Collision indication based on yaw rate and lateral speed thresholds

Abstract

The technologies and systems of this disclosure implement a collision indication based on yaw rate and lateral velocity thresholds. Specifically, a path inner band is determined for a predicted path of a host vehicle. In response to determining that a target is within the path inner band, the lateral movement of the host vehicle at a certain moment is estimated based on whether the yaw rate of the host vehicle meets the yaw rate threshold. The lateral movement of the target at that moment is also determined based on whether the lateral velocity of the target meets the lateral velocity threshold. A collision indication is generated in response to determining that the host vehicle and the target may be within the path inner band at that moment based on the lateral movement. In this way, the collision indication more accurately reflects an impending collision, thereby improving safety while also reducing false positive events.

Description

Background Art

[0001] Determining whether a collision with a target object is imminent is important for many vehicle operations (e.g., Advanced Driver Assistance Systems (ADAS), Automatic Emergency Braking (AEB), Enhanced Steering Assistance (ESA), semi-autonomous driving technologies, autonomous driving technologies). For example, when it is determined that a collision is imminent, the AEB system can apply braking force, or the ESA system can provide steering input to avoid the collision. Accurately determining an imminent collision not only mitigates actual threats (e.g., those that may cause a collision), but also minimizes false positives (e.g., those that do not cause a collision). In some cases, traditional techniques are unable to accurately determine an imminent collision. As a result, downstream operations (e.g., ADAS, AEB, ESA) are negatively affected, which may lead to reduced safety and / or user experience. Summary of the Invention

[0002] This document relates to systems, components, techniques, and methods for implementing collision indication based on yaw rate and lateral speed thresholds. The techniques and methods described herein may be performed by systems and / or components. The systems and components include means (e.g., a processing system) for performing the techniques and methods described herein.

[0003] Some aspects described below include a method that includes: determining a predicted path of a host vehicle and an in-path band of the predicted path. The method further includes: determining whether a target is within the in-path band; and in response to determining that the target is within the in-path band: determining a host lateral movement based on whether the yaw rate of the host vehicle meets a yaw rate threshold; and based on the host lateral movement and the in-path band, determining whether the host vehicle is likely to be within the in-path band at a certain future time. The method further includes: determining a target lateral movement based on whether the lateral speed of the target meets a lateral speed threshold; and based on the target lateral movement and the in-path band, determining whether the target is likely to be within the in-path band at a future time. The method also includes: in response to determining that the host vehicle and the target are likely to be within the in-path band at a future time, generating a collision indication that causes the host vehicle to perform an action. Other aspects described below include a system for performing the above method and a computer-readable storage medium including instructions that, when executed by at least one processor, cause the processor to perform the above method.

[0004] This Summary of the Invention introduces a simplified concept for implementing collision indication based on yaw rate and lateral speed thresholds, which is further described in the Detailed Description and the Drawings. This Summary of the Invention is not intended to identify essential features of the claimed subject matter, nor is it intended to be used to determine the scope of the claimed subject matter. Brief Description of the Drawings

[0005] Systems and techniques for implementing collision indication based on yaw rate and lateral velocity thresholds are described with reference to the following figures, in which some of the same reference numerals are used throughout to refer to examples of similar or like features and components.

[0006] Figure 1 An example environment is shown in which collision indication based on yaw rate and lateral velocity thresholds can be used in accordance with the techniques of the present disclosure.

[0007] Figure 2 An example is shown in accordance with the techniques of the present disclosure Figure 1 of other aspects of an example environment.

[0008] Figure 3 An example system of a host vehicle is shown in accordance with the techniques of the present disclosure, the system being configured to implement collision indication based on yaw rate and lateral velocity thresholds.

[0009] Figure 4 An example data flow for collision indication based on yaw rate and lateral velocity thresholds is shown in accordance with the techniques of the present disclosure.

[0010] Figure 5 An example method for collision indication based on yaw rate and lateral velocity thresholds is shown in accordance with the techniques of the present disclosure. DETAILED DESCRIPTION

[0011] OVERVIEW

[0012] Accurately determining an impending collision with a target is an important tool in many vehicle operations. A variety of situations often result in inaccurate traditional collision determination. For example, some techniques rely only on the yaw rate of the host vehicle or inputs from multiple sensors to determine an impending collision with a target. Such techniques are often unreliable (e.g., they may produce too many false positive collision determinations), or are too slow in determining an impending collision to leave sufficient time for an appropriate reaction for downstream operations.

