Characterization and tracking algorithm for multi-lane roads

Abstract

Embodiments relating to methods and systems for locating the position of a vehicle on the road surface are described. [Solution] Linked reference landmarks present on the road surface can be used to determine the location of a vehicle on the road surface and / or predict the vehicle's path along the road surface.

Description

Technical Field

[0001] Cross - reference to Related Applications

[0001] This application claims the benefit of U.S. Provisional Patent Application No. 62 / 930,525, filed on November 4, 2019, under 35 U.S.C. § 119(e). The disclosure of the same is incorporated herein by reference in its entirety.

[0002] Field

[0002] The disclosed embodiments relate to the characterization of multi - lane roads, tracking algorithms, and related systems.

Background Art

[0003] Background

[0003] For example, some types of advanced vehicle functions, including autonomous or semi - autonomous driving mechanisms (e.g., autonomous steering systems, active and semi - active suspension systems, etc.), may rely on systems and methods that have the ability to accurately, highly - resolve, and reproducibly localize a vehicle on a road surface.

Summary of the Invention

Means for Solving the Problems

[0004] Summary

[0004] In one embodiment, a method of identifying a vehicle's location includes sensing one or more parameters associated with a road surface of a road that the vehicle is passing over, identifying a first reference landmark on the road that the vehicle has encountered using the sensed one or more parameters, identifying a second reference landmark on the road that is linked to the first reference landmark, and predicting that the vehicle will pass through a portion of the road surface that extends between the first reference landmark and the second reference landmark.

[0005]

[0005] In one embodiment, a method for locating a vehicle includes sensing one or more parameters associated with the road surface of a road on which the vehicle is traveling; identifying a first reference landmark on the road encountered by the vehicle, at least in part based on the sensed one or more parameters; continuing to sense one or more parameters as the vehicle travels across the road surface; and determining the position of the vehicle on the road surface by comparing the one or more parameters only with information relating to the first reference landmark and the portion of the road surface extending inclusively between the first reference landmark and at least one reference landmark linked to the first reference landmark.

[0006]

[0006] In one embodiment, the vehicle includes one or more sensors configured to sense one or more parameters associated with the road surface of the road the vehicle is traveling on, and a processor operably coupled to one or more sensors. The processor may be configured to sense one or more parameters associated with the road surface as the vehicle travels along the road, to use the sensed one or more parameters to identify a first reference landmark on the road encountered by the vehicle, to identify a second reference landmark on the road linked to the first reference landmark, and to predict that the vehicle will pass over a portion of the road surface extending between the first reference landmark and the second reference landmark.

[0007]

[0007] In one embodiment, the vehicle includes one or more sensors configured to sense one or more parameters associated with the road surface of the road the vehicle is traveling on, and a processor operably coupled to one or more sensors. The processor may be configured to sense one or more parameters associated with the road surface of the road the vehicle is traveling on, identify a first reference landmark on the road encountered by the vehicle at least partially based on the sensed one or more parameters, continue to sense one or more parameters as the vehicle travels across the road surface, and determine the position of the vehicle on the road surface by comparing one or more parameters only with information relating to the first reference landmark and the portion of the road surface extending implicitly between the first reference landmark and at least one reference landmark linked to the first reference landmark.

[0008]

[0008] In one embodiment, a method for generating a road map includes determining whether each of a plurality of vehicles traveling on the road surface has encountered a plurality of reference landmarks, determining the route each vehicle takes to the plurality of reference landmarks, identifying the links between the plurality of reference landmarks, generating a mesh of the plurality of reference landmarks and the links extending between the plurality of reference landmarks, and storing the mesh in non-temporary processor-readable memory for future recall and / or use.

[0009]

[0009] The concepts described above, and the further concepts described below, should be understood to be in any preferred combination, as the Disclosure is not limited in this respect. Furthermore, other advantages and novel features of the Disclosure will become apparent from the following detailed description of various non-limiting embodiments when considered in relation to the attached drawings.

[0010]

[0010] If this Specification and two or more documents incorporated by reference contain conflicting and / or inconsistent disclosures, this Specification shall prevail. If the documents incorporated by reference contain conflicting and / or inconsistent disclosures with respect to each other, the document with the more recent effective date shall prevail.

