the left threat zone 320 generally includes edges 322, 324, 326, 328 having lateral vertices (relative to the host vehicle 200), such as Figure 3 . In such an example, the control module 102 may construct the lateral vertices based on various parameters associated with the road, the host vehicle 300, the threat vehicle 200, etc. For example, the lateral vertices may be constructed based on one or more of the following: the width of the road lane 310, the target trajectory of the host vehicle 200, the area associated with the threat vehicle 300 (e.g., the threat zone 318), the kinematic characteristics (e.g., position and velocity) of the threat vehicle 300, the width of the host vehicle 200, the calibratable comfort zone, etc. Then, once the lateral vertices are constructed, the control module 102 may connect (or enclose) the lateral vertices to form the boundary of the left threat zone 320.

[0054] Additionally, in some embodiments, the left and right threat zones 320, 330 may be constructed using one or more tapers, such as Figure 3 For example, left threat zone 320 is shown as including tapered portions 334, 336 at the rear portion of zone 320. Likewise, right threat zone 330 may include a similar tapered portion (if applicable). In such an example, tapered portions 334, 336 (e.g., excluding areas from zone 320) may account for the lack of a rear object camera in host vehicle 200. In some examples, Figure 1 The control module 102 may create the tapered portions 334 , 336 when constructing the threat zone 320 (or the threat zone 330 ) by offsetting the rearmost apex of the threat zone inward, thereby improving feature availability.

[0055] In various embodiments, Figure 1The control module 102 can be Figure 3 A threat zone (e.g., a critical threat zone) 318 is created around the vehicle 300 of FIG. 300. In such an example, the threat zone 318 may be constructed in a similar manner as the left and right threat zones, as further explained below. For example, the control module 102 may construct the longitudinal vertices based on parameters associated with the road (e.g., the width of the lane 304, etc.), one or more of the kinematic characteristics associated with the threatening vehicle 300, etc. Then, once the longitudinal vertices are constructed, the control module 102 may connect (or enclose) the vertices to form the boundaries of the threat zone 318. In such an example, the control module 102 may exclude the front threat zone 318 from the left threat zone 320 or the right threat zone 330, which in turn may reduce the number of false positive activations associated with detecting the target as a side threat in the zones 320, 330, as further explained below.

[0056] Continue to refer Figure 1 , the control module 102 can determine whether another threat (e.g., a lateral threat) exists in the generated threat region of interest. For example, the control module 102 can identify the generally Figure 3 One or more side threats to the side of the host vehicle 200. In various embodiments, the control module 102 can detect characteristics associated with the side threats, such as the type of threat (e.g., based on the size of the threat, a car, a semi-trailer, etc.), the speed of the threat, etc.

[0057] In various embodiments, the control module 102 may transpose the target / threat relative to the side threat zone (e.g., Figure 3 In this example, transposing the target (e.g., a vehicle to the side of the host vehicle 200) to a single point-based target can minimize noise as reported by the multiple sensors and cameras of the detection module 106 (such as discarding / skipping returns or splitting long semi-finished products into multiple targets) to avoid track skipping.

[0058] For example, Figure 4 Depicted is a host vehicle 200 and Figure 3 FIG. 1 is a diagram of a front threatening vehicle 300 traveling along a road 302. In this example, the control module 102 constructs Figure 3 The left threat area 320. Figure 4, control module 102 identifies various threats generally to the side of host vehicle 200, such as threats 430, 432, 434, 440, 450, 452, 454. In this example, threats 430, 432, 434 (triangular) may be considered fused targets (e.g., multiple targets blended together), threat 440 (oval) may be a camera detected target, and threats 450, 452, 454 (square) may be radar detected targets. In various embodiments, a confidence level (e.g., low, medium, high, etc.) may be associated with each identified threat, if desired. Although in Figure 4 200, but it will be appreciated that a similar threat zone may be constructed to the right of the host vehicle 200 in which the threat is identified, if applicable (e.g., Figure 3 Right threat area 330).

[0059] Then, Figure 1 The control module 102 may determine whether any of the identified side threats are present in the constructed threat region of interest. In various embodiments, the control module 102 may make this determination based on the projected vectors. For example, the control module 102 may generate a vector projected laterally at each identified threat.