[0013] The techniques and systems of this disclosure implement a collision indication using an in-path band that combines lateral movement estimation based on yaw rate and lateral velocity thresholds. Specifically, an in-path band is determined for a predicted path of a vehicle. In response to determining that a target is within the in-path band, the lateral movement of the host vehicle at a certain moment is estimated based on whether the yaw rate of the host vehicle meets the yaw rate threshold. The lateral movement of the target at that moment is also estimated based on whether the lateral velocity of the target meets the lateral velocity threshold. In response to determining that the host vehicle and the target may be within the in-path band at that moment based on the lateral movement, a collision indication is generated. By determining the lateral movement based on whether the thresholds are met, the collision indication more accurately reflects an impending collision, thereby improving safety and reducing false positive events. In this way, the safety and user experience of downstream operations (e.g., ADAS, AEB, ESA) are improved.

[0014] Example Environment

[0015] Figure 1 An example environment 100 is shown in which a collision indication based on yaw rate and lateral velocity thresholds can be used. The example environment 100 includes a host vehicle 102 and a target 104. The host vehicle 102 can be any type of system (e.g., car, sedan, truck, motorcycle, electric bicycle, boat, aerial vehicle). The target 104 can be any type of moving or stationary object (e.g., car, sedan, truck, motorcycle, electric bicycle, boat, pedestrian, cyclist, boulder). The host vehicle 102 can use one or more sensor systems (e.g., radar sensor, vision sensor, lidar sensor) to detect the target 104.

[0016] The host vehicle 102 is traveling along a path 106 (e.g., a predicted path) at a host speed 108 and a host yaw rate 110. As shown, the path 106 curves with a radius 112. The host yaw rate 110 and the host speed 108 can be used to predict or otherwise determine the path 106 and / or the radius 112. It should be noted that the path 106 can be straight or any other shape without departing from the scope of the present disclosure.

[0017] The collision module 114 of the host vehicle 102 (which is at least partially implemented in hardware) includes a path module 116 that determines an in-path band 118. The in-path band 118 is a lateral band that is centered on the path 106 and decreases in width along the path 106 away from the host vehicle 102. The amount by which the in-path band 118 decreases in width can depend on the situation and can be based on the host speed 108, the host yaw rate 110, and / or the distance 120 from the host vehicle 102.

[0018] The path module 116 (or more generally, the collision module 114) can determine that the target 104 is within the path band 118, which enables the collision module 114 to determine whether the host vehicle 102 and the target 104 may be within the path band 118 at a future time, as discussed further below.

[0019] Figure 2 A further aspect of the example environment 100 is shown. The target 104 has a target lateral velocity 202. The target lateral velocity 202 can be the lateral component of the total velocity (not shown) of the target 104. The collision module 114 also includes a lateral movement module 204 that is configured to determine a host lateral movement 206 and a target lateral movement 208 in response to determining that the target 104 is within the path band 118. The host lateral movement 206 represents how far the host vehicle 102 may have traveled laterally over a period of time. This time can be based on the time to collision (TTC) with the target 104. The target lateral movement 208 represents how far the target 104 may have traveled laterally over that period of time.

[0020] The collision module 114 is configured to determine whether the host vehicle 102 and the target 104 may be within the path band 122 after that period of time. If they may be within the path band 122, a collision with the target 104 can be determined to be imminent (subject to optional other factors, as discussed below).

[0021] Example system

[0022] Figure 3 An example system 300 is shown that is configured to be disposed within the host vehicle 102 and is configured to implement a collision indication based on a yaw rate and a lateral velocity threshold. The components (and sub-components) of the example system 300 can be arranged anywhere within or on the host vehicle 102. The example system 300 can include at least one processor 302, a computer-readable storage medium 304 (e.g., a medium, media, multiple media), and vehicle components 310. These components are operatively and / or communicatively coupled via a link 306.

[0023] The processor 302 (e.g., an application processor, a microprocessor, a digital signal processor (DSP), a controller) is coupled to the computer-readable storage medium 304 via a link 306 and executes instructions (e.g., code) stored in the computer-readable storage medium 304 (e.g., a non-transitory storage device such as a hard disk drive, an SSD, flash memory, read-only memory (ROM)) to implement or otherwise cause the collision module 114 (or a portion thereof) to perform the techniques described herein. Although shown within the computer-readable storage medium 304, the collision module 114 (or a portion thereof) can be a stand-alone component (e.g., having a dedicated computer-readable storage medium including instructions and / or executing on dedicated hardware such as a dedicated processor, a pre-programmed field-programmable gate array (FPGA), a system-on-chip (SOC), etc.). The processor 302 and the computer-readable storage medium 304 can be any number of components, including multiple components distributed throughout the host vehicle 102, remote from the host vehicle 102, dedicated, or shared with other components, modules, or systems of the host vehicle 102 and / or configured in a different manner than shown without departing from the scope of the present disclosure.