[0011] Brief explanation of the drawing

[0011] The attached drawings are not intended to be drawn to actual size. In the drawings, identical or nearly identical components shown in various drawings may be represented by the same reference numerals. For clarity purposes, not all components may be marked in all drawings. [Brief explanation of the drawing]

[0012] [Figure 1]

[0012] Figure 1 is a schematic diagram of one embodiment of the vehicle. [Figure 2]

[0013] Figure 2 is a schematic diagram of one embodiment of a processor operably coupled to various exemplary systems in a vehicle. [Figure 3]

[0014] Figure 3 shows different possible common lanes that may be associated with travel along a road containing two parallel lanes, according to one embodiment. [Figure 4]

[0015] Figure 4 shows a schematic arrangement of different reference landmarks arranged along the length and width of the road surface according to one embodiment. [Figure 5]

[0016] Figure 5 shows an exemplary mesh of multiple linked reference landmarks associated with the road profile of a road surface, according to one embodiment. [Figure 6]

[0017] Figure 6 shows a schematic arrangement of different reference landmarks arranged along the length and width of the road surface according to one embodiment. [Figure 7]

[0018] Figure 7 is a schematic diagram of one embodiment of a method for generating a road map that includes a road profile having a mesh containing linked reference landmarks. [Figure 8]

[0019] Figure 8 is a schematic diagram of one embodiment of a method for determining the location of a vehicle using linked reference landmarks. [Modes for carrying out the invention]

[0013] Detailed explanation

[0020] As described above, certain vehicle systems may use location data related to the location of a vehicle on the road surface. However, the inventors have recognized that roads with multiple lanes (referred to herein as “multi-lane roads”) can present further problems for various location systems. For example, for multi-lane roads, it may be desirable to specify the location of a vehicle in two dimensions relative to the road surface. In one such example, it may be desirable to specify the position of a vehicle on the road surface both longitudinally (e.g., “300 feet from mile marker 4 on Interstate 85”) and laterally (e.g., “within the center lane of a three-lane road”). Conventional Global Navigation Satellite Systems (GNSS), such as GPS, are generally not precise enough to decompose specific lanes on multi-lane roads. In addition, the inventors recognized that while specialized differential GNSS sensors and / or advanced specialized camera systems could be used to more accurately pinpoint the position of a vehicle on the road surface, these systems increase the cost and complexity of the vehicle and further increase the possibility of failure due to environmental conditions (e.g., poor visibility due to weather or time of day). Recognizing this problem, the inventors recognized the advantages of various systems and methods for performing lane-specific location on multi-lane roads, particularly using road profile-based location systems. More specifically, the inventors recognized the advantages of using reference landmarks present on the road surface that can be used to pinpoint the location of a vehicle on the road surface. This can include not only longitudinal vehicle location along the length of the road, but also lateral vehicle location on the road surface, as detailed below. These systems and methods can provide improved accuracy, computational efficiency, and reliability compared to typical location systems used for vehicle location along the longitudinal and / or lateral dimensions of the road surface.

[0014]

[0021] While it may be desirable to determine the lateral position of a vehicle on the road surface, various conditions can complicate determining a vehicle's position. For example, when traveling along a multi-lane road, a driver may change lanes at various points for different reasons. Therefore, within a single journey on a multi-lane road, the actual path taken by a vehicle may include multiple lane divisions. That said, it is generally assumed that, at any given time, a driver is more likely to stay in their current lane than to change lanes. However, this assumption may not hold true in places where there may be specific reasons for many vehicles to change lanes at the same location (e.g., when traffic may be slower at a particular time, in the exit lane of a main road, or to avoid construction work).