[0060] For example, Figure 5 Depicted include Figure 3 FIG. 3 is a diagram of a left threat region 320 and various identified threats 502, 504, 506. As shown, the left threat region 320 includes boundary edges 322, 324. Figure 5 In the example of Figure 3 The control module 102 creates a test point for each identified threat 502, 504, 506 of the host vehicle 200 and the threat zone 320. In some examples, each test point may be between the host vehicle 200 and the closest boundary edge of the threat zone (e.g., boundary edge 324). The control module 102 then projects vectors 508, 510, 512 from the test point to its corresponding identified threat 502, 504, 506, respectively.

[0061] The control module 102 may determine whether the identified threats 502, 504, 506 are located in the left threat zone 320 based on the vectors 508, 510, 512. For example, the control module 102 may count the number of intersections of the vector (e.g., the test line) with the boundary edges 322, 324 of the left threat zone 320. If the number of intersections is an even number (e.g., zero intersections or two intersections), the control module 102 may infer that the associated identified threat is not within the threat zone 320. However, if the number of intersections is an odd number (e.g., 1), the control module 102 may infer that the associated identified threat is within the threat zone 320. Figure 5 , vector 508 does not intersect threat zone 320 (e.g., zero intersections) before encountering threat 502, and therefore, threat 502 does not exist in region of interest 320, as shown. Likewise, vector 512 intersects threat zone 320 at both boundary edges 322, 324 (e.g., two intersections 514, 516) before encountering threat 506, and therefore, threat 506 does not exist in region 320. However, vector 510 intersects threat zone 320 at one boundary edge 324 before encountering threat 504 (e.g., one intersection 518), and therefore, threat 504 exists in region of interest 320.

[0062] In various embodiments, even when a noisy sensing event occurs, Figure 1 The control module 102 may also track objects around the host vehicle 200. For example, the control module 102 may periodically monitor objects (e.g., Figure 4 fused target / threat 430, 432, 434). If a noisy perception event occurs (e.g., target drop, skip, return, etc.), the control module 102 may implement an object persistence algorithm to track the noisy target. In such an example, the control module 102 may persist the noisy target based on the last known kinematic information. For example, the control module 102 determines the kinematic information associated with the side target / threat (e.g., based on data obtained from the detection module 106) and tracks it based on the kinematic information. Then, if a noisy perception event occurs such that the current kinematic information becomes unavailable, the control module 102 may continue to track the target based on one or more previous values ​​of the kinematic information. In such an example, the control module 102 may continue to use the persisted kinematic information to track the target until the noisy perception event ends or the confidence level in the persisted information drops below a threshold.

[0063] For example, the following equations (3)-(5) provide relationships for perpetuating kinematic information for a target. In equations (3) and (4), the last known position in the x and y directions (I x,I y ), the last known velocity components in the x and y directions (v x 、v y ) and the last known heading angle (h) to calculate the position (I) of the target in the x and y directions (e.g., plane) xp ,I yp ). In addition, in equation (5), the last known heading angular rate or yaw (γ) and bank inclination angle can be used as The heading (h) is calculated as a function of Equation (3) xp =(l x +v x dt)cos(hdt)+(l y +v y dt)sin(hdt) Equation (4) xp =(l x +v x dt)sin(hdt)+(l y +v y dt)cos(hdt)

[0064] Continue to refer Figure 1 , the control module 102 generates one or more signals based on whether any identified threats are located within the lateral threat region of interest and transmits the one or more signals to the AES control module 104. For example, in response to determining that the identified threat is present in the threat region (e.g., Figure 4-5 320), the control module 102 may generate and transmit a control signal to the AES control module 104, thereby preventing the AES control module 104 from initiating control of the host vehicle 200 along the target path according to the particular AES maneuver. Alternatively, the control module 102 may generate and transmit a control signal to the AES control module 104, thereby allowing the AES control module 104 to initiate control of the host vehicle 200 along the target path according to the particular AES maneuver in response to determining that the identified threat does not exist in the threat zone. In still other embodiments, if the identified threat does not exist in the threat zone, the control module 102 may not generate and transmit a control signal to the AES control module 104. In such an example, the AES control module 104 may continue the AES maneuver.

[0065] For example, Figure 6 Depicted is a host vehicle 200 and Figure 4 FIG. 3 is a diagram of a front threatening vehicle 300 traveling along a road 302. In this example, Figure 1The control module 102 detects the threatening vehicle 300 and constructs a Figure 3 , determining (e.g., based on information from the AES control module 104, the detection module 106, etc.) a target path 670 for a left AES maneuver of the host vehicle 200 to avoid the threat vehicle 300, constructing Figure 4 The left threat area 320 (excluding the threat area 318), and then Figure 4 The threats 430, 434, 440, 450, 454 are identified as being within the left threat zone 320, as explained herein. Once any of the threats 430, 434, 440, 450, 454 are identified as being with respect to the left threat zone 320, the control module 102 prevents the AES control module 104 from initiating control of the host vehicle 200 according to the target path 670.