[0024] The computer-readable storage medium 304 also contains sensor data 308 generated by one or more sensors (not shown), which can be local to or remote from the example system 300. The sensor data 308 indicates or otherwise enables the determination of information available for performing the techniques described herein. For example, the sensor data 308 can be used to indicate or otherwise determine the path 106, the host speed 108, the host yaw rate 110, the radius 112, the distance 120, or the target lateral velocity 202.

[0025] In some implementations, the sensor data 308 can be from a remote source (e.g., via the link 306). The example system 300 can include a communication system (not shown) that receives sensor data from the target 104 or another remote source. For example, vehicle-to-vehicle or vehicle-to-everything (V2V / V2X) connections can be used to obtain information available for performing the techniques described herein.

[0026] The vehicle component 310 includes one or more systems or components that are communicatively coupled to the collision module 114 and are configured to perform functions using the output from the collision module 114 (e.g., a collision indication). The vehicle component 310 can affect the corresponding dynamics of the host vehicle 102 (e.g., speed, acceleration, heading, vehicle configuration, vehicle operation or function). For example, the vehicle component 310 can include an AEB system that applies braking force or an ESA system that applies steering force to mitigate an impending collision. The vehicle component 310 is communicatively coupled to the collision module 114 via the link 306. Although shown as a separate component, the vehicle component 310 can be part of the collision module 114 and vice versa.

[0027] By using the example system 300, the host vehicle 102 can more accurately determine an impending collision (e.g., more true positives and fewer false positives), enabling better utilization of downstream operations (e.g., the vehicle component 310). In so doing, the host vehicle 102 can provide better safety and / or experience for the occupants of the host vehicle 102, the target 104, and / or other vehicles or pedestrians.

[0028] Example data flow

[0029] Figure 4 An example data flow 400 of a collision indication based on yaw rate and lateral speed thresholds is shown. The example data flow 400 can be implemented in any of the previously described environments and by any of the previously described systems or components. For example, the example data flow 400 can be implemented in the example environment 100 and / or by the example system 300. The example data flow 400 can also be implemented in other environments by other systems or components and using other data flows or techniques. The example data flow 400 can be implemented by one or more entities (e.g., the collision module 114). The order of showing and / or describing operations is not intended to be construed as a limitation, and the order can be rearranged without departing from the scope of the present disclosure. Additionally, any number of operations can be combined with any other number of operations to implement the example data flow or an alternative data flow.

[0030] The example data flow 400 begins with the attributes 402 of the environment (e.g., the example environment 100) obtained by the collision module 114. As shown, the attributes 402 include the host speed 108, the host yaw rate 110, road information 404 (e.g., map data, radar positioning data, surrounding objects), the target location 406 (e.g., relative to the host vehicle 102), and the target lateral speed 202.

[0031] Attribute 402 can be obtained, received, or determined by the collision module 114 in any manner known to those of ordinary skill in the art. For example, the collision module 114 can determine the attribute 402 directly from the sensor data 308, from a bus or interface connected to a sensor that docks with the example system 300, or from another module or system of the example system 300. Regardless of how or where the attribute 402 is collected, received, derived, or calculated, the collision module 114 is configured to use the attribute 402 to determine the collision indication 408.

[0032] As a further example of the data flow 400, the attribute 402 is input into the path module 116. The path module 116 is configured to determine the path 106 and the in-path band 118. The path 106 can be based on the primary speed 108 and the primary yaw rate 110 and includes a radius 112. As discussed above, the in-path band 118 can decrease in width along the path 106 away from the primary vehicle 102. The amount of decrease can be based on the primary speed 108, the primary yaw rate 110, and the distance 120 (determined from the target location 406).