[0015]

[0022] In addition to the above, there may be certain locations where drivers repeatedly take routes that do not precisely correspond to a given lane. For example, a driver may not properly negotiate a corner on a curve, causing them to stray from the lane markers associated with individual lanes. In these cases, the actual route taken by the vehicle may differ from the “lane” defined by the lane markers on the road. Therefore, it is useful to introduce the term “common lane.” As used herein, a common lane may refer to a route along a section of road that is commonly traversed by multiple vehicles, or by the same vehicle over multiple journeys. Since drivers can generally follow lane markings with minimal lane changes, in certain locations, the common lane of a section of road may overlap with the actual lanes. However, as described herein, in situations such as when a driver routinely fails to properly negotiate a curve (and thus crosses the lane markings), when a driver routinely changes their actual lane, for example, to exit a main road and / or to avoid a semi-permanent obstruction, and / or for other appropriate reasons, the common lane of a road section may differ from the actual lane (as defined by the lane markers). However, these variations in the paths a driver may take can complicate determining the vehicle's position.

[0016]

[0023] In view of the above, in one embodiment, it may be desirable to determine the location of a vehicle passing through a road surface. This may include sensing one or more parameters associated with the road surface through which the vehicle is passing. The one or more sensed parameters of the road surface may be used to identify a first reference landmark on the road surface encountered by the vehicle. After identifying the first reference landmark, the first reference landmark may be used to provide information related to a likely path of travel of the vehicle on the coming portion of the road surface. For example, barring the presence of some other event such as an off-ramp, an obstacle, or some other event associated with traveling along the road surface as described above, the vehicle will likely continue to be in the same travel lane. Accordingly, a road map including a plurality of linked reference landmarks may be used to determine one or more reference landmarks linked to the first reference landmark identified as being encountered by the vehicle. Therefore, by identifying one or more reference landmarks linked to the first reference landmark, it may be possible to predict that the vehicle will pass through a portion of the road surface extending between the first reference landmark and one or more subsequent reference landmarks linked to the first landmark. This may be done iteratively, whereby each reference landmark encountered by the vehicle is identified and associated with other linked reference landmarks as the vehicle progresses along the road surface.

[0017]

[0024] In some cases, it may be desirable to help reduce the computational resources associated with identifying the location of a vehicle on the portion of the road surface it is traveling on. In such embodiments, a first reference landmark encountered by the vehicle may be identified. Then, one or more reference landmarks linked to the first reference landmark may also be identified. However, as the vehicle moves between the linked reference landmarks, it may be desirable to limit the comparison of sensing parameters associated with the road surface to the portion of the road surface that extends between and includes the linked reference landmarks, rather than comparing this comparison to information associated with the entire road surface. For example, this could involve limiting the comparison to a specific common lane on a multi-lane road. This comparison of sensing parameters with a more limited portion of the road extending between the linked reference landmarks may continue as long as the comparison is not inconsistent with the vehicle still being located on the portion of the road extending between the reference landmarks, unless other sensed vehicle parameters indicate that the vehicle has left its current lane. However, if the comparison indicates that the vehicle is no longer on a selected portion of the road surface, and / or the sensed vehicle parameters indicate that the vehicle has left its lane, a coarser comparison of one or more sensed parameters of the road surface may be made more coarsely compared with a reference profile of the road surface to identify another reference landmark that can indicate the vehicle's position on the road surface, and then the process using the linked reference landmark may be resumed. Thus, the location algorithm may transition between a computationally intensive approximate location algorithm and a computationally intensive location algorithm in which linked reference landmarks may be used to narrow down the portion of the road surface reference profile used to pinpoint the vehicle's location on the road surface.

[0018]

[0025] The location identification method referred to in the above embodiments can be used to determine and / or predict the location of a vehicle in any desired combination of dimensions with respect to the road surface. For example, in one embodiment, the location identification module can be used to determine and / or predict the longitudinal position of the vehicle on the road surface. In another embodiment, the location identification module can be used to determine and / or predict the lateral position of the vehicle on the road surface. In yet another embodiment, the location identification module can be used to determine and / or predict the longitudinal and lateral positions of the vehicle together. Therefore, the methods and systems described herein can be considered to provide an improved method for location identification of a vehicle on a surface, and in some cases, more specifically, for roughly determining the lateral position of a vehicle on a road surface. As used herein, the longitudinal position of a vehicle on the road surface can refer to the position of the vehicle along the length of the road. Correspondingly, the lateral position of a vehicle on the road surface can refer to the position of the vehicle along the width of the road, which can correspond to the position of the vehicle with respect to a separate lane disposed across the width of the road.