[0066] Figure 7-11 The diagram shows the Figure 1 The vehicle system 100 is used for a vehicle (e.g., Figure 2 The example control processes 700, 800, 900, 1000, 1100 of evasive steering control in a vehicle 200 of FIG. 1 are provided in conjunction with FIG. 1 . Figure 1 Although the vehicle system 100 including the control module 102 is described, any of the control processes 700 , 800 , 900 , 1000 , 1100 may be adopted by another suitable system.

[0067] exist Figure 7 , the control process 700 begins at 702, where the control module 102 detects whether a front threat (eg, vehicle 300) is present in front of a host vehicle (eg, Figure 2 The determination may be made based on vehicle data and / or non-driver data obtained, for example, from steering sensors 108, brake sensors 110, and sensors 112 and cameras 114 of detection module 106, as explained above. If no at 702, control returns to 702. However, if a front threat is detected at 702, control continues to 704, where control module 102 (or AES control module 104) determines a vehicle target path for the AES maneuver of the host vehicle. Control then continues to 706.

[0068] At 706, the control module 102 generates a threat region of interest based on the target path. For example, if the target path is on the left, the control module 102 generally generates the threat region of interest on the left side of the host vehicle. In such an example, the control module 102 may construct the threat region of interest as an irregular polygonal shape defined by a boundary corresponding to the geometry of the road, as explained above. Control then continues to 708.

[0069] At 708, the control module 102 determines whether any threats are detected in the generated threat zone of interest. For example, the control module 102 may determine various targets lateral to the host vehicle and then identify whether any of the targets are within the threat zone of interest. In such an example, the identified targets within the threat zone may be tagged as threats. If no at 708, control continues to 710, where the control module 102 allows the AES maneuver to be initiated (e.g., by the AES control module 104), as explained herein. Control may then return to 702, as shown. Otherwise, if yes at 708, control continues to 712, where the control module 102 prevents the AES maneuver from being initiated, as explained herein. Control may then return to 702.

[0070] exist Figure 8 In the control process 800, the control process 800 starts at 802 and 808. At 802, the control module 102 obtains or otherwise detects the host vehicle (e.g., Figure 2 Control then continues to 804, where the control module 102 calculates one or more properties associated with the target, such as the target's speed, acceleration, position (e.g., in the x and y directions), heating, etc. Such properties may be calculated based on data obtained from the detection module 106. Control then continues to 806, where the control module 102 calculates, rates, and classifies the threat level of the detected forward target based on one or more of the properties calculated based on, for example, the host vehicle dynamics and the target properties, as explained herein. Control then continues to 814.

[0071] At 808, the control module 102 monitors one or more driver inputs associated with the host vehicle. For example, the control module 102 may Figure 1The steering sensor 108 and / or brake sensor 110 of the control module 102 receive the driver input. Then, control continues to 810, where the control module 102 accesses the driver's intention based on the monitored input. For example, the control module 102 can determine the intention (e.g., turning to the left, etc.) based on the rotation angle of the steering wheel, the applied torque on the steering wheel, the torque rate, the application of the vehicle brakes, etc. Control then continues to 812, where the control module 102 classifies the driver's intention confidence level and direction, as explained herein. Control then continues to 814.

[0072] At 814 , the control module 102 calculates a combined score associated with the front threat level and the driver confidence level. The combined score may be calculated according to equation (2) above. Control then continues to 816 .

[0073] At 816, the control module 102 determines whether the calculated score is greater than a defined threshold. For example, the combined score may range between 0 and 1, and the defined threshold may be 0.5, 0.6, 0.7, etc. If no at 816, control returns to 802, 808. However, if the combined score is greater than the defined threshold at 816, control continues to 818.

[0074] At 818, the control module 102 determines whether any side threats (e.g., other vehicles) are on the side of the host vehicle corresponding to the driver's intention. For example, if the driver's intention is to turn to the left, the control module 102 can determine whether any objects are present on the left side of the host vehicle. In various embodiments, the control module 102 makes this determination based on data obtained from the detection module 106, as explained herein. Control continues to 820, where the control module 102 determines whether there are no threats on the side (e.g., side). If not (e.g., a threat exists), control returns to 802, 808. Otherwise, if there are no threats on the side at 820, control continues to 822, 824.