[0033] The attribute 402 is also input into the lateral movement module 204. The lateral movement module 204 is configured to determine the primary lateral movement 206 and the target lateral movement 208. To do so, the lateral movement module 204 calculates a yaw rate threshold 410 for the primary vehicle 102. The yaw rate threshold 410 can be based on the primary speed 108, driver input (e.g., the primary yaw rate 110), and / or the road information 404. The yaw rate threshold 410 represents the minimum yaw rate for estimating the primary lateral movement 206. For example, the primary lateral movement 206 can be determined according to Equation 1.

[0034]

[0035] where ω is the primary yaw rate 110, ω min is the yaw rate threshold 410, R is the radius 112, and Δt is the time (e.g., the TTC with the target 104).

[0036] The lateral movement module 204 also calculates a lateral speed threshold 412 for the target 104. The lateral speed threshold 412 can be based on the speed of the target (e.g., the target lateral speed 202), the distance 120, and / or the road information 404. The lateral speed threshold 412 represents the minimum target lateral speed 202 for estimating the target lateral movement 208. For example, the target lateral movement 208 can be determined according to Equation 2.

[0037]

[0038] where v lat is the target lateral speed 202, v lat_minis the lateral velocity threshold 412.

[0039] The primary lateral movement 206, the target lateral movement 208, and the in-path band 118 are received by the collision determination module 414. The collision determination module 414 is configured to determine whether the primary vehicle 102 and / or the target 104 may be within the in-path band 118 at that moment. To do so, the collision determination module 414 may determine whether the lateral movements (e.g., the primary lateral movement 206 and the target lateral movement 208) are still within the in-path band 118. If so, a collision determination 416 may be made.

[0040] The collision determination 416 may be received by the hysteresis module 418, which is configured to determine whether the collision determination 416 should become a collision indication 408. To do so, the hysteresis module 418 may determine whether there has been any previous collision determination 420 for the target 104. In other words, the hysteresis module 418 may generate the collision indication 408 only in response to determining that the target 104 has become a threat (e.g., has had a collision determination 416) for a certain amount of time. Doing so mitigates false positives that may be generated based on transient spikes in the attribute 402 (e.g., due to transient conditions or measurement noise or interference from sensors).

[0041] As an alternative to, or in combination with, the previous collision determination 420, the hysteresis module 418 may check whether any bypass conditions 422 are met. The bypass conditions 422 may include determining that the target is outside of the road on which the primary vehicle 102 is traveling (e.g., based on the target location 406 and the road information 404). In other words, the hysteresis module 418 may ensure that the target 104 is within the road before generating the collision indication 408.

[0042] The bypass conditions 422 may also include determining that the primary vehicle 102 is traveling in a straight line while the target 104 is turning. Conversely, the bypass conditions 422 may also include determining that the primary vehicle 102 is turning while the target 104 is moving in a straight line. In other words, before generating the collision indication 408, the hysteresis module 418 may ensure that the primary vehicle 102 is not traveling in a straight line while the target is turning, or that the primary vehicle 102 is not turning while the target 104 is moving in a straight line.

[0043] Although shown within the collision module 114, the path module 116, the lateral movement module 204, the collision determination module 414, and / or the hysteresis module 418 may be separate from the collision module 114. For example, the path module 116, the lateral movement module 204, the collision determination module 414, or the hysteresis module 418 may be stand-alone components and / or may be implemented via dedicated hardware.

[0044] Then, a collision indication 408 is output for receipt by a vehicle component 310. The vehicle component 310 uses the collision indication 408 to alter the functionality of the host vehicle 102. For example, the vehicle component 310 can cause an alert (visual, audible, and / or tactile), change the steering angle of the host vehicle 102, apply a braking force to the host vehicle 102, or alter the operation of a semi-autonomous or autonomous function of the host vehicle. It should be noted that the vehicle component 310 can represent multiple functions or systems that receive the collision indication 408.

[0045] By using the techniques described above, the collision indication 408 can be based on a decreasing width of the in-path band, a yaw rate, and a lateral velocity threshold, which determine how a lateral movement, a hysteresis condition, and / or a bypass scenario is not met. In this way, the collision indication 408 is more accurate in more environments and situations. As a result, more true positives are generated, and more false positives are avoided, thereby improving the safety of the passengers of the host vehicle 102, the target 104, and / or others in the vicinity of the host vehicle 102.