[0019]

[0026] To facilitate the implementation of the location identification module described above, it may be desirable to provide a road map that includes linked reference landmarks positioned along a particular road surface. For example, in some embodiments, the road map may be generated based on aggregated information from multiple vehicles traveling along a particular road. This disclosure is not limited in this respect, and this information may be provided by a single vehicle traveling along a particular section of road multiple times, and / or by multiple vehicles traveling along the same section of road. In either case, the information obtained may be used to form a reference profile of the road surface, which can be analyzed to determine the presence of one or more reference landmarks on the road surface, as will be further detailed below. After identifying distinct reference landmarks, it may be determined whether each vehicle traveling along the road surface encounters various reference landmarks. In some embodiments, this may be done by comparing parameters associated with the road surface with the reference profile for each vehicle traveling along the road surface. The travel path of each vehicle to multiple reference landmarks may be determined, and links extending between the multiple reference landmarks may be identified. For example, a vehicle may have a travel path that extends along a route that includes a subset of multiple reference landmarks. The reference landmarks included along the travel path may then be linked to each other. This process is continued for each vehicle, and this information can be aggregated to generate a mesh of linked reference landmarks. The mesh may include multiple reference landmarks and links extending between them. To facilitate the use of the road map containing the mesh, the road map and associated mesh may be stored in non-temporary processor-readable memory for future recall and / or use, as further described herein.

[0020]

[0027] Due to the difficulties involved in sensing and responding in real time to road features present on the road surface while a vehicle is in motion, in some embodiments, it may be desirable to control one or more systems of the vehicle based on previously recorded information related to the road surface to improve response time, and / or to proactively control one or more systems based on previously recorded information related to the road surface. For example, as described above, it may be possible to determine the current location of the vehicle on the road surface using reference landmarks. In addition, one or more reference landmarks present in the upcoming portion of the road surface may be linked to reference landmarks previously encountered by the vehicle. Therefore, information such as a reference road profile, related to either the upcoming reference landmark and / or the portion of the road surface extending between the linked reference landmarks, may be used to control one or more systems of the vehicle without relying solely on real-time measurements to determine one or more operating parameters of these systems, as will be further described below. For example, to improve the operation of a vehicle system as it passes an upcoming section of the road surface, one or more operating parameters may be set before encountering a specific road feature on the road surface, and / or, one or more systems may be made to operate based on expected inputs to the vehicle from one or more road features located along a section of the road surface extending between linked reference landmarks, before sensing the road feature.

[0021]

[0028] Depending on the embodiment, road profile matching may be used to determine the location of a vehicle on the road surface using the various systems and methods described herein. As more fully described in International Application PCT / US2020 / 023610 (published as International Publication 2020 / 191188), U.S. Patent Application No. 16,130,311 (published as U.S. Patent Application Publication 2019 / 0079539), and U.S. Patent Application No. 16,672,004 (published as U.S. Patent Application Publication 2020 / 0139784), which are incorporated herein by reference in their entirety for all purposes, road profile generation and matching is a highly accurate localization method for determining the location of a vehicle on the road surface. An exemplary method of road profile-based location identification may, for example, first operate by collecting a reference road profile using sensors to sense one or more parameters associated with the road surface, such as force and / or motion inputs by the road surface into one or more parts of a vehicle, height variations of various parts of a vehicle relative to the road surface, optical sensors such as laser displacement sensors, laser velocity Doppler transducers (LVDTs), lidar sensors, radar sensors, and / or any other suitable input parameters. From the reference road profile, a number of distinctive features (e.g., a set of clearly distinguishable bumps and dips) may be identified, as referred herein to as reference landmarks. A suitable method for identifying these reference landmarks within the reference road profile may, for example, include comparing a subdivision of the road profile with all other subdivisions within a given region and identifying the one with the lowest correlation to the others (i.e., higher uniqueness). Each reference landmark may be associated with a specific absolute or relative location along the road surface. For example, this location on the road surface may include lateral and / or longitudinal positional information relative to the road surface. Data on these reference landmarks and associated locations can be stored within a reference road profile. Subsequently, when a vehicle travels over a given road surface where the reference road profile is available, a measurement road profile can be recorded corresponding to one or more parameters sensed by one or more sensors of the vehicle as the vehicle travels over the road surface.Next, this measurement road profile can be compared with a reference landmark stored in a reference road profile. When a “match” occurs, i.e., when a vehicle passes over a road feature located on the road surface that was previously identified as a reference landmark, the vehicle’s location can be determined using the known location of the reference landmark. In this case as well, international application PCT / US2020 / 023610 describes various exemplary systems and methods for identifying a reference landmark, generating and storing a reference road profile containing the reference landmark, comparing the measurement road profile with the reference road profile, and determining the vehicle’s location.