[0075] The control module 102 calculates or otherwise determines an AES target path for the host vehicle to avoid the preceding threat at 822, and then determines at 824 whether any threats (e.g., other vehicles) are located along the target path, as explained herein. Control continues to 826, where the control module 102 determines whether the target path is free of threats, as explained above. If not (e.g., a threat is present in the AES path), control returns to 802, 808. Otherwise, if at 826 the target path is free of threats, control continues to 828.

[0076] At 828, the control module 102 allows the AES manipulation to be initiated along the target path (eg, via Figure 1 The AES control module 104 of the embodiment of the present invention is used as explained herein. Control then continues to 830, where the AES control module 104 controls the host vehicle along the AES target path until the forward threat is avoided and the desired position and heading of the host vehicle is achieved. Control then returns to 802, 808.

[0077] exist Fig. 9 , the control process 900 begins at 902, where the control module 102 determines whether the host vehicle (e.g., Figure 2 If not, control returns to 902 or may end. If yes at 902, control continues to 904, 906.

[0078] At 904, the control module 102 creates a target zone and a relative position of the target zone relative to the host vehicle. For example, the control module 102 can use the target size estimate to create the target zone from the point-based targets (e.g., based on data obtained from the detection module 106). Then, at 906, the control module 102 creates and assigns a specific track to each target in the target zone (e.g., Figure 4 Each fusion target 430, 432, 434). Control then continues to 910, 922.

[0079] At 910, the control module 102 detects whether a noise-aware event has occurred. In such an example, the noise-aware event may include, for example, a target being discarded, skipped, returned, etc. In other examples, the noise-aware event may include a detected target track identifier being discarded. If no at 910, control returns to 902 as shown or to 910 if desired. If yes at 910, control continues to 912.

[0080] At 912, the control module 102 determines whether each target has returned to its fused target track. For example, the control module 102 may make this determination: whether the relationships shown in equations (6) and (7) below are both true. In this example, x ,I y represents the last known position in the x and y directions, I xp ,I yp represents the calculated position of the target as determined in equations (2) and (4) above, and d x d yIf each target has returned to its fused target track (e.g., equations (6) and (7) are true for each target), control continues to 918. However, if not each target has returned to its fused target track (e.g., neither of equations (6) and (7) is true for the target), control continues to 914. Equation (6) |l x -l xp |<d x Equation (7) |l y -l yp |<d y .

[0081] At 914, the control module 102 makes permanent the targets that have not returned to their fused target orbits based on the last known kinematic information, as explained above. For example, the control module 102 may implement equations (3)-(5) above to make permanent such targets. Control continues to 916, 922.

[0082] At 916, the control module 102 determines whether the persistent target confidence level for the target is less than a threshold or whether the targets have returned to their fused target tracks. If no, control continues to 920 where the control module continues to monitor the persistent targets. Control then returns to 912. If yes at 916, control continues to 918 where the control module stops monitoring the persistent targets. Control can then end when desired.

[0083] At 922, the control module 102 augments the fused target track(s) with the associated persistent target track(s) to maintain continuity in the target report. Control then continues to 924 where the control module 102 creates a threat region of interest as explained herein.

[0084] exist Fig.10 , the control process 1000 begins at 1002, where the control module 102 determines whether the host vehicle (e.g., Figure 2 The AES-enabled system is enabled on the vehicle 200 of the host vehicle and whether a forward threat is detected, as explained herein. If not, control returns to 1002 or can end. If yes at 1002, control continues to 1004, where the control module 102 monitors the target path of the host vehicle and estimates an alternative path (e.g., an AES path) to avoid the forward threat. Control then continues to 1006.

[0085] At 1006, the control module 102 begins to create a front threat region of interest. Specifically, at 1006, the control module 102 creates longitudinal vertices of the front threat region of interest based on, for example, the kinematic characteristics of the front threat (e.g., as a function of the position, velocity, etc. of the front threat). The control module 102 may then connect (e.g., enclose) the longitudinal vertices with boundaries to create the front threat region of interest. Control then continues to 1008.