[0046] Example Method

[0047] Figure 5 An example method 500 for a collision indication based on a yaw rate and a lateral velocity threshold is shown. The example method 500 can be implemented in any of the previously described environments, by any of the previously described systems or components, and using any of the previously described data streams, process flows, or techniques. For example, the example method 500 can be implemented in the example environment 100, by the example system 300, and / or by following the example data stream 400. The example method 500 can also be implemented in other environments, by other systems or components, and using other data streams, process flows, or techniques. The example method 500 can be implemented by one or more entities (e.g., the collision module 114). The order of the operations shown and / or described is not intended to be construed as a limitation, and the order can be rearranged without departing from the scope of the present disclosure. Additionally, any number of operations can be combined with any other number of operations to implement an example process flow or an alternative process flow.

[0048] At 502, an in-path band of the host vehicle is determined. For example, the path module 116 can determine the in-path band 118 of the host vehicle 102 based on the path 106, the host speed 108, the host yaw rate 110, and / or the distance 120.

[0049] At 504, in response to determining that the target is within the in-path band, determine the lateral movement of the host vehicle at a certain moment based on whether the yaw rate of the host vehicle meets a yaw rate threshold. For example, the path module 116 may determine that the target 104 is within the in-path band 118, and the lateral movement module 204 may determine the yaw rate threshold 410 and use it to determine the host lateral movement 206 at that moment (the TTC with the target 104).

[0050] At 506, determine the lateral movement of the target at that moment based on whether the lateral speed of the target meets a lateral speed threshold. For example, the lateral movement module 204 may determine the lateral speed threshold 412 and use it to determine the target lateral movement 208 at that moment.

[0051] At 508, generate a collision indication in response to determining that the host vehicle and the target may be within the in-path band at that moment. For example, the collision determination module 414 may generate a collision determination 416 and pass it to the hysteresis module 418 to generate a collision indication 408.

[0052] At 510, output the collision indication for receipt by the vehicle components. For example, the hysteresis module 418 may output the collision indication 408 for receipt by the vehicle components 310 to change the function of the host vehicle 102.

[0053] By influencing the collision indication based on the example method 800, a more accurate collision indication can be generated. In doing so, the efficiency of downstream operations (e.g., the vehicle components 310) is improved while ensuring that these operations are not activated unnecessarily (e.g., false positive steering / braking events). Thus, the safety and experience of the people (and other objects) in and around the host vehicle 102 can be improved.

[0054] Example

[0055] Example 1: A method, the method comprising: determining a predicted path of a main vehicle; determining a path inner band of the predicted path, the path inner band centered on the predicted path and decreasing in width along a direction away from the predicted path of the main vehicle; determining whether a target is within the path inner band; and in response to determining that the target is within the path inner band: determining a yaw rate of the main vehicle; determining a yaw rate threshold of the main vehicle, the yaw rate threshold being usable to determine how to determine a main lateral movement of the main vehicle; determining the main lateral movement based on whether the yaw rate of the main vehicle meets the yaw rate threshold; determining whether the main vehicle may be within the path inner band at a certain future moment based on the main lateral movement and the path inner band; determining a lateral speed of the target; determining a lateral speed threshold of the target, the lateral speed threshold being usable to determine how to determine a target lateral movement of the target; determining the target lateral movement based on whether the lateral speed of the target meets the lateral speed threshold; determining whether the target may be within the path inner band at a future moment based on the target lateral movement and the path inner band; and in response to determining that the main vehicle and the target may be within the path inner band at a future moment, generating a collision indication; and in response to generating the collision indication, causing the main vehicle to perform an action.

[0056] Example 2: The method of Example 1, wherein the predicted path is based on a yaw rate of the main vehicle and a speed of the main vehicle.

[0057] Example 3: The method of Example 1 or 2, wherein a decreasing amount of the width of the path inner band is based on at least one of the following: a speed of the main vehicle, a yaw rate, or a distance between the main vehicle and the target.

[0058] Example 4: The method of Example 1, 2, or 3, wherein the yaw rate threshold is based on at least one of the following: a speed of the main vehicle, a yaw rate, or road information.

[0059] Example 5: The method of any of the foregoing examples, wherein determining the main lateral movement comprises: in response to determining that the yaw rate does not meet the yaw rate threshold, determining the main lateral movement to be zero; or in response to determining that the yaw rate meets the yaw rate threshold, determining the main lateral movement based on a radius of curvature of the predicted path, the yaw rate, and a future moment.

[0060] Example 6: The method of any of the foregoing examples, wherein the future moment includes an estimated collision time between the main vehicle and the target.

[0061] Example 7: The method of any of the foregoing examples, wherein the lateral speed threshold is based on at least one of the following: a speed of the target, a distance between the main vehicle and the target, or road information.