[0022]

[0029] Depending on the embodiment, each reference landmark may include lateral position information relative to the road surface (for example, a reference landmark may be lane-specific). For lane identification, each reference landmark may be sufficiently distinguishable not only longitudinally along a particular road but also laterally within the road. For example, a reference landmark may be, for example, a pothole, drainage grate, manhole cover, or other road feature present only within a particular lane and not in adjacent lanes. Since a vehicle passes through road features associated with a specific lateral position or lane, such landmarks can enable precise lateral location determination and make it relatively simple to determine the vehicle's current lateral position or lane of travel. Even more precise lateral location determination can be achieved by measuring a wheel-specific road profile. For example, if only the right wheel of an automobile passes through a reference landmark, then the lateral location of the vehicle's wheels within the road can be determined more precisely.

[0023]

[0030] It should be noted that road profiles can change over time (e.g., due to road repaving, the development of potholes in the road, etc.). However, changes in the road surface can make the identification and prediction of linked reference landmarks inaccurate, which presents a challenge when attempting to implement such location methods. Therefore, depending on the embodiment, the reference road profile and reference landmarks along the road surface can be updated over a given period of time. For example, a given vehicle may travel along the same road surface multiple times within a given period of time (e.g., a commuter or delivery van driver may travel along the same set of road surfaces multiple times a week). In addition, multiple vehicles may travel along the same road surface over a given period of time. Changes in the road profile can be captured as described herein by collecting road profile data as multiple vehicles travel along a given road surface one or more times (e.g., "crowdsourcing" from multiple vehicles), or by measuring the road profile each time a given vehicle travels along a given road surface. In addition, feature signals contained within road profiles associated with various reference landmarks can be updated using this aggregated data to change reference information associated with different reference landmarks, add new reference landmarks, and / or remove reference landmarks that no longer exist on the road surface. This information can then be used to update links between different reference landmarks present on the road surface, as will be further detailed below.

[0024]

[0031] In certain embodiments, each reference landmark within a reference road profile may be associated with a confidence level. A road profile may be measured each time a vehicle travels along a given road. In some embodiments, the confidence level associated with a given reference landmark may be increased when the measured road profile has features that match that landmark. Conversely, the confidence level associated with a given reference landmark may be decreased each time a subsequent measured road profile has features that do not match that landmark. In certain embodiments, if the confidence level associated with a given reference landmark falls below a threshold, it may be completely removed from the reference road profile. For example, if a reference road profile includes a reference landmark corresponding to a pothole or other road feature, but a sufficient number of vehicles traveling along the relevant road do not detect the reference landmark, then it may be assumed that the corresponding pothole or road feature no longer exists (e.g., the local government has repaired it). A sufficient number may be selected by the system designer, operator, or owner based on many factors, such as typical operating information related to a particular section of the road, including the average number of vehicles passing per day, the time between recent passes, or the average and typical speeds for a road section compared to the individual speeds of recent passes, as well as other considerations, such as weather conditions and, for example, the driver's behavior as inferred from steering and accelerator input signals. In such circumstances, if it is determined that a reference landmark no longer exists, it may be desirable to remove the corresponding reference landmark from the reference road profile.

[0025]

[0032] As described above, road profiles containing multiple reference landmarks can change over time. In addition to removing reference landmarks that no longer exist, it may also be desirable to add new reference landmarks to the road profile over time. For example, in certain embodiments, a measurement road profile may be added to the reference road profile of a given road in order to create an updated reference road profile. For example, if a particular measurement road profile deviates substantially from an existing reference road profile (i.e., if the road features in a particular measurement road profile do not correspond to the reference landmarks included in the