Patent Description:
Radar systems can enable a vehicle to detect stationary and non-stationary objects at different ranges. Improved performance is provided by radar over other sensors used by vehicles for autonomous driving or other driving-safety or driving-assistance functions; a radar-equipped vehicle can detect and track objects under many driving conditions, including low light, rain, snow, and fog. Still, under certain conditions, some radar systems may report false detections or fail to detect an object altogether. Inaccurate radar detections may be reported in situations where a radar system struggles to differentiate between multiple objects (e.g., two vehicles traveling in close proximity) or an articulated object (e.g., a truck towing a trailer or a multi-section bus). Consequently, operator intervention and/or compromised driving safety may result.

<CIT> discloses techniques for identifying and tracking specific vehicles based on vehicle radar data that are well suited for platooning, convoying and other autonomous or semi-autonomous driving applications.

This document describes techniques and systems related to tracking different sections of articulated vehicles. The present disclosure provides a method, a system and a computer-readable storage medium according to the independent claims. Embodiments are given in the subclaims, the description and the drawings.

According to an embodiment, a radar system for installation on a first vehicle includes at least one processor. The at least one processor is configured to track a second vehicle driving in a field of view of the radar system. The at least one processor is 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. The at least one processor is further configured to, 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.

This document also describes methods performed by the above-summarized techniques and components and other configurations of the radar system set forth herein, as well as means for performing these methods.

The details of one or more aspects for tracking different sections of articulated vehicles are described in this document with reference to the following figures. The same numbers are used throughout the drawings to reference like features and components:.

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.

<FIG> illustrates an example environment <NUM> in which a vehicle with a radar system is configured to track different sections of an articulated vehicle, in accordance with this disclosure. The environment <NUM> includes a vehicle <NUM> equipped with a radar system <NUM> configured to track different sections of articulated vehicles, in accordance with techniques, apparatuses, and systems of this disclosure. An output from the radar system <NUM> may enable operations of the vehicle <NUM>. An object's range, angle of approach, or velocity may be determined by the radar system <NUM> or derivable from the output, which takes the form of radar data.

Although illustrated as a car, the vehicle <NUM> can 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 vehicle <NUM> represents any moving platform, including moving machinery or robotic equipment, that can benefit from having a radar representation of the environment <NUM>.

Detected in a field of view of the radar system <NUM> are multiple moving objects <NUM>, <NUM>, and <NUM> (also sometimes referred to as "targets of interest"). The moving objects <NUM> and <NUM> are referred to as unarticulated vehicles <NUM> and <NUM>. In contrast, the object <NUM> is referred to as an articulated vehicle <NUM>, which includes at least two discernible sections connected by a hinge. In general, the objects <NUM>, <NUM>, and <NUM> are 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 objects <NUM>, <NUM>, and <NUM> can 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 system <NUM> is configured for installation as part of the vehicle <NUM>. In the depicted environment <NUM>, the radar system <NUM> is mounted near, or integrated within, a front portion of the vehicle <NUM> to detect the objects and avoid collisions. The radar system <NUM> can be a mechanic-replaceable component, part, or system of the vehicle <NUM>, which, due to a failure, may need to be replaced or repaired over the life of the vehicle <NUM>. The radar system <NUM> can include an interface to at least one automotive system. The radar system <NUM> can output, via the interface, a signal based on electromagnetic energy received by the radar system <NUM>. The output signal from the radar system <NUM> represents radar data and can take many forms.