[0062] Example 8: The method of any of the preceding examples, wherein determining the target lateral movement includes: in response to determining that the lateral speed does not meet the lateral speed threshold, determining the target lateral movement to be zero; or in response to determining that the lateral speed meets the lateral speed threshold, determining the target lateral movement based on the radius of curvature of the predicted path, the yaw rate, and a future time.

[0063] Example 9: The method of any of the preceding examples, wherein generating a collision indication is further in response to at least one of the following: identifying a previous determination that the host vehicle and the target may be within the in-path band at a future time; determining that the target is within the road on which the host vehicle is traveling; determining that when the target is turning, the host vehicle is not traveling in a straight line; or determining that when the target is traveling in a straight line, the host vehicle is not changing lanes or turning.

[0064] Example 10: A system comprising at least one processor configured to: determine a predicted path of a host vehicle; determine an in-path band of the predicted path, the in-path band centered on the predicted path and decreasing in width along a direction away from the predicted path of the host vehicle; determine whether a target is within the in-path band; and in response to determining that the target is within the in-path band: determine a yaw rate of the host vehicle; determine a yaw rate threshold of the host vehicle, the yaw rate threshold being capable of being used to determine how to determine a primary lateral movement of the host vehicle; determine the primary lateral movement based on whether the yaw rate of the host vehicle meets the yaw rate threshold; determine whether the host vehicle may be within the in-path band at a certain future time based on the primary lateral movement and the in-path band; determine a lateral speed of the target; determine a lateral speed threshold of the target, the lateral speed threshold being capable of being used to determine how to determine a target lateral movement of the target; determine the target lateral movement based on whether the lateral speed of the target meets the lateral speed threshold; determine whether the target may be within the in-path band at a future time based on the target lateral movement and the in-path band; and generate a collision indication in response to determining that the host vehicle and the target may be within the in-path band at a future time.

[0065] Example 11: The system of Example 10, wherein the predicted path is based on a yaw rate of the host vehicle and a speed of the host vehicle.

[0066] Example 12: The system of Example 10 or 11, wherein the amount of decrease in the width of the in-path band is based on at least one of the following: a speed of the host vehicle, a yaw rate, or a distance between the host vehicle and the target.

[0067] Example 13: The system of Example 10, 11, or 12, wherein the yaw rate threshold is based on at least one of the following: a speed of the host vehicle, a yaw rate, or road information.

[0068] Example 14: The system of any one of Examples 10 to 13, wherein determining the primary lateral movement includes: determining that the primary lateral movement is zero in response to determining that the yaw rate does not meet the yaw rate threshold; or determining the primary lateral movement based on the radius of curvature of the predicted path, the yaw rate, and a future time in response to determining that the yaw rate meets the yaw rate threshold.

[0069] Example 15: The system of any one of Examples 10 to 14, wherein the future time includes an estimated time to collision between the host vehicle and the target.

[0070] Example 16: The system of any one of Examples 10 to 15, wherein the lateral velocity threshold is based on at least one of the following: the velocity of the target, the distance between the host vehicle and the target, or road information.

[0071] Example 17: The system of any one of Examples 10 to 16, wherein determining the target lateral movement includes: determining that the target lateral movement is zero in response to determining that the lateral velocity does not meet the lateral velocity threshold; or determining the target lateral movement based on the radius of curvature of the predicted path, the yaw rate, and a future time in response to determining that the lateral velocity meets the lateral velocity threshold.

[0072] Example 18: The system of any one of Examples 10 to 17, wherein a collision indication is generated in response to a previously determined identification that the host vehicle and the target may be within the path footprint at a future time.

[0073] Example 19: The system of any one of Examples 10 to 18, wherein a collision indication is further generated in response to at least one of the following: determining that the target is within the road on which the host vehicle is traveling; determining that the host vehicle is not traveling in a straight line while the target is turning; or determining that the host vehicle is not changing lanes or turning while the target is traveling in a straight line.