[0086] At 1008, the control module 102 determines whether the AES path is on the left side. If yes, control continues to 1010, where the control module assigns the lateral vertices to the left side of the host vehicle, and then connects (e.g., surrounds) the lateral vertices to form the boundary of the left threat zone of interest (which excludes the front threat zone), as explained herein. Control then continues to 1014,. If no at 1008 (e.g., the AES path is on the right side), control continues to 1012, where the control module assigns the lateral vertices to the right side of the host vehicle, and then connects (e.g., surrounds) the lateral vertices to form the boundary of the right threat zone of interest (which excludes the front threat zone), as explained herein. Control then continues to 1014.

[0087] At 1014, the control module 102 determines whether the AES path is clear. For example, the control module 102 can determine whether any identified targets / threats exist in the left threat zone of interest or the right threat zone of interest (depending on which threat zone is constructed at 1010, 1012). If yes at 1014, control continues to 1016, where the control module 102 allows the AES manipulation to be initiated (e.g., by the AES control module 104), as explained herein. Control can then end as shown or return to 1002. Otherwise, if no at 1014, control continues to 1018, where the control module 102 prevents the AES manipulation from being initiated, as explained herein. Control can then end as shown or return to 1002.

[0088] exist Fig.11 , the control process 1100 begins at 1102, where the control module 102 determines whether the host vehicle (e.g., Figure 2 The AES-enabled system is enabled on the vehicle 200 of the vehicle, whether a front threat is detected, and whether the side for AES manipulation is determined, as explained herein. If not, control returns to 1102 or can end. If yes at 1102, control continues to 1104, 1106, 1108, 1110.

[0089] At 1104, the control module 102 generates a threat zone of interest on the side for the AES maneuver, as explained above. Then, at 1106, the control module 102 may apply one or more tapers at the rear of the threat zone of interest to suppress false detections, as explained above. At 1108, the control module 102 identifies a target on the side of the host vehicle where the AES maneuver is planned, as explained herein. The control module 102 then selects one of the identified targets at 1110. Control then continues to 1112.

[0090] At 1112, the control module 102 projects a vector from (or to) the selected target to (or from) the lateral test point, as explained above. Control then continues to 1114, where the control module 102 determines how many times the vector intersects the boundary of the threat zone of interest. Control then continues to 1116.

[0091] At 1116, the control module 102 determines whether the number of vector intersections is an odd number (e.g., 1). If so, the target is considered a threat within the threat region of interest at 1118. Control then continues to 1122. However, if the number of vector intersections is not an odd number (e.g., an even number such as 0 or 2), the target is considered outside the threat region of interest at 1120. Control then continues to 1122.

[0092] At 1122, the control module 102 determines whether any of the targets identified at 1108 still exist. If yes, the control module 102 selects the next identified target at 1124. Control then returns to 1112. If no at 1122, control continues to 1126, where the control module 102 determines whether any of the identified targets are considered threats within the threat zone of interest. If no at 1126, control continues to 1128, where the control module 102 allows the AES manipulation to be initiated (e.g., by the AES control module 104), as explained herein. Control may then end. Otherwise, if yes at 1126, control continues to 1130, where the control module 102 prevents the AES manipulation from being initiated, as explained herein. Control may then end.

[0093] The above description is essentially only illustrative, and is in no way 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 when studying the drawings, the specification and the appended claims. It should be understood that one or more steps in the method can be performed in different orders (or simultaneously) without changing the principles of the present disclosure. Further, although each of the embodiments 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 of the other embodiments and / or combined with the features of any of the other embodiments, 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 to each other remains within the scope of the present disclosure.

[0094] Various terms are used to describe the spatial and functional relationships between elements (e.g., between modules, circuit elements, semiconductor layers, etc.), including "connected," "engaged," "coupled," "adjacent," "immediately adjacent," "on top of," "above," "below," and "disposed." Unless explicitly described as "directly," when describing the 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 exist (spatially or functionally) between the first and second elements. As used herein, the phrase "at least one of A, B, and C" should be understood to mean a logical (A or B or C) using a non-exclusive logical "or," and should not be understood to mean "at least one of A, at least one of B, and at least one of C."

[0095] In the drawings, as indicated by the arrows, the direction of the arrows generally demonstrates the flow of information (such as data or instructions) of interest to the illustration. For example, when element A and element B exchange a variety of information but the information transmitted from element A to element B is relevant to the illustration, the arrow may point from element A to element B. The unidirectional arrow does not imply that other information is not transmitted from element B to element A. Further, for information sent from element A to element B, element B may send a request for the information or a positive acknowledgement of receipt of the information to element A.

[0096] In this application, including the definitions below, the term "circuit" may be used instead of the term "module" or the term "controller". 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 group) that executes code; a memory circuit (shared, dedicated, or group) 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.

[0097] 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 perform a certain functionality on behalf of a client module.

[0098] As used above, the term "code" 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" encompasses a single processor circuit that executes some or all of the code from multiple modules. The term "group processor circuit" encompasses a processor circuit that executes some or all of the code from one or more modules in conjunction with additional processor circuits. References to multiple processor circuits encompass 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" encompasses a single memory circuit that stores some or all of the code from multiple modules. The term "group memory circuit" encompasses a memory circuit that stores some or all of the code from one or more modules in conjunction with additional memory.

[0099] The term "memory circuit" is a subset of the term "computer-readable medium". As used herein, the term "computer-readable medium" does not cover transient electrical or electromagnetic signals propagated through a medium (such as, on a carrier wave); the term "computer-readable medium" may thus be considered tangible and non-transient. Non-limiting examples of non-transient 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 drive), and optical storage media (such as, CD, DVD, or Blu-ray disc).

[0100] The apparatus and method described in this application can be implemented partially or completely 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 translated into computer programs by routine work of a skilled technician or programmer.

[0101] 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.

[0102] 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) object 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 5th Revision), Ada, ASP (Active Server Pages), PHP (PHP: Hypertext Preprocessor), Scala, Eiffel, Smalltalk, Erlang, Ruby, Visual Lua, MATLAB, SIMULINK, and

Claims

1. A vehicle system for evasive steering control in a vehicle, the vehicle system comprising: an avoidance evasive steering (AES) module configured to automatically control the vehicle; as well as A control module is in communication with the AES module, and the control module is configured to: detecting whether a first threat exists in front of the vehicle; In response to detecting a first threat in front of the vehicle, determining a path for the vehicle for AES maneuvers to avoid the first threat in front of the vehicle; generating a threat region of interest lateral to the vehicle along a path of the vehicle for the AES maneuver; determining whether a second threat exists in the threat region of interest; as well as In response to determining that the second threat is present in the threat zone of interest, the AES module is prevented from initiating control of the vehicle in accordance with the AES maneuver. 2 . The vehicle system of claim 1 , wherein the threat region of interest is an irregular polygonal shape defined by boundaries corresponding to the geometry of a road in which the vehicle continues to move.

3. The vehicle system of claim 2, wherein the control module is configured to construct vertices of the boundary based on one or more of a width of a road lane, a trajectory of the vehicle, an area associated with a first threat in front of the vehicle, and a width associated with the vehicle.

4. The vehicle system of claim 2, wherein the control module is configured to: identifying a second threat to the side of the vehicle while the vehicle is moving based on data received from one or more sensors; and The vector is projected to determine whether the second threat exists in the threat region of interest. 5 . The vehicle system of claim 1 , wherein the control module is configured to: determine kinematic information associated with the second threat; and track the second threat based on the kinematic information. 6 . The vehicle system of claim 5 , wherein the control module is configured to track the second threat based on one or more previous values ​​of the kinematic information.

7. The vehicle system of claim 1, wherein the control module is configured to: receiving vehicle data associated with one or more parameters of the vehicle while the vehicle is moving, the vehicle data indicating an intent of a driver controlling the vehicle; receiving non-driver data indicative of an environmental parameter in front of the vehicle while the vehicle is moving; as well as Whether the first threat is present in front of the vehicle is detected based on the vehicle data and the non-driver data.

8. The vehicle system of claim 7, wherein the control module is configured to: determining a confidence value for the driver based on the vehicle data; determining a threat value based on the non-driver data; calculating a score based on the confidence value and the threat value; as well as Whether the first threat is present in front of the vehicle is detected based on the score and a threshold.

9. A vehicle comprising the vehicle system of claim 1 configured to control an evasive turn of the vehicle.

10. A method for controlling evasive steering in a vehicle, the method comprising: detecting whether a first threat exists in front of the vehicle; In response to detecting a first threat in front of the vehicle, determining a path of the vehicle for an avoidance evasive steering (AES) maneuver to avoid the first threat in front of the vehicle; generating a threat region of interest lateral to the vehicle along a path of the vehicle for the AES maneuver; determining whether a second threat exists in the threat region of interest; as well as In response to determining that the second threat is present in the threat zone of interest, an AES module is prevented from initiating control of the vehicle in accordance with the AES maneuver.

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