Patent ID: 12241964

DETAILED DESCRIPTION

Overview

In some vehicles, including automobiles equipped with autonomous driving and advanced safety features, a perception system (e.g., a radar system, a lidar system, a camera system, other range sensor) is used to accurately localize the vehicle relative to other objects nearby. The perception system reports a relative position and size of nearby vehicles; an output from the perception system can be used as an input to another system (e.g., an autonomous driving system, an advanced safety system), thereby improving situational awareness and driving safety, including that of passengers of other vehicles.

A rectangular bounding box is commonly used to convey the relative position and size of another vehicle relative to a vehicle. The dimensions of the bounding box approximate groups of detections observed, relative to a vehicle position or position of other detections and/or bounding boxes in a field of view. Using rectangular bounding boxes still may come with some disadvantages.

When multiple vehicles are positioned in close proximity of each other (e.g., when vehicles tailgate by traveling unsafely in the same lane with little separation between them), a perception system can mistake a large group of detections for a single vehicle (e.g., that is greater than one car-length). Instead of drawing multiple bounding boxes to delineate each of the different vehicles, the perception system may inaccurately generate just one bounding box encompassing the entire group of detections. In addition, it is common for long vehicles to be tracked inaccurately. Long vehicles are often articulated, which by definition means the vehicle includes a combination of two or more rigid sections that are configured to pivot about a common hinge. A tractor-trailer, an accordion-style bus, and a truck towing a camper are some examples of articulated vehicles. In either case, where the perception system is incorrectly treating a group of detections, a rectangular bounding box may not always accurately represent the relative position and size of the one or more objects in the environment.

A perception system may struggle to accurately maintain a bounding box around a group of detections tied to a group of vehicles or a group of vehicle sections, particularly as each of the members of the group is allowed to move independently, even if only to slightly change its own direction or speed. A difference in these velocities can cause a bounding box dimension to stretch as the group of detections grow or shrink as the group of detections diminish (e.g., as an articulation angle, measured at a connecting hinge between to articulating sections increases beyond zero degrees). The perception system may overload a vehicle's onboard computer hardware attempting to resolve the group of detections to maintain the bounding box at its original dimensions (e.g., as the articulation angle increases and decreases with turning and a curvature of a road).

Furthermore, an inaccurately drawn bounding box can be particularly troubling for an autonomous driving or advanced cruise control system that relies on the perception system to make driving decisions. By mistaking a poorly drawn bounding box, the vehicle may incorrectly assume it is safe or unsafe to travel in an adjacent lane, particularly when traveling around a curve. In the real world, the tractor-trailer may safely stay in its travel lane, but to the perception system or other system that relies on its output, the tractor-trailer may appear to be an out-of-control vehicle or a vehicle that requires an unsafe separation distance, which can result in a manual override that requires an operator to take back control.

This document describes techniques and systems related to tracking different sections of articulated vehicles. Specifically, the techniques and systems provide a way for estimating a hinge point and an articulation angle of an articulated vehicle, given perception data obtained from a perception system. For ease of description, the described techniques primarily focus on the context of radar-based tracking, including radar tracking for automotive applications. The techniques may, however, apply to other types of tracking, including other types of tracking in automotive applications, as well as radar and other types of tracking in other non-automotive contexts. Also, for the ease of description, unless otherwise specified, an articulated vehicle has two separate sections, although the techniques generally apply to separately and concurrently tracking all sections of an articulated vehicle, including those with more than two sections.

As one example, a vehicle uses a radar system that can discern between unarticulated vehicles and articulated vehicles, which by definition have multiple sections that can pivot in different directions to assist in turning or closely following a curve in a road. The radar system obtains radar detections indicative of another vehicle traveling nearby. When the radar detections indicate the other vehicle may be an articulated vehicle, the radar system tracks each identifiable section, rather than tracking all the sections together. A bounding box is generated for each identifiable section; the radar system separately and concurrently monitors a velocity of each bounding box. The multiple bounding boxes that are drawn enable the radar system to accurately track each connected section of the articulated vehicle, including to detect whether any movement occurs between two connected sections, for accurately localizing the vehicle when both vehicles share a road. By configuring a perception system to convey, in its output, an articulated vehicle as two or more distinct bounding boxes, the techniques and systems improve driving safety and situational awareness.

Application of the described technique may have benefits for vehicle computer systems, including execution of a driving-software stack, which may include an object-fusion module configured to perform matching and grouping of multiple perception system outputs. In addition, a threat assessment and trajectory planning module that controls a trajectory of the vehicle may benefit from receiving a more-accurate definition of the edges of a target. With a more-accurate representation of an articulated vehicle than a single rectangular box, accuracy of downstream autonomous driving and advanced safety features that rely on the representation (e.g., a radar output) can be improved.

Example Environment

FIG.1-1illustrates an example environment100in which a vehicle with a radar system is configured to track different sections of an articulated vehicle, in accordance with this disclosure. The environment100includes a vehicle102equipped with a radar system104configured to track different sections of articulated vehicles, in accordance with techniques, apparatuses, and systems of this disclosure. An output from the radar system104may enable operations of the vehicle102. An object's range, angle of approach, or velocity may be determined by the radar system104or derivable from the output, which takes the form of radar data.

Although illustrated as a car, the vehicle102can represent other types of motorized vehicles (e.g., a motorcycle, a bus, a tractor, a tractor-trailer vehicle, or construction equipment), non-motorized vehicles (e.g., a bicycle), railed vehicles (e.g., a train or a trolley car), watercraft (e.g., a boat or a ship), aircraft (e.g., an airplane or a helicopter), or spacecraft (e.g., satellite). In general, the vehicle102represents any moving platform, including moving machinery or robotic equipment, that can benefit from having a radar representation of the environment100.

Detected in a field of view of the radar system104are multiple moving objects106,108, and110(also sometimes referred to as “targets of interest”). The moving objects108and110are referred to as unarticulated vehicles108and110. In contrast, the object106is referred to as an articulated vehicle106, which includes at least two discernible sections connected by a hinge. In general, the objects106,108, and110are composed of one or more materials that reflect radar signals or, in other examples, an appropriate reflection medium for enabling detection by some other type of perception sensing system. Depending on the application, the objects106,108, and110can represent detections of individual targets, one or more clutter(s) of radar detections, one or more cluster(s) of radar detections, and/or one or more cloud(s) of radar detections. Throughout this disclosure, the detections, the clutter, the clusters, and/or the clouds of radar detections are represented with small circles (dots), where each small dot represents an example of one or more radar detections.

The radar system104is configured for installation as part of the vehicle102. In the depicted environment100, the radar system104is mounted near, or integrated within, a front portion of the vehicle102to detect the objects and avoid collisions. The radar system104can be a mechanic-replaceable component, part, or system of the vehicle102, which, due to a failure, may need to be replaced or repaired over the life of the vehicle102. The radar system104can include an interface to at least one automotive system. The radar system104can output, via the interface, a signal based on electromagnetic energy received by the radar system104. The output signal from the radar system104represents radar data and can take many forms.

At least one automotive system of the vehicle102relies on the radar data that is output from the radar system104. Examples of such automotive systems include a driver-assistance system, an autonomous-driving system, or a semi-autonomous-driving system. Another example of systems that may rely on the radar data provided by the radar system104can include a fusion tracker that combines sensor data from a variety of perception sensors, including the radar system104, to generate a multi-sensor representation of the environment100. A benefit to operating a fusion tracker using a multiple-bounding-box representation of an articulated vehicle instead of a single bounding box is that the fusion tracker may operate more efficiently and with greater accuracy. The fusion tracker can quickly combine the radar data with other high-resolution sensor data that aligns with the radar data. With the radar tracking individual sections of an articulated vehicle, the fusion tracker can convey, in its fused output, relative changes in movement between individual sections of an articulated vehicle, providing a sensor fusion output that is more accurate than if fusion tracking with a conventional radar system that is not configured to track articulated vehicles in accordance with the described techniques.

The automotive systems of the vehicle102may use radar data provided by the radar system104to perform a function, also referred to as a vehicle operation. In the environment100, the radar system104can detect and track the multiple moving objects106,108, and110by transmitting and receiving one or more radar signals through an antenna system. For example, a driver-assistance system can provide blind-spot monitoring and generate an alert indicating a potential collision with the object106detected by the radar system104. To do so, the radar system104can transmit electromagnetic signals between 100 and 400 gigahertz (GHz), between 4 and 100 GHz, or between approximately 70 and 80 GHz. The radar system104includes a transmitter (not illustrated) and at least one antenna element to transmit electromagnetic signals. The radar system104includes a receiver (not illustrated) and at least one antenna element, which may be the same or different than the transmit element, to receive reflected versions of these electromagnetic signals. The transmitter and the receiver can be incorporated together on the same integrated circuit (e.g., a transceiver integrated circuit or package) or separately on different integrated circuits or chips.

The radar system104may track the objects106,108, and110as they appear to be driving in a field of view. For example, as the radar system104increasingly detects a higher count of radar detections, the radar system104can detect and track one or more clusters of radar detections, such as at a rear, a middle, and/or a front of the articulated vehicle106. Without necessarily determining whether the articulated vehicle106is articulated, the radar system104can at least determine whether the various clusters of radar detections off the object106represent a same vehicle or object.

The radar system104can create a bounding box112for the entire object106. In furtherance of drawing the bounding box112, the radar system104can determine whether these various clusters of radar detections are stationary or non-stationary; whether the clusters of radar detections associated with the objects106move with approximately a same or a different velocity (speed and direction); and whether a range (distance) between each cluster of the object106is changing or is nearly constant. Similarly, the radar system104can create a bounding box114for the object108and a bounding box116for the object110. In continuing the example with driver-assistance system receiving radar data from the radar system104, the radar data may indicate to the driver-assistance system dimensions of the bounding boxes112,114, and116, that the driver-assistance system may use to determine positions of the objects106,108, and110, e.g., for determining when it is safe or unsafe to change lanes. Based on the radar data being output from the radar system104, an autonomous-driving system may move the vehicle102to a particular location on the road while avoiding collisions with the objects106,108, and110.

Articulation Determination

FIG.1-2illustrates another example environment100-1in which a vehicle with a radar system is configured to track different sections of an articulated vehicle, in accordance with this disclosure. The environment100-1is an example of the environment100, in which the vehicle102overtakes or drives adjacent to the articulated vehicle106when both vehicles102and106are driving on a turn.

When approaching the articulated vehicle106, the radar data output from the radar system104may enable the autonomous-driving system of the vehicle102to determine whether to perform emergency braking, whether to perform a lane change, whether to adjust a speed, or whether to take any driving action at all. The autonomous-driving system can base those determinations on size, positions, and movement of individual sections of the articulated vehicle106relative to safety margins the vehicle102uses for driving through traffic.

Other radar systems may track the articulated vehicle106with only the single bounding box112, as shown in bothFIGS.1-1and1-2. When driving straight, a single bounding box for an articulated vehicle may be a somewhat accurate representation of the vehicle's size and position. However, when the road turns and the articulated vehicle is made to turn with it, the single bounding box approximation has multiple errors when compared to the vehicle's true size and position. As shown inFIG.1-2, the bounding box112is inaccurately reporting the position of the articulated vehicle106so that the articulated vehicle106appears to be crossing into a travel lane of the vehicle102. The vehicle102, if equipped with a radar system that is not configured in accordance with the techniques of this disclosure, may falsely determine that the articulated vehicle106is veering into or out of the travel lane. Therefore, the radar data that is output from these other radar systems may be inaccurate at times (particularly around turns). Consequently, always representing and tracking an articulated vehicle using just a single bounding box can compromise safe driving, especially while driving on a curved or windy road.

Unlike these other types of radar systems, the radar system104is configured to determine whether an object being tracked is articulated. The radar system104can track individual sections of an articulated vehicle, and output radar data with bounding boxes sized and positioned to correspond to the individual sections being tracked, rather than outputting radar data with a single bounding box that roughly approximates the articulated as a static unarticulated shape. For example, the radar system104can generate a bounding box112-1at the front of the articulated vehicle106and further generate a bounding box112-2near the rear of the articulated vehicle106. As will become clear below, the radar system104can track an estimated hinge point between the front and rear sections of the articulated vehicle106and maintain resemblance of actual movement of the articulated vehicle106in repositioning and rotating the bounding boxes112-1and112-2about the estimated hinge point.

By individually tracking multiple sections of the articulated vehicle106using at least two bounding boxes112-1and112-2instead of only generating the bounding box112, the radar system104enables the vehicle102to drive safely past, or adjacent to, the articulated vehicle106with a fluid driving maneuver that is free of hesitation or jerkiness. The radar system104does not misrepresent the detections in a course manner using only the bounding box112. This way, when the articulated vehicle106is detected by the radar system104, the radar data output to the driver-assistance system provides a highly accurate size and position representation of where different articulated sections of the articulated vehicle106appear in real life. This enables the vehicle102to drive in autonomous or semi-autonomous modes in a smooth and predictable manner, which resembles a driving style of a confident driver that is operating the vehicle102in a similar scenario but under manual control.

To enable tracking of articulated sections, the radar system may initially represent the object106using the bounding box112. With most articulated vehicles being longer than a standard passenger vehicle, the radar system104can apply a vehicle length-based criterion to the bounding box112before expending computing resources to determine whether the object106being represented is articulated. This initial filter of smaller vehicles prevents computing sources from having to determine whether every object is an articulated vehicle or not, which improves computational efficiency of the radar system104.

The radar system104may utilize a threshold length (e.g., greater than 3.0 meters), which, when compared to dimensions of the bounding box112, can be used as an indicator to classify the object106as possibly articulated or as not possibly articulated. In other words, whether or not an object is articulated may depend on whether that object is greater than the length threshold (e.g., greater than a regular passenger car length). The radar system104may compare a length of the bounding box112to the length threshold to determine whether the object106has a potential for being articulated, even if (as is illustrated inFIG.1-1) all sections appear, in the radar data, to be fixed in an unarticulated manner (e.g., when driving on a straight road). This length threshold can be applied by the radar system104prior to or as a condition of determining whether the object is actually articulated. This way, if a bounding-box length is estimated to be greater than the threshold length, the object is classified as a possibly articulated vehicle, which is suitable for further processing to determine whether articulation exists. With a bounding box that does not exceed the threshold length, the radar system104may classify an object as a short vehicle that is not a possible articulated vehicle, which, therefore, can be tracked using a single bounding box.

Whether a vehicle is articulated or unarticulated is not typically a concern for shorter vehicles that can easily fit within safety margins of a travel lane. This initial length criteria that may be applied by the radar system104derives some of its benefit from a relationship that exists between a vehicle length and a turn radius; long vehicles tend to have a wide turn radius. This wide turn-radius makes driving a challenge, particularly when other vehicles are traveling in adjacent lanes or when driving in narrow streets with parked cars and other static moving objects that share the road, which may necessitate reliance on some form of articulation. Because of a hinge connecting two sections that are allowed to pivot, an articulated vehicle, such as the articulated vehicle106, can make sharper turns (without encroaching on an adjacent lane or shoulder) than an unarticulated vehicle, such as the unarticulated vehicle108, which is of comparable length. The use of a hinge and articulation configuration is not necessary for a standard-length vehicle, such as the object110, but more often applies to vehicles that are longer than the standard length. Hence, the radar system104, responsive to determining that the object110is not of sufficient length, can refrain from determining whether the object110is articulated or unarticulated and default to tracking the object110as an unarticulated vehicle. That said, the ultimate determination as to whether a vehicle is articulated cannot be determined based on length alone.

Another possible indicator of an articulated vehicle is a behavior of the vehicle during a turning maneuver or when driving around a curve. The radar system104may initially consider the articulated vehicle106and the unarticulated vehicle108to both be possible articulated vehicles until the radar system104can capture sufficient information about the size and position of any intermediate sections, which often occurs during a turn. That is, eventually, when the road turns or a possible articulated vehicle turns, each individual section that makes up the articulated vehicle106can be observed as groups of detections that appear to move with different velocities the further the vehicle travels into a curve. Articulation enables the articulated vehicle106to follow a curve more closely than an unarticulated vehicle, such as the unarticulated vehicle108. In practice, this means that a front section of the articulated vehicle106will have a grouping of radar detections that have a velocity120-1that is different than a velocity120-2of a group of radar detections captured at a tail section of the articulated vehicle106. Whereas the group of detections at the front of the unarticulated vehicle108will appear in the radar data to have a somewhat consistent velocity with the group of detections at the tail of the unarticulated vehicle108.

Example Device

FIG.2illustrates an example vehicle102-1, including a radar system104-1configured to track different sections of an articulated vehicle, in accordance with this disclosure. The radar system104is an example of the radar system104. The vehicle102-1is an example of the vehicle102.

The radar system104-1may be part of an object detection and tracking system202. In addition to the radar system104-1, the object detection and tracking system202may also include a lidar system204, an imaging system206, and/or other systems that may be used to detect and track an object. The radar system104-1, however, can operate as a standalone system without communicating with or using data from the lidar system204and/or the imaging system206. Additionally, the object detection and tracking system202can perform the techniques and the methods described herein by using radar data from the radar system104-1alone.

The vehicle102-1also includes a vehicle-based system210, such as a driver-assistance system212and/or an autonomous-driving system214. The vehicle-based system210uses radar data from the radar system104-1to perform a function. For example, the driver-assistance system212tracks articulated (e.g., the object106) and/or unarticulated vehicles (e.g., the objects108and110), monitors their proximity to the vehicle102-1and generates an alert that indicates a potential collision or an unsafe distance to the vehicles driving alongside the vehicle102-1. In this case, radar data (e.g., targets of interest, clutter(s) of radar detections, cluster(s) of radar detections, and/or cloud(s) of radar detections) from the radar system104-1indicate whether the vehicle102-1may safely drive alongside the other vehicles in the field of view.

As another example, on a windy road, the driver-assistance system212suppresses false alerts responsive to radar data indicating that an articulated vehicle (e.g., the object106) driving on an adjacent lane is veering into a travel lane of the vehicle102-1. In this way, the driver-assistance system212can avoid falsely alerting a driver of the vehicle102-1that the articulated vehicle is driving unsafely close or colliding with the vehicle102-1. By suppressing these false alerts, the driver-assistance system212avoids confusing or unnecessarily worrying the driver of the vehicle102-1.

The autonomous-driving system214may move the vehicle102-1to a particular location while avoiding collisions with or getting unsafely close to the vehicles driving alongside the vehicle102-1. The radar data provided by the radar system104-1can provide information about the other objects' location and movement to enable the autonomous-driving system214to perform emergency braking, perform a lane change, or adjust the vehicle102-1's speed. Additionally, the autonomous-driving system214of the vehicle102-1can determine whether a vehicle driving alongside is an articulated vehicle. When driving alongside the articulated vehicle, the autonomous-driving system214of the vehicle102-1performs a driving maneuver by tracking separately and concurrently the different sections of the articulated vehicle, as is further described below.

The radar system104-1includes a communication interface220to transmit the radar data to the vehicle-based system210or another component of the vehicle102-1over a communication bus of the vehicle102-1. In general, the radar data provided by the communication interface220is in a format usable by the object detection and tracking system202. In some implementations, the communication interface220may provide information to the radar system104-1, such as the speed of the vehicle102-1or whether a turning blinker is on or off. The radar system104-1can use this information to appropriately configure itself. For example, the radar system104-1can determine if a selected object (e.g.,106) is stationary by comparing a Doppler for the selected object to the speed of the vehicle102-1. Alternatively, the radar system104-1can dynamically adjust the field of view or in-lane azimuth angles based on whether a right-turning blinker or a left-turning blinker is on.

The radar system104-1also includes at least one antenna array222and at least one transceiver224to transmit and receive radar signals. The antenna array222includes at least one transmit antenna element and a plurality of receive antenna elements separated in azimuth and elevation directions. In some situations, the antenna array222also includes multiple transmit antenna elements to implement a multiple-input multiple-output (MIMO) radar capable of transmitting multiple distinct waveforms at a given time (e.g., a different waveform per transmit antenna element). The antenna elements can be circularly polarized, horizontally polarized, vertically polarized, or a combination thereof.

Using the antenna array222, the radar system104can form beams that are steered or un-steered and wide or narrow. The steering and shaping can be achieved through analog beamforming or digital beamforming. The one or more transmitting antenna elements can have, for instance, an un-steered omnidirectional radiation pattern or can produce a wide steerable beam to illuminate a large volume of space. To achieve target angular accuracies and angular resolutions, the receiving antenna elements can be used to generate hundreds of narrow steered beams with digital beamforming. In this way, the radar system104-1can efficiently monitor an external environment and detect one or more sections of an articulated vehicle, such as a first section of an articulated vehicle and a second section of the articulated vehicle.

The transceiver224includes circuitry and logic for transmitting and receiving radar signals via the antenna array222. Components of the transceiver224can include amplifiers, mixers, switches, analog-to-digital converters, or filters for conditioning the radar signals. The transceiver224also includes logic to perform in-phase/quadrature (I/Q) operations, such as modulation or demodulation. A variety of modulations can be used, including linear frequency modulations, triangular frequency modulations, stepped frequency modulations, or phase modulations. The transceiver224can be configured to support continuous-wave or pulsed radar operations. A frequency spectrum (e.g., range of frequencies) that the transceiver224uses to generate the radar signals can encompass frequencies between one and four-hundred gigahertz (GHz), between four and one hundred GHz, or between approximately seventy and eighty GHz, for example. The bandwidths can be on the order of hundreds of megahertz or on the order of gigahertz.

The radar system104-1also includes one or more processors226. The processor226can be implemented using any type of processor, for example, a central processing unit (CPU), a microprocessor, a multi-core processor, and so forth. Although the processor226is illustrated as being part of the radar system104-1, the processor226can be part of the object detection and tracking system202and may support the lidar system204and the imaging system206, in addition to the radar system104-1.

The object detection and tracking system202that includes the radar system104-1also includes one or more computer readable media (CRM)230(e.g., a computer-readable storage medium), and the CRM230excludes propagating signals. The CRM230may include various data-storage media, such as volatile memory (e.g., dynamic random-access memory, DRAM), non-volatile memory (e.g., Flash), optical media, magnetic media, and so forth. The CRM230may include instructions (e.g., code, algorithms) that may be executed using the processor226. The instructions (not illustrated) stored in the CRM230, in part, interpret, manipulate, and/or use sensor data232that may also be stored in the CRM230. The sensor data232includes the radar data (e.g., clutters of radar detections, clusters of radar detections, and/or clouds of radar detections) of the radar system104-1. The sensor data232may also include lidar data of the lidar system204and imaging data (e.g., video, still frames) of the imaging system206. In one aspect, the instructions stored in the CRM230include a vehicle tracker234and an articulated vehicle tracker236.

The vehicle tracker234may share some similarities with an existing vehicle tracker and can detect and track stationary and/or non-stationary objects. The vehicle tracker234can determine whether various clusters of radar detections are being reflected from one object or multiple objects. The vehicle tracker234can generate a bounding box for each detected vehicle in the proximity of the vehicle102-1. The vehicle tracker234may determine and track a location, a centroid, and a velocity vector of each bounding box. Unlike other existing vehicle trackers, however, the vehicle tracker234may categorize and treat long vehicles differently in the proximity of the vehicle102-1. Specifically, once the vehicle tracker234determines that a vehicle meets or exceeds a threshold length (e.g., greater than 3.0 meters), the vehicle tracker234triggers the articulated vehicle tracker236to make a determination about whether the target is an articulated vehicle.

The articulated vehicle tracker236helps determine whether a vehicle is articulated or unarticulated. If the articulated vehicle tracker236determines that a vehicle is articulated, the articulated vehicle tracker236then determines a location of a hinge point, where the hinge point couples or connects a first section (first part) and a second section (second part) of the articulated vehicle. Using the articulated vehicle tracker236, the radar system104-1of the vehicle102-1can track separately and concurrently the first and the second sections of the articulated vehicle. The articulated vehicle tracker236can generate a first bounding box associated with a first section (e.g., front-end section) of a possible articulated vehicle and a second bounding box (e.g., rear-end section) associated with a second section of the possible articulated vehicle. The articulated vehicle tracker236enables the radar system104to track separately and concurrently the first and the second bounding boxes of the suspected articulated vehicle.

The radar system104-1may use the vehicle tracker234and the articulated vehicle tracker236concurrently. The articulated vehicle tracker236may also use the lidar system204to estimate a closest edge to the vehicle102-1of the articulated vehicle. Before describing the articulation determination in detail, next,FIG.3describes shortcomings of some other existing vehicle trackers that may track an articulated vehicle using only a single bounding box as opposed to using multiple boxes, as is done with the radar system104-1.

FIG.3illustrates an example environment300showing some drawbacks of using a conventional radar system, which is not configured to track different sections of an articulated vehicle. The environment300includes a portion of a road that turns to the right. A tractor-trailer vehicle306, which is an articulated vehicle, drives alongside a vehicle302that is equipped with a traditional radar system that is unable to discern whether articulation exists with a target. Unlike the vehicle102-1, the vehicle302uses a radar system304without the aid of the articulated vehicle tracker236. The existing radar system304fails to determine that the tractor-trailer vehicle306is an articulated vehicle. Instead, the existing radar system304may detect and track the tractor-trailer vehicle306as being non-articulated. This may be a reasonable approach if the vehicle302and the tractor-trailer vehicle306always drive on straight road lanes, but this approach fails as the vehicles drive on a bendy or curvy portion of the road, as is illustrated inFIG.3.

In one aspect, the radar system304may detect one or more clusters of radar detections at a rear, a front, and anywhere in-between the tractor-trailer vehicle306. The radar system304may then determine that all the radar detections are associated with a single vehicle, inFIG.3, the tractor-trailer vehicle306. The radar system304can then create a single bounding box312for the whole tractor-trailer vehicle306. As is illustrated inFIG.3, by not using the articulated vehicle tracker236, the tracked velocity vector320-1is inconsistent with a velocity vector320-2of the tractor-trailer vehicle306. More importantly, the bounding box312fails to accurately represent where the tractor-trailer vehicle306is located on the road, relative to a position of the vehicle302. Instead, as both vehicles320and306may make a right turn, the bounding box312appears to encroach closer to the vehicle302within an unsafe separation distance. Consequently, by using the radar system304, a driving system (e.g., an autonomous-driving system) of the vehicle302may overcorrect motion of the vehicle302and cause the vehicle302to drive unsafely into another lane, driving outside the road, speeding up, breaking, or performing any other unnecessary driving maneuver, which may diminish driving safety and reduce passenger comfort.

Hinge Points and Articulation Angles

FIGS.4-1to4-2illustrate example environments400-1and400-2, showing further details of using a radar system that is configured to track different sections of an articulated vehicle, in accordance with this disclosure. The environments400-1and400-2are described in the context ofFIGS.1and2. Each of the environments400-1and400-2includes a vehicle102-2, which is an example of the vehicles102and102-1. Driving in an adjacent lane to the vehicle102-2is a semi-tractor trailer106-2, which is an example of the objects106-1and106.

Focusing first onFIG.4-1, in response to the radar system104-2identifying the semi-tractor trailer106-2as a long vehicle, the vehicle tracker234invokes the articulated vehicle tracker236for further processing of the radar data produced by the radar system104-2to determine whether an object being tracked by the vehicle tracker234is articulated.

Independent of how the vehicle tracker234treats the semi-tractor trailer106-2, the articulated vehicle tracker236begins tracking a suspected articulated vehicle by locating a hinge point between two sections of the suspected articulated vehicle. For example, the articulated vehicle tracker236can tell that a large group of detections at the back of the semi-tractor trailer are moving consistently with another group of detections at the front of the semi-tractor trailer. A hinge point422-1can be determined to be at an intersection between a velocity vector420-1of the back section and a velocity vector420-2of the front section. The articulated vehicle tracker436can generate a first bounding box412-1around the back section and a second bounding box412-2around the front section. The articulated vehicle tracker236determines the hinge point422-1to be between the first and second bounding boxes412-1and412-2, such that they are not overlapping. In this situation, the articulation angle424-1between the first bounding box412-1and the second bounding box412-2is approximately zero degrees. When the articulation angle424-1is near zero, the hinge point422-1determination can be difficult to resolve.

Switching toFIG.4-2, the articulated vehicle tracker236may wait until the vehicle102-2and the semi-tractor trailer106-2are driving on a curved road or taking a turn before establishing a hinge point422-2. In this situation, the articulation angle424-2between the first bounding box412-1and the second bounding box412-2is greater than zero degrees. The articulated vehicle tracker236can extrapolate the velocity vector420-1and the velocity vector420-2to find the intersection at which the hinge point422-2estimation is made.

Upon extrapolating out to the hinge point422-2, the articulated vehicle tracker236can regularly update its calculations to improve its track on the semi-tractor trailer106-2. For example, as a turn becomes increasingly sharper, the articulated vehicle tracker236may identify an increasing difference in the velocity vectors420-1and420-2. This increase in the articulation angle424-2provides an increased accuracy in the hinge point422-2. Depending on the capability of the radar system104-2, the hinge point422-2may become valid for subsequent use in controlling the vehicle102-1in response to a degree of certainty in the calculation being achieved. The articulated vehicle tracker236may output a degree of certainty or confidence associated with its radar data calculations, including the hinge point422-2. When the articulation angle424-2is near zero degrees, this degree of certainty may be low, whereas when the articulation angle424-2deviates from zero degrees, the confidence in the hinge point422-2is increasing.

Based on the estimated hinge point422-2and the articulation angle424-2, the articulated vehicle tracker236determines, based further on an estimated width of the object106-2being tracked, positions and orientations of one or more side edges426of the articulated vehicle being tracked. A width428of the object106-2being tracked corresponds to the estimated width of either of the bounding boxes412-1and412-2. The width428of the object106-2, the hinge point422-2, and the articulation angle424-2are used by the articulated vehicle tracker236to estimate the locations of the side edges426of the vehicle. In some cases, a remote processing service may assist in analyzing radar data collected during this time to aid in resolving the locations of the side edges426. Low-pass filtering may be used to reduce noise on these estimates. Long-term understanding of the hinge point422-2and the articulation angle424-2as determined over time can be used as feedback information to help reduce noise levels and improve accuracy of the bounding boxes412-1and412-2, which are now linked to movement of individual articulated sections. The articulated vehicle tracker236may output a position of the edge426of the semi-tractor trailer106-2that is closest to the vehicle102as an indication of a safety buffer zone.

The articulated vehicle tracker236may determine the width428of the first bounding box412-1in addition to determining the width428of the second bounding box412-2, from which an overall width428of the semi-tractor trailer106-2is estimated (e.g., by averaging, by taking a greater of). To estimate the closest edge426of the semi-tractor trailer106-2, the articulated vehicle tracker236uses the hinge point422-2, the articulation angle424-2, and the width428to estimate a portion of the edge426between two articulated sections. By providing a highly accurate representation of the semi-tractor trailer106-2, as it turns, the articulated vehicle tracker236enables the vehicle102-2to be able to safely drive adjacent to the semi-tractor trailer106-2, without any false pre-collision warnings that might otherwise happen if the semi-tractor trailer106-2were tracked with just one bounding box, instead of the two bounding boxes412-1and412-2.

Example Process

FIG.5illustrates a process500for tracking different sections of an articulated vehicle, in accordance with this disclosure. The process500is shown as a set of operations (or acts) performed but not necessarily limited to the order or combinations in which the operations are shown herein. Further, any of one or more of the operations may be repeated, combined, or reorganized to provide other methods. In portions of the following discussion, reference may be made to entities detailed in the other drawings, reference to which is made for example only. The process500is not limited to performance by one entity or multiple entities.

At502, a vehicle driving in a field of view of a radar system is tracked using a single bounding box. For example, the radar system104can track the object106in a field of view using the bounding box112.

At504, whether the vehicle is a long vehicle is determined. For example, the radar system104compares a length of the bounding box112to a length threshold. If this length is less than the threshold, the NO branch from504is taken, and the object106is tracked with the bounding box112alone. However, in response to determining that the object106is a long vehicle based on the length exceeding the length threshold, the YES branch from504is taken. This point in the process500coincides with the vehicle tracker234invoking the articulated vehicle tracker236, which may represent two parallel tracking schemes until the radar system104is confident that the object106can be tracked with only one bounding box or if multiple bounding boxes should be used, in the case of articulation.

At506, a bounding box for a front section of the vehicle and another bounding box for a rear section of the vehicle are determined. For example, the radar system104may generate bounding boxes112-1and112-2.

At508, a velocity vector determined for each of the two bounding boxes generated for the front and rear sections is determined. For example, the bounding boxes112-1and112-2are characterized by the velocity vector120-1and the velocity vector120-1.

At510, whether the vehicle is articulated is determined. For example, the velocity vectors120-1and120-2are monitored. A hinge point can be determined by estimating an intersection between the two velocity vectors120-1and120-2, particularly when the object106is traveling around a turn and the front and rear sections, if articulated, are allowed to move in different directions. If the articulation angle at the hinge point remains near zero degrees, even during a turning maneuver, the NO branch from510is taken and the vehicle is determined to be unarticulated. If the articulation angle at the hinge point increases above zero degrees, particularly during a turning maneuver, the YES branch from510is taken and the vehicle is determined to be articulated.

At512, the vehicle is tracked using the two bounding boxes generated for the front and rear sections instead of the single bounding box. For example, the two bounding boxes112-1and112-2may replace the bounding box112. In other examples, the bounding box112may be generated in addition to the two bounding boxes112-1and112-2, with the bounding box112being designated as a less accurate solution for the object106.

At514, a driving maneuver is performed based on the two bounding boxes generated for the front and rear sections. For example, the radar system104outputs to an autonomous driving system an indication of the two bounding boxes112-1and112-2. With an estimated nearest edge of the object106determined from dimensions of the bounding boxes112-1and112-2, the vehicle102can drive safely adjacent or otherwise near the object106without receiving false alarms or false reporting of potential collision situations.

As another example, consider the radar system104tracking the object108using the bounding box114. In this example, the object108is a school bus and, therefore, unarticulated.

For example, at504, the radar system104compares a length of the bounding box114to a length threshold. If this length is less than the threshold, the NO branch from504is taken and the object108is tracked with the bounding box114alone. However, in response to determining that the object108is a long vehicle based on the length exceeding the length threshold, the YES branch from504is taken.

At506, the radar system104produces a bounding box for a front section of the object108, and another bounding box for a rear section of the object108is determined.

At508, a velocity vector determined for each of the two bounding boxes generated for the front and rear sections of the object108is evaluated to determine, at510, whether the object108is articulated. For instance, a hinge point can be determined by estimating an intersection between two velocity vectors, particularly when the object108travels around a turn and the front and rear sections, if articulated, are allowed to move in different directions. If the articulation angle at the hinge point remains near zero degrees, even during a turning maneuver, the NO branch from510is taken and the object108is determined to be unarticulated. The unarticulated vehicle is tracked using just the single bounding box114. A driving maneuver can be performed using an edge of the bounding box114to keep the vehicle102out of the path of the object118, particularly when in an adjacent lane during a turn.

Accuracy Improvement

FIGS.6-1and6-2illustrate aspects of an accuracy improvement function of a radar system that is configured to track different sections of an articulated vehicle, in accordance with this disclosure. In each of the various examples described above, there is an implicit assumption that a velocity vector of a steerable section of an articulated vehicle (e.g., a tractor portion of a tractor-trailer vehicle) is parallel to that section's longitudinal axis and, therefore, can be used as a direct indication of the angular orientation of the velocity vector of the steerable section. In reality, if radar detections are associated with a front portion of the steerable section (e.g., a front portion of the tractor part of a tractor-trailer vehicle), then the angular orientation of the velocity vector of the steerable section may be reported as more closely related to the direction the front wheels are pointing.

For example,FIG.6-1includes an environment600in which a velocity vector604of a steerable portion of a tractor-trailer vehicle is reported by the radar system104. Also represented inFIG.6-1is a direction602(angular orientation) of a longitudinal axis of the steerable portion of a tractor-trailer vehicle. The steerable portion is connected at a hinge point622to a trailer portion; the two portions of the tractor-trailer are meant to pivot at the hinge point622to affect an articulation angle624that is computed between them. A consequence of assuming that the velocity vector604is parallel to the direction602of the longitudinal axis is that edge positions may appear in an incorrect location, and the hinge point622may be incorrect. An articulated vehicle tracker, such as the articulated vehicle tracker236, may invoke an accuracy improvement function, which reduces this inaccuracy.

To prevent or at least diminish this inaccuracy, position information, velocity information, and curvature information associated with front and rear bounding boxes may be used in combination with a tractor-trailer vehicle dynamics model to estimate the hinge point622. The direction602can be computed as a parallel line to a connecting line between a front position of a front bounding box, with the hinge point622.

For example,FIG.6-2depicts an example tractor-trailer dynamics model630. The hinge point622is located at the intersection of the trailer's longitudinal axis with a line containing each of the trailer and tractor sections, one center of rotation (COR) for the tractor, and one COR for the trailer. The trailer section's longitudinal axis is the line containing the trailer's velocity vector at a rear position (which can be assumed to be centered laterally on the trailer). Each COR can be easily computed from this position, velocity, and curvature information.

For example, the radar system104updates, based on an accuracy improvement function, the bounding box112-1and the bounding box112-2. By running track filters on the bounding boxes112-1and112-2, the radar system104outputs dimensions including COR from the position, velocity, and curvature information reported from the track filters. The radar system104can compute the line intersection of the COR lines to obtain a position of the hinge point622. The location of the hinge point622is assumed to be unchanging with time. Hence, any historical information regarding that position obtained under good conditions (e.g., with CORs on opposite ends of the tractor-trailer vehicle) can be used at a current time instant, even under bad conditions. Then, the articulation angle624is computed along with a pointing angle of the tractor portion.

There are a number of practical issues to be overcome for this Accuracy Improvement Idea to be feasible. Track filters executed by the radar system104can have time lags, especially in reporting a curvature estimate. This may cause the CORs computed using slow track filters to have significant levels of error. Because these CORs may be used to compute a line intersecting with the trailer longitudinal axis, there may be a significant error in the computed hinge point622. If the two CORs are near each other, then the error in the computed intersection point will be particularly sensitive to the errors in the COR positions. In the extreme but presumably common case of an entire tractor-trailer vehicle being in a steady-state turn, the two CORs are to be located at the same position, theoretically making it difficult to identify the location of the hinge point622. That said, a trailer's orientation may be unaffected by the outcome of the computation of the location of the hinge point622; only its length may be affected.

The radar system104uses the accuracy improvement function to determine an updated velocity of the bounding box112-1and an updated velocity of the bounding box112-2and determine whether the object106is an articulated vehicle. Responsive to determining whether the object106is an articulated vehicle based on the updated velocities, the radar system104may output updated radar data that causes the vehicle102to perform a driving maneuver by separately or concurrently tracking the bounding boxes112-1and112-2.

EXAMPLES

Some further examples of tracking articulated vehicles in proximity to a vehicle are described below.

Example 1. A method, comprising: tracking, by a first vehicle, a second vehicle driving in a field of view of a radar system of the first vehicle, the tracking of the second vehicle comprising: generating, using the radar system of the first vehicle, a first bounding box associated with a first section of the second vehicle and a second bounding box associated with a second section of the second vehicle; and determining, based on a first velocity vector associated with the first bounding box and a second velocity vector associated with the second bounding box, whether the second vehicle is an articulated vehicle; and responsive to determining that the second vehicle is the articulated vehicle, performing, by the first vehicle, a driving maneuver by separately and concurrently tracking, in the field of view, the first bounding box and the second bounding box.

Example 2. The method of example 1, further comprising: initiating the determining of whether the second vehicle is the articulated vehicle responsive to the second vehicle meeting or exceeding a threshold length; responsive to the second vehicle being the articulated vehicle, locating a hinge point on or between the first section and the second section of the articulated vehicle; and responsive to locating the hinge point, setting the first bounding box and the second bounding box to be non-overlapping.

Example 3. The method of example 2, further comprising: locating the hinge point responsive to the articulated vehicle driving on a curved road or taking a turn; and determining an articulation angle between the first bounding box and the second bounding box, wherein the articulation angle is greater than zero degrees.

Example 4. The method of example 3, further comprising: determining a width of the first bounding box; determining a width of the second bounding box; estimating a closest edge of the articulated vehicle to the first vehicle by using: the hinge point; the articulation angle; the first width; and the second width; and performing, by the first vehicle, the driving maneuver by avoiding driving unsafely close to or colliding with the articulated vehicle.

Example 5. The method of example 4, further comprising: further performing, by the first vehicle, the driving maneuver by avoiding the edge of the articulated vehicle.

Example 6. The method of example 1, further comprising: tracking, by the first vehicle, a third vehicle driving in the field of view of the radar system, the tracking of the third vehicle comprising: generating, using the radar system, a third bounding box associated with a first section of the third vehicle and a fourth bounding box associated with a second section of the third vehicle; determining, based on a third velocity vector associated with the third bounding box and a fourth velocity vector associated with the fourth bounding box, that the third vehicle is an unarticulated vehicle; and replacing the third bounding box and the fourth bounding box with a fifth bounding box associated with the first section and the second section of the third vehicle; and responsive to determining that the third vehicle is the unarticulated vehicle, performing, by the first vehicle, another driving maneuver by tracking, in the field of view, the fifth bounding box associated with the third vehicle.

Example 7. The method of example 1, further comprising: updating, based on an accuracy improvement function, the first bounding box and the second bounding box; determining, based on an updated first velocity vector associated with the first bounding box and an updated second velocity vector associated with the updated second bounding box, whether the second vehicle is an articulated vehicle; and responsive to determining that the second vehicle is the articulated vehicle based on the updated first velocity vector and the updated second velocity vector, separately or concurrently tracking, in the field of view, at least one of the first bounding box or the second bounding box to perform the driving maneuver.

Example 8. A system comprising at least one processor of a first vehicle, the at least one processor configured to: track a second vehicle driving in a field of view of a radar system of the first vehicle, the at least one processor configured to track the second vehicle by: generating a first bounding box associated with a first section of the second vehicle and a second bounding box associated with a second section of the second vehicle; and determining, based on a first velocity vector associated with the first bounding box and a second velocity vector associated with the second bounding box, whether the second vehicle is an articulated vehicle; and responsive to determining that the second vehicle is the articulated vehicle, perform a driving maneuver by separately and concurrently tracking, in the field of view, the first bounding box and the second bounding box.

Example 9. The system of example 8, wherein the at least one processor is further configured to track the second vehicle by: initiating the determining whether the second vehicle is the articulated vehicle responsive to the second vehicle meeting or exceeding a threshold length; responsive to the second vehicle being the articulated vehicle, locating a hinge point on or between the first section and the second section of the articulated vehicle; and responsive to locating the hinge point, setting the first bounding box and the second bounding box to be non-overlapping.

Example 10. The system of example 9, wherein the at least one processor is further configured to track the second vehicle by: locating the hinge point responsive to the articulated vehicle driving on a curved road or taking a turn; and determining an articulation angle between the first bounding box and the second bounding box, wherein the articulation angle is greater than zero degrees.

Example 11. The system of example 10, wherein the at least one processor is further configured to: track the second vehicle further by: determining a first length and a first width associated with the first bounding box; determining a second length and a second width associated with the second bounding; and estimating a closest edge, to the first vehicle, of the articulated vehicle by using: the hinge point; the articulation angle; the first length and the first width; and the second length and the second width; and perform the driving maneuver by avoiding driving unsafely close to or colliding with the articulated vehicle.

Example 12. The system of example 11, wherein the at least one processor is further configured to: perform the driving maneuver further by avoiding the edge of the second vehicle.

Example 13. The system of example 8, wherein the field of view comprises: a 360-degree field of view; one or more overlapping or non-overlapping 180-degree fields of view; one or more overlapping or non-overlapping 120-degree fields of view; or one or more overlapping or non-overlapping 90-degree fields of view.

Example 14. The system of example 8, wherein the at least one processor is further configured to: update, based on an accuracy improvement function, the first bounding box and the second bounding box; determine, based on an updated first velocity associated with the first bounding box and an updated second velocity associated with the updated second bounding box, whether the second vehicle is an articulated vehicle; and responsive to determining whether the second vehicle is an articulated vehicle based on the updated first velocity and the updated second velocity, further perform the driving maneuver based on whether the second vehicle is an articulated vehicle, separately or concurrently tracking, in the field of view, at least one of the first bounding box or the second bounding box.

Example 15. A computer-readable storage medium comprising instructions that, when executed, cause at least one processor of a first vehicle to: track a second vehicle driving in a field of view of a radar system of the first vehicle by at least: generating a first bounding box associated with a first section of the second vehicle and a second bounding box associated with a second section of the second vehicle; and determining, based on a first velocity vector associated with the first bounding box and a second velocity vector associated with the second bounding box, whether the second vehicle is an articulated vehicle; and responsive to determining that the second vehicle is the articulated vehicle, perform a driving maneuver by separately and concurrently tracking, in the field of view, the first bounding box and the second bounding box.

Example 16. The computer-readable storage medium of example 15, wherein the instructions, when executed, further cause the at least one processor to track the second vehicle by at least: initiating the determining whether the second vehicle is the articulated vehicle responsive to the second vehicle meeting or exceeding a threshold length; responsive to the second vehicle being the articulated vehicle, locating a hinge point on or between the first section and the second section of the articulated vehicle; and responsive to locating the hinge point, setting the first bounding box and the second bounding box to be non-overlapping.

Example 17. The computer-readable storage medium of example 16, wherein the instructions, when executed, further cause the at least one processor to track the second vehicle by at least: locating the hinge point responsive to the articulated vehicle driving on a curved road or taking a turn; and determining an articulation angle between the first bounding box and the second bounding box, wherein the articulation angle is greater than zero degrees.

Example 18. The computer-readable storage medium of example 17, wherein the instructions, when executed, further cause the at least one processor to track the second vehicle by at least: determining a first length and a first width of the first bounding box; determining a second length and a second width of the second bounding; and estimating a closest edge, to the first vehicle, of the articulated vehicle by using: the hinge point; the articulation angle; the first length and the first width; and the second length and the second width; and further cause the at least one processor to perform the driving maneuver by avoiding driving unsafely close to or colliding with the articulated vehicle.

Example 19. The computer-readable storage medium of example 18, wherein the instructions, when executed, further cause the at least one processor to perform the driving maneuver by at least: performing the driving maneuver by avoiding the edge of the second vehicle.

Example 20. The computer-readable storage medium of example 15, wherein the instructions, when executed, further cause the at least one processor to track the second vehicle by at least: updating, based on an accuracy improvement function, the first bounding box and the second bounding box; determining, based on an updated first velocity associated with the first bounding box and an updated second velocity associated with the updated second bounding box, whether the second vehicle is an articulated vehicle; and responsive to determining whether the second vehicle is an articulated vehicle based on the updated first velocity and the updated second velocity, performing the driving maneuver further based on whether the second vehicle is an articulated vehicle by separately or concurrently tracking, in the field of view, at least one of the first bounding box and the second bounding box.

CONCLUSION

While various embodiments of the disclosure are described in the foregoing description and shown in the drawings, it is to be understood that this disclosure is not limited thereto but may be variously embodied to practice within the scope of the following claims. From the foregoing description, it will be apparent that various changes may be made without departing from the scope of the disclosure as defined by the following claims. In addition to radar systems, problems associated with bistatic conditions can occur in other systems (e.g., image systems, lidar systems, ultrasonic systems) that identify and process tracks from a variety of sensors. Therefore, although described as a way to improve radar detections of static objects, the techniques of the foregoing description can be applied to other problems to effectively detect bistatic conditions and take appropriate action.

The use of “or” and grammatically related terms indicates non-exclusive alternatives without limitation unless the context clearly dictates otherwise. As used herein, a phrase referring to “at least one of” a list of items refers to any combination of those items, including single members. As an 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 with multiples 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).