[0074] Example 20: A computer-readable storage medium, the computer-readable storage medium comprising instructions that, when executed by at least one processor, cause the processor to: determine a predicted path of a main vehicle; determine a path inner band of the predicted path, the path inner band being centered on the predicted path and decreasing in width along a direction away from the predicted path of the main vehicle; determine whether a target is within the path inner band; and in response to determining that the target is within the path inner band: determine a yaw rate of the main vehicle; determine a yaw rate threshold of the main vehicle, the yaw rate threshold being capable of being used to determine how to determine a main lateral movement of the main vehicle; determine the main lateral movement based on whether the yaw rate of the main vehicle meets the yaw rate threshold; determine whether the main vehicle may be within the path inner band at a certain future moment based on the main lateral movement and the path inner band; determine a lateral speed of the target; determine a lateral speed threshold of the target, the lateral speed threshold being capable of being used to determine how to determine a target lateral movement of the target; determine the target lateral movement based on whether the lateral speed of the target meets the lateral speed threshold; determine whether the target may be within the path inner band at a future moment based on the target lateral movement and the path inner band; and in response to determining that the main vehicle and the target may be within the path inner band at a future moment, generate a collision indication.

[0075] Example 21: A system, the system comprising: a processor configured to execute the method of any one of Examples 1 to 9.

[0076] Example 22: A computer-readable storage medium, the computer-readable storage medium comprising instructions that, when executed by at least one processor, cause the processor or an associated system to execute the method of any one of Examples 1 to 9.

[0077] Example 23: A system comprising means for executing the method of any one of Examples 1 - 9.

[0078] Example 24: A method executed by the system of any one of Examples 10 to 19.

[0079] Conclusion

[0080] Although various embodiments of the present disclosure have been described in the foregoing description and illustrated in the accompanying drawings, it should be understood that the present disclosure is not limited thereto, but may be implemented in various ways within the scope of the following claims for practice. From the foregoing description, it will be apparent that various changes may be made without departing from the spirit and scope of the present disclosure as defined by the following claims.

[0081] Unless the context clearly dictates otherwise, the use of "or" and grammatically related terms means unrestricted non-exclusive alternatives. As used herein, the phrase "at least one" in reference to a list of items means any combination of those items, including a single member. By way of example, "at least one of a, b, or c" is intended to cover: a, b, c, a - b, a - c, b - c, and a - b - c, as well as any combination having multiple of the same element (e.g., a - a, a - a - a, a - a - b, a - a - c, a - b - b, a - c - c, b - b, b - b - b, b - b - c, c - c, and c - c - c, or any other ordering of a, b, and c).

Claims

1. A method, the method comprising: Determine whether a target is within an in-path band of a predicted path of a host vehicle, the in-path band being centered on the predicted path and decreasing in width along the predicted path away from the host vehicle; And In response to determining that the target is within the in-path band: Determine a yaw rate threshold for the host vehicle, the yaw rate threshold being capable of being used to determine how to determine a main lateral movement of the host vehicle; Determine the main lateral movement based on whether the yaw rate of the host vehicle meets the yaw rate threshold; Based on the main lateral movement and the in-path band, determine whether the host vehicle is likely to be within the in-path band at a certain future time; Determine a lateral speed threshold for the target, the lateral speed threshold being capable of being used to determine how to determine a target lateral movement of the target; Determine the target lateral movement based on whether the lateral speed of the target meets the lateral speed threshold; Based on the target lateral movement and the in-path band, determine whether the target is likely to be within the in-path band at the future time; And In response to determining that the host vehicle and the target are likely to be within the in-path band at the future time, generate a collision indication that causes the host vehicle to perform an action.

2. The method according to claim 1, wherein The predicted path is based on the yaw rate of the host vehicle and the speed of the host vehicle.

3. The method according to claim 1, characterized in that The amount of decrease in the width of the in-path band is based on at least one of the following: the speed of the host vehicle, the yaw rate, or the distance between the host vehicle and the target.

4. The method according to claim 1, wherein The yaw rate threshold is based on at least one of the following: the speed of the host vehicle, the yaw rate, or road information.

5. The method according to claim 1, characterized in that, Determining the main lateral movement includes: In response to determining that the yaw rate does not meet the yaw rate threshold, determine the main lateral movement to be zero; or In response to determining that the yaw rate meets the yaw rate threshold, determine the main lateral movement based on the radius of curvature of the predicted path, the yaw rate, and the future time.

6. The method according to claim 1, wherein The future time includes an estimated time to collision between the host vehicle and the target.

7. The method according to claim 1, wherein The lateral speed threshold is based on at least one of the following: the speed of the target, the distance between the host vehicle and the target, or road information.

8. The method according to claim 1, wherein Determining the target lateral movement includes: In response to determining that the lateral speed does not meet the lateral speed threshold, determine the target lateral movement to be zero; or In response to determining that the lateral speed meets the lateral speed threshold, determine the target lateral movement based on the radius of curvature of the predicted path, the yaw rate, and the future time.

9. The method according to claim 1, characterized in that, Further generate the collision indication in response to at least one of the following: An earlier determination that the host vehicle and the target are likely to be within the in-path band at the future time; Determine that the target is within the road on which the host vehicle is traveling; Determine that when the target is turning, the host vehicle is not traveling in a straight line; Or Determine that when the target is moving straight, the host vehicle is not changing lanes or turning.

10. A system includes at least one processor configured to: Determine whether the target is within an in-path band of a predicted path of the host vehicle, the in-path band being centered on the predicted path and decreasing in width along the predicted path away from the host vehicle; And In response to determining that the target is within the in-band of the path: Determine a yaw rate threshold of the host vehicle, which can be used to determine how to determine the main lateral movement of the host vehicle; Determine the main lateral movement based on whether the yaw rate of the host vehicle meets the yaw rate threshold; Based on the main lateral movement and the in-band of the path, determine whether the host vehicle is likely to be within the in-band of the path at a certain future time; Determine a lateral speed threshold of the target, which can be used to determine how to determine the target lateral movement of the target; Determine the target lateral movement based on whether the lateral speed of the target meets the lateral speed threshold; Based on the target lateral movement and the in-band of the path, determine whether the target is likely to be within the in-band of the path at the future time; And In response to determining that the host vehicle and the target are likely to be within the in-band of the path at the future time, generate a collision indication.

11. The system according to claim 10, wherein, The predicted path is based on the yaw rate of the host vehicle and the speed of the host vehicle.

12. The system according to claim 10, wherein The width decrement of the in-band of the path is based on at least one of the following: the speed of the host vehicle, the yaw rate, or the distance between the host vehicle and the target.

13. The system according to claim 10, wherein The yaw rate threshold is based on at least one of the following: the speed of the host vehicle, the yaw rate, or road information.

14. The system according to claim 10, wherein Determining the main lateral movement includes: In response to determining that the yaw rate does not meet the yaw rate threshold, determine that the main lateral movement is zero; or In response to determining that the yaw rate meets the yaw rate threshold, determine the main lateral movement based on the radius of curvature of the predicted path, the yaw rate, and the future time.

15. The system according to claim 10, wherein The future time includes the estimated time to collision between the host vehicle and the target.

16. The system according to claim 10, wherein The lateral speed threshold is based on at least one of the following: the speed of the target, the distance between the host vehicle and the target, or road information.

17. The system according to claim 10, wherein, Determining the target lateral movement includes: In response to determining that the lateral speed does not meet the lateral speed threshold, determine that the target lateral movement is zero; or In response to determining that the lateral speed meets the lateral speed threshold, determine the target lateral movement based on the radius of curvature of the predicted path, the yaw rate, and the future time.

18. The system according to claim 10, wherein Further generate the collision indication in response to a previous determination that the host vehicle and the target are likely to be within the in-band of the path at the future time.

19. The system according to claim 10, wherein Further generate the collision indication in response to at least one of the following: Determine that the target is within the road on which the host vehicle is traveling; Determine that when the target is turning, the host vehicle is not moving straight; Or Determine that when the target is moving straight, the host vehicle is not changing lanes or turning.

20. A computer-readable storage medium, the computer-readable storage medium comprising instructions that, when executed by at least one processor, cause the processor to: Determine whether the target is within the in-path band of the predicted path of the main vehicle, where the in-path band is centered on the predicted path and decreases in width along the predicted path away from the main vehicle; and in response to determining that the target is within the in-band of the path: determine a yaw rate threshold for the host vehicle, the yaw rate threshold being usable to determine how to determine a main lateral movement of the host vehicle; determine the main lateral movement based on whether the yaw rate of the host vehicle meets the yaw rate threshold; based on the main lateral movement and the in-band of the path, determine whether the host vehicle is likely to be within the in-band of the path at a certain future time; determine a lateral speed threshold for the target, the lateral speed threshold being usable to determine how to determine a target lateral movement of the target; determine the target lateral movement based on whether the lateral speed of the target meets the lateral speed threshold; based on the target lateral movement and the in-band of the path, determine whether the target is likely to be within the in-band of the path at the future time; and in response to determining that the host vehicle and the target are likely to be within the in-band of the path at the future time, generate a collision indication.

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