At least one automotive system of the vehicle <NUM> relies on the radar data that is output from the radar system <NUM>. 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 system <NUM> can include a fusion tracker that combines sensor data from a variety of perception sensors, including the radar system <NUM>, to generate a multi-sensor representation of the environment <NUM>. 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 vehicle <NUM> may use radar data provided by the radar system <NUM> to perform a function, also referred to as a vehicle operation. In the environment <NUM>, the radar system <NUM> can detect and track the multiple moving objects <NUM>, <NUM>, and <NUM> by 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 object <NUM> detected by the radar system <NUM>. To do so, the radar system <NUM> can transmit electromagnetic signals between <NUM> and <NUM> gigahertz (GHz), between <NUM> and <NUM>, or between approximately <NUM> and <NUM>. The radar system <NUM> includes a transmitter (not illustrated) and at least one antenna element to transmit electromagnetic signals. The radar system <NUM> includes 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 system <NUM> may track the objects <NUM>, <NUM>, and <NUM> as they appear to be driving in a field of view. For example, as the radar system <NUM> increasingly detects a higher count of radar detections, the radar system <NUM> can detect and track one or more clusters of radar detections, such as at a rear, a middle, and/or a front of the articulated vehicle <NUM>. Without necessarily determining whether the articulated vehicle <NUM> is articulated, the radar system <NUM> can at least determine whether the various clusters of radar detections off the object <NUM> represent a same vehicle or object.

The radar system <NUM> can create a bounding box <NUM> for the entire object <NUM>. In furtherance of drawing the bounding box <NUM>, the radar system <NUM> can determine whether these various clusters of radar detections are stationary or non-stationary; whether the clusters of radar detections associated with the objects <NUM> move with approximately a same or a different velocity (speed and direction); and whether a range (distance) between each cluster of the object <NUM> is changing or is nearly constant. Similarly, the radar system <NUM> can create a bounding box <NUM> for the object <NUM> and a bounding box <NUM> for the object <NUM>. In continuing the example with driver-assistance system receiving radar data from the radar system <NUM>, the radar data may indicate to the driver-assistance system dimensions of the bounding boxes <NUM>, <NUM>, and <NUM>, that the driver-assistance system may use to determine positions of the objects <NUM>, <NUM>, and <NUM>, e.g., for determining when it is safe or unsafe to change lanes. Based on the radar data being output from the radar system <NUM>, an autonomous-driving system may move the vehicle <NUM> to a particular location on the road while avoiding collisions with the objects <NUM>, <NUM>, and <NUM>.

<FIG> illustrates another example environment <NUM>-<NUM> in which a vehicle with a radar system is configured to track different sections of an articulated vehicle, in accordance with this disclosure. The environment <NUM>-<NUM> is an example of the environment <NUM>, in which the vehicle <NUM> overtakes or drives adjacent to the articulated vehicle <NUM> when both vehicles <NUM> and <NUM> are driving on a turn.

When approaching the articulated vehicle <NUM>, the radar data output from the radar system <NUM> may enable the autonomous-driving system of the vehicle <NUM> to 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 vehicle <NUM> relative to safety margins the vehicle <NUM> uses for driving through traffic.

Other radar systems may track the articulated vehicle <NUM> with only the single bounding box <NUM>, as shown in both <FIG> and <FIG>. 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 in <FIG>, the bounding box <NUM> is inaccurately reporting the position of the articulated vehicle <NUM> so that the articulated vehicle <NUM> appears to be crossing into a travel lane of the vehicle <NUM>. The vehicle <NUM>, if equipped with a radar system that is not configured in accordance with the techniques of this disclosure, may falsely determine that the articulated vehicle <NUM> is 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 system <NUM> is configured to determine whether an object being tracked is articulated. The radar system <NUM> can 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 system <NUM> can generate a bounding box <NUM>-<NUM> at the front of the articulated vehicle <NUM> and further generate a bounding box <NUM>-<NUM> near the rear of the articulated vehicle <NUM>. As will become clear below, the radar system <NUM> can track an estimated hinge point between the front and rear sections of the articulated vehicle <NUM> and maintain resemblance of actual movement of the articulated vehicle <NUM> in repositioning and rotating the bounding boxes <NUM>-<NUM> and <NUM>-<NUM> about the estimated hinge point.

By individually tracking multiple sections of the articulated vehicle <NUM> using at least two bounding boxes <NUM>-<NUM> and <NUM>-<NUM> instead of only generating the bounding box <NUM>, the radar system <NUM> enables the vehicle <NUM> to drive safely past, or adjacent to, the articulated vehicle <NUM> with a fluid driving maneuver that is free of hesitation or jerkiness. The radar system <NUM> does not misrepresent the detections in a course manner using only the bounding box <NUM>. This way, when the articulated vehicle <NUM> is detected by the radar system <NUM>, 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 vehicle <NUM> appear in real life. This enables the vehicle <NUM> to 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 vehicle <NUM> in a similar scenario but under manual control.

To enable tracking of articulated sections, the radar system may initially represent the object <NUM> using the bounding box <NUM>. With most articulated vehicles being longer than a standard passenger vehicle, the radar system <NUM> can apply a vehicle length-based criterion to the bounding box <NUM> before expending computing resources to determine whether the object <NUM> being 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 system <NUM>.

The radar system <NUM> may utilize a threshold length (e.g., greater than <NUM> meters), which, when compared to dimensions of the bounding box <NUM>, can be used as an indicator to classify the object <NUM> as 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 system <NUM> may compare a length of the bounding box <NUM> to the length threshold to determine whether the object <NUM> has a potential for being articulated, even if (as is illustrated in <FIG>) 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 system <NUM> prior 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 system <NUM> may 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 system <NUM> derives 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 vehicle <NUM>, can make sharper turns (without encroaching on an adjacent lane or shoulder) than an unarticulated vehicle, such as the unarticulated vehicle <NUM>, which is of comparable length. The use of a hinge and articulation configuration is not necessary for a standard-length vehicle, such as the object <NUM>, but more often applies to vehicles that are longer than the standard length. Hence, the radar system <NUM>, responsive to determining that the object <NUM> is not of sufficient length, can refrain from determining whether the object <NUM> is articulated or unarticulated and default to tracking the object <NUM> as 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 system <NUM> may initially consider the articulated vehicle <NUM> and the unarticulated vehicle <NUM> to both be possible articulated vehicles until the radar system <NUM> can 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 vehicle <NUM> can 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 vehicle <NUM> to follow a curve more closely than an unarticulated vehicle, such as the unarticulated vehicle <NUM>. In practice, this means that a front section of the articulated vehicle <NUM> will have a grouping of radar detections that have a velocity <NUM>-<NUM> that is different than a velocity <NUM>-<NUM> of a group of radar detections captured at a tail section of the articulated vehicle <NUM>. Whereas the group of detections at the front of the unarticulated vehicle <NUM> will appear in the radar data to have a somewhat consistent velocity with the group of detections at the tail of the unarticulated vehicle <NUM>.

<FIG> illustrates an example vehicle <NUM>-<NUM>, including a radar system <NUM>-<NUM> configured to track different sections of an articulated vehicle, in accordance with this disclosure. The radar system <NUM> is an example of the radar system <NUM>. The vehicle <NUM>-<NUM> is an example of the vehicle <NUM>.

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

The vehicle <NUM>-<NUM> also includes a vehicle-based system <NUM>, such as a driver-assistance system <NUM> and/or an autonomous-driving system <NUM>. The vehicle-based system <NUM> uses radar data from the radar system <NUM>-<NUM> to perform a function. For example, the driver-assistance system <NUM> tracks articulated (e.g., the object <NUM>) and/or unarticulated vehicles (e.g., the objects <NUM> and <NUM>), monitors their proximity to the vehicle <NUM>-<NUM> and generates an alert that indicates a potential collision or an unsafe distance to the vehicles driving alongside the vehicle <NUM>-<NUM>. 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 system <NUM>-<NUM> indicate whether the vehicle <NUM>-<NUM> may safely drive alongside the other vehicles in the field of view.

As another example, on a windy road, the driver-assistance system <NUM> suppresses false alerts responsive to radar data indicating that an articulated vehicle (e.g., the object <NUM>) driving on an adjacent lane is veering into a travel lane of the vehicle <NUM>-<NUM>. In this way, the driver-assistance system <NUM> can avoid falsely alerting a driver of the vehicle <NUM>-<NUM> that the articulated vehicle is driving unsafely close or colliding with the vehicle <NUM>-<NUM>. By suppressing these false alerts, the driver-assistance system <NUM> avoids confusing or unnecessarily worrying the driver of the vehicle <NUM>-<NUM>.

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

The radar system <NUM>-<NUM> includes a communication interface <NUM> to transmit the radar data to the vehicle-based system <NUM> or another component of the vehicle <NUM>-<NUM> over a communication bus of the vehicle <NUM>-<NUM>. In general, the radar data provided by the communication interface <NUM> is in a format usable by the object detection and tracking system <NUM>. In some implementations, the communication interface <NUM> may provide information to the radar system <NUM>-<NUM>, such as the speed of the vehicle <NUM>-<NUM> or whether a turning blinker is on or off. The radar system <NUM>-<NUM> can use this information to appropriately configure itself. For example, the radar system <NUM>-<NUM> can determine if a selected object (e.g., <NUM>) is stationary by comparing a Doppler for the selected object to the speed of the vehicle <NUM>-<NUM>. Alternatively, the radar system <NUM>-<NUM> can 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 system <NUM>-<NUM> also includes at least one antenna array <NUM> and at least one transceiver <NUM> to transmit and receive radar signals. The antenna array <NUM> includes at least one transmit antenna element and a plurality of receive antenna elements separated in azimuth and elevation directions. In some situations, the antenna array <NUM> also 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 array <NUM>, the radar system <NUM> can 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 system <NUM>-<NUM> can 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 transceiver <NUM> includes circuitry and logic for transmitting and receiving radar signals via the antenna array <NUM>. Components of the transceiver <NUM> can include amplifiers, mixers, switches, analog-to-digital converters, or filters for conditioning the radar signals. The transceiver <NUM> also 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 transceiver <NUM> can be configured to support continuous-wave or pulsed radar operations. A frequency spectrum (e.g., range of frequencies) that the transceiver <NUM> uses 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 system <NUM>-<NUM> also includes one or more processors <NUM>. The processor <NUM> can 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 processor <NUM> is illustrated as being part of the radar system <NUM>-<NUM>, the processor <NUM> can be part of the object detection and tracking system <NUM> and may support the lidar system <NUM> and the imaging system <NUM>, in addition to the radar system <NUM>-<NUM>.

The object detection and tracking system <NUM> that includes the radar system <NUM>-<NUM> also includes one or more computer readable media (CRM) <NUM> (e.g., a computer-readable storage medium), and the CRM <NUM> excludes propagating signals. The CRM <NUM> may include various data-storage media, such as volatile memory (e.g., dynamic random-access memory, DRAM), nonvolatile memory (e.g., Flash), optical media, magnetic media, and so forth. The CRM <NUM> may include instructions (e.g., code, algorithms) that may be executed using the processor <NUM>. The instructions (not illustrated) stored in the CRM <NUM>, in part, interpret, manipulate, and/or use sensor data <NUM> that may also be stored in the CRM <NUM>. The sensor data <NUM> includes the radar data (e.g., clutters of radar detections, clusters of radar detections, and/or clouds of radar detections) of the radar system <NUM>-<NUM>. The sensor data <NUM> may also include lidar data of the lidar system <NUM> and imaging data (e.g., video, still frames) of the imaging system <NUM>. In one aspect, the instructions stored in the CRM <NUM> include a vehicle tracker <NUM> and an articulated vehicle tracker <NUM>.

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

The articulated vehicle tracker <NUM> helps determine whether a vehicle is articulated or unarticulated. If the articulated vehicle tracker <NUM> determines that a vehicle is articulated, the articulated vehicle tracker <NUM> then 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 tracker <NUM>, the radar system <NUM>-<NUM> of the vehicle <NUM>-<NUM> can track separately and concurrently the first and the second sections of the articulated vehicle. The articulated vehicle tracker <NUM> can 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 tracker <NUM> enables the radar system <NUM> to track separately and concurrently the first and the second bounding boxes of the suspected articulated vehicle.

The radar system <NUM>-<NUM> may use the vehicle tracker <NUM> and the articulated vehicle tracker <NUM> concurrently. The articulated vehicle tracker <NUM> may also use the lidar system <NUM> to estimate a closest edge to the vehicle <NUM>-<NUM> of the articulated vehicle. Before describing the articulation determination in detail, next, <FIG> describes 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 system <NUM>-<NUM>.

<FIG> illustrates an example environment <NUM> showing some drawbacks of using a conventional radar system, which is not configured to track different sections of an articulated vehicle. The environment <NUM> includes a portion of a road that turns to the right. A tractor-trailer vehicle <NUM>, which is an articulated vehicle, drives alongside a vehicle <NUM> that is equipped with a traditional radar system that is unable to discern whether articulation exists with a target. Unlike the vehicle <NUM>-<NUM>, the vehicle <NUM> uses a radar system <NUM> without the aid of the articulated vehicle tracker <NUM>. The existing radar system <NUM> fails to determine that the tractor-trailer vehicle <NUM> is an articulated vehicle. Instead, the existing radar system <NUM> may detect and track the tractor-trailer vehicle <NUM> as being non-articulated. This may be a reasonable approach if the vehicle <NUM> and the tractor-trailer vehicle <NUM> always 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 in <FIG>.

In one aspect, the radar system <NUM> may detect one or more clusters of radar detections at a rear, a front, and anywhere in-between the tractor-trailer vehicle <NUM>. The radar system <NUM> may then determine that all the radar detections are associated with a single vehicle, in <FIG>, the tractor-trailer vehicle <NUM>. The radar system <NUM> can then create a single bounding box <NUM> for the whole tractor-trailer vehicle <NUM>. As is illustrated in <FIG>, by not using the articulated vehicle tracker <NUM>, the tracked velocity vector <NUM>-<NUM> is inconsistent with a velocity vector <NUM>-<NUM> of the tractor-trailer vehicle <NUM>. More importantly, the bounding box <NUM> fails to accurately represent where the tractor-trailer vehicle <NUM> is located on the road, relative to a position of the vehicle <NUM>. Instead, as both vehicles <NUM> and <NUM> may make a right turn, the bounding box <NUM> appears to encroach closer to the vehicle <NUM> within an unsafe separation distance. Consequently, by using the radar system <NUM>, a driving system (e.g., an autonomous-driving system) of the vehicle <NUM> may overcorrect motion of the vehicle <NUM> and cause the vehicle <NUM> to 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.

<FIG> illustrate example environments <NUM>-<NUM> and <NUM>-<NUM>, 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 environments <NUM>-<NUM> and <NUM>-<NUM> are described in the context of <FIG> and <FIG>. Each of the environments <NUM>-<NUM> and <NUM>-<NUM> includes a vehicle <NUM>-<NUM>, which is an example of the vehicles <NUM> and <NUM>-<NUM>. Driving in an adjacent lane to the vehicle <NUM>-<NUM> is a semi-tractor trailer <NUM>-<NUM>, which is an example of the objects <NUM>-<NUM> and <NUM>.

Focusing first on <FIG>, in response to the radar system <NUM>-<NUM> identifying the semi-tractor trailer <NUM>-<NUM> as a long vehicle, the vehicle tracker <NUM> invokes the articulated vehicle tracker <NUM> for further processing of the radar data produced by the radar system <NUM>-<NUM> to determine whether an object being tracked by the vehicle tracker <NUM> is articulated.

Independent of how the vehicle tracker <NUM> treats the semi-tractor trailer <NUM>-<NUM>, the articulated vehicle tracker <NUM> begins tracking a suspected articulated vehicle by locating a hinge point between two sections of the suspected articulated vehicle. For example, the articulated vehicle tracker <NUM> can 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 point <NUM>-<NUM> can be determined to be at an intersection between a velocity vector <NUM>-<NUM> of the back section and a velocity vector <NUM>-<NUM> of the front section. The articulated vehicle tracker <NUM> can generate a first bounding box <NUM>-<NUM> around the back section and a second bounding box <NUM>-<NUM> around the front section. The articulated vehicle tracker <NUM> determines the hinge point <NUM>-<NUM> to be between the first and second bounding boxes <NUM>-<NUM> and <NUM>-<NUM>, such that they are not overlapping. In this situation, the articulation angle <NUM>-<NUM> between the first bounding box <NUM>-<NUM> and the second bounding box <NUM>-<NUM> is approximately zero degrees. When the articulation angle <NUM>-<NUM> is near zero, the hinge point <NUM>-<NUM> determination can be difficult to resolve.

Switching to <FIG>, the articulated vehicle tracker <NUM> may wait until the vehicle <NUM>-<NUM> and the semi-tractor trailer <NUM>-<NUM> are driving on a curved road or taking a turn before establishing a hinge point <NUM>-<NUM>. In this situation, the articulation angle <NUM>-<NUM> between the first bounding box <NUM>-<NUM> and the second bounding box <NUM>-<NUM> is greater than zero degrees. The articulated vehicle tracker <NUM> can extrapolate the velocity vector <NUM>-<NUM> and the velocity vector <NUM>-<NUM> to find the intersection at which the hinge point <NUM>-<NUM> estimation is made.

Upon extrapolating out to the hinge point <NUM>-<NUM>, the articulated vehicle tracker <NUM> can regularly update its calculations to improve its track on the semi-tractor trailer <NUM>-<NUM>. For example, as a turn becomes increasingly sharper, the articulated vehicle tracker <NUM> may identify an increasing difference in the velocity vectors <NUM>-<NUM> and <NUM>-<NUM>. This increase in the articulation angle <NUM>-<NUM> provides an increased accuracy in the hinge point <NUM>-<NUM>. Depending on the capability of the radar system <NUM>-<NUM>, the hinge point <NUM>-<NUM> may become valid for subsequent use in controlling the vehicle <NUM>-<NUM> in response to a degree of certainty in the calculation being achieved. The articulated vehicle tracker <NUM> may output a degree of certainty or confidence associated with its radar data calculations, including the hinge point <NUM>-<NUM>. When the articulation angle <NUM>-<NUM> is near zero degrees, this degree of certainty may be low, whereas when the articulation angle <NUM>-<NUM> deviates from zero degrees, the confidence in the hinge point <NUM>-<NUM> is increasing.

Based on the estimated hinge point <NUM>-<NUM> and the articulation angle <NUM>-<NUM>, the articulated vehicle tracker <NUM> determines, based further on an estimated width of the object <NUM>-<NUM> being tracked, positions and orientations of one or more side edges <NUM> of the articulated vehicle being tracked. A width <NUM> of the object <NUM>-<NUM> being tracked corresponds to the estimated width of either of the bounding boxes <NUM>-<NUM> and <NUM>-<NUM>. The width <NUM> of the object <NUM>-<NUM>, the hinge point <NUM>-<NUM>, and the articulation angle <NUM>-<NUM> are used by the articulated vehicle tracker <NUM> to estimate the locations of the side edges <NUM> of 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 edges <NUM>. Low-pass filtering may be used to reduce noise on these estimates. Long-term understanding of the hinge point <NUM>-<NUM> and the articulation angle <NUM>-<NUM> as determined over time can be used as feedback information to help reduce noise levels and improve accuracy of the bounding boxes <NUM>-<NUM> and <NUM>-<NUM>, which are now linked to movement of individual articulated sections. The articulated vehicle tracker <NUM> may output a position of the edge <NUM> of the semi-tractor trailer <NUM>-<NUM> that is closest to the vehicle <NUM> as an indication of a safety buffer zone.

The articulated vehicle tracker <NUM> may determine the width <NUM> of the first bounding box <NUM>-<NUM> in addition to determining the width <NUM> of the second bounding box <NUM>-<NUM>, from which an overall width <NUM> of the semi-tractor trailer <NUM>-<NUM> is estimated (e.g., by averaging, by taking a greater of). To estimate the closest edge <NUM> of the semi-tractor trailer <NUM>-<NUM>, the articulated vehicle tracker <NUM> uses the hinge point <NUM>-<NUM>, the articulation angle <NUM>-<NUM>, and the width <NUM> to estimate a portion of the edge <NUM> between two articulated sections. By providing a highly accurate representation of the semi-tractor trailer <NUM>-<NUM>, as it turns, the articulated vehicle tracker <NUM> enables the vehicle <NUM>-<NUM> to be able to safely drive adjacent to the semi-tractor trailer <NUM>-<NUM>, without any false pre-collision warnings that might otherwise happen if the semi-tractor trailer <NUM>-<NUM> were tracked with just one bounding box, instead of the two bounding boxes <NUM>-<NUM> and <NUM>-<NUM>.

<FIG> illustrates a process <NUM> for tracking different sections of an articulated vehicle, in accordance with this disclosure. The process <NUM> is 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 process <NUM> is not limited to performance by one entity or multiple entities.

At <NUM>, a vehicle driving in a field of view of a radar system is tracked using a single bounding box. For example, the radar system <NUM> can track the object <NUM> in a field of view using the bounding box <NUM>.

At <NUM>, whether the vehicle is a long vehicle is determined. For example, the radar system <NUM> compares a length of the bounding box <NUM> to a length threshold. If this length is less than the threshold, the NO branch from <NUM> is taken, and the object <NUM> is tracked with the bounding box <NUM> alone. However, in response to determining that the object <NUM> is a long vehicle based on the length exceeding the length threshold, the YES branch from <NUM> is taken. This point in the process <NUM> coincides with the vehicle tracker <NUM> invoking the articulated vehicle tracker <NUM>, which may represent two parallel tracking schemes until the radar system <NUM> is confident that the object <NUM> can be tracked with only one bounding box or if multiple bounding boxes should be used, in the case of articulation.

At <NUM>, 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 system <NUM> may generate bounding boxes <NUM>-<NUM> and <NUM>-<NUM>.

At <NUM>, a velocity vector determined for each of the two bounding boxes generated for the front and rear sections is determined. For example, the bounding boxes <NUM>-<NUM> and <NUM>-<NUM> are characterized by the velocity vector <NUM>-<NUM> and the velocity vector <NUM>-<NUM>.

At <NUM>, whether the vehicle is articulated is determined. For example, the velocity vectors <NUM>-<NUM> and <NUM>-<NUM> are monitored. A hinge point can be determined by estimating an intersection between the two velocity vectors <NUM>-<NUM> and <NUM>-<NUM>, particularly when the object <NUM> is 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 from <NUM> is 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 from <NUM> is taken and the vehicle is determined to be articulated.

At <NUM>, 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 boxes <NUM>-<NUM> and <NUM>-<NUM> may replace the bounding box <NUM>. In other examples, the bounding box <NUM> may be generated in addition to the two bounding boxes <NUM>-<NUM> and <NUM>-<NUM>, with the bounding box <NUM> being designated as a less accurate solution for the object <NUM>.

At <NUM>, a driving maneuver is performed based on the two bounding boxes generated for the front and rear sections. For example, the radar system <NUM> outputs to an autonomous driving system an indication of the two bounding boxes <NUM>-<NUM> and <NUM>-<NUM>. With an estimated nearest edge of the object <NUM> determined from dimensions of the bounding boxes <NUM>-<NUM> and <NUM>-<NUM>, the vehicle <NUM> can drive safely adjacent or otherwise near the object <NUM> without receiving false alarms or false reporting of potential collision situations.

As another example, consider the radar system <NUM> tracking the object <NUM> using the bounding box <NUM>. In this example, the object <NUM> is a school bus and, therefore, unarticulated.

For example, at <NUM>, the radar system <NUM> compares a length of the bounding box <NUM> to a length threshold. If this length is less than the threshold, the NO branch from <NUM> is taken and the object <NUM> is tracked with the bounding box <NUM> alone. However, in response to determining that the object <NUM> is a long vehicle based on the length exceeding the length threshold, the YES branch from <NUM> is taken.

At <NUM>, the radar system <NUM> produces a bounding box for a front section of the object <NUM>, and another bounding box for a rear section of the object <NUM> is determined.

At <NUM>, a velocity vector determined for each of the two bounding boxes generated for the front and rear sections of the object <NUM> is evaluated to determine, at <NUM>, whether the object <NUM> is articulated. For instance, a hinge point can be determined by estimating an intersection between two velocity vectors, particularly when the object <NUM> travels 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 from <NUM> is taken and the object <NUM> is determined to be unarticulated. The unarticulated vehicle is tracked using just the single bounding box <NUM>. A driving maneuver can be performed using an edge of the bounding box <NUM> to keep the vehicle <NUM> out of the path of the object <NUM>, particularly when in an adjacent lane during a turn.

<FIG> and <FIG> illustrate 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> includes an environment <NUM> in which a velocity vector <NUM> of a steerable portion of a tractor-trailer vehicle is reported by the radar system <NUM>. Also represented in <FIG> is a direction <NUM> (angular orientation) of a longitudinal axis of the steerable portion of a tractor-trailer vehicle. The steerable portion is connected at a hinge point <NUM> to a trailer portion; the two portions of the tractor-trailer are meant to pivot at the hinge point <NUM> to affect an articulation angle <NUM> that is computed between them. A consequence of assuming that the velocity vector <NUM> is parallel to the direction <NUM> of the longitudinal axis is that edge positions may appear in an incorrect location, and the hinge point <NUM> may be incorrect. An articulated vehicle tracker, such as the articulated vehicle tracker <NUM>, 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 point <NUM>. The direction <NUM> can be computed as a parallel line to a connecting line between a front position of a front bounding box, with the hinge point <NUM>.

For example, <FIG> depicts an example tractor-trailer dynamics model <NUM>. The hinge point <NUM> is 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 system <NUM> updates, based on an accuracy improvement function, the bounding box <NUM>-<NUM> and the bounding box <NUM>-<NUM>. By running track filters on the bounding boxes <NUM>-<NUM> and <NUM>-<NUM>, the radar system <NUM> outputs dimensions including COR from the position, velocity, and curvature information reported from the track filters. The radar system <NUM> can compute the line intersection of the COR lines to obtain a position of the hinge point <NUM>. The location of the hinge point <NUM> is 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 angle <NUM> is 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 system <NUM> can 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 point <NUM>. 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 point <NUM>. That said, a trailer's orientation may be unaffected by the outcome of the computation of the location of the hinge point <NUM>; only its length may be affected.

Claim 1:
A method, comprising:
obtaining, by a first vehicle (<NUM>), from a radar system (<NUM>) of the first vehicle (<NUM>), radar data including radar detections that reflect from objects (<NUM>, <NUM>, <NUM>) in the field of view of the radar system;
tracking, by the first vehicle (<NUM>), based on the radar data, a second vehicle driving in the field of view by:
determining a first section of the second vehicle and a second section of the second vehicle that is separate from the first section;
generating (<NUM>) a first bounding box (<NUM>-<NUM>) associated with the first section and a second bounding box (<NUM>-<NUM>) associated with the second section;
determining (<NUM>) a first velocity vector (<NUM>-<NUM>) for the first bounding box (<NUM>-<NUM>) and a second velocity vector (<NUM>-<NUM>) for the second bounding box (<NUM>-<NUM>);
determining a hinge point (<NUM>-<NUM>, <NUM>-<NUM>) between the first bounding box (<NUM>- <NUM>) and the second bounding box (<NUM>-<NUM>) by estimating an intersection between the first velocity vector (<NUM>-<NUM>) and the second velocity vector (<NUM>-<NUM>); and
determining (<NUM>) whether the second vehicle is an articulated vehicle (<NUM>) by determining if an articulation angle (<NUM>-<NUM>, <NUM>-<NUM>) between the first velocity vector (<NUM>-<NUM>) and the second velocity vector (<NUM>-<NUM>) at the hinge point (<NUM>) increases above zero degrees; and
responsive to determining that the second vehicle is an articulated vehicle (<NUM>), performing (<NUM>), by the first vehicle (<NUM>), a driving maneuver by separately and concurrently tracking, in the field of view, the first bounding box (<NUM>-<NUM>) and the second bounding box (<NUM>-<NUM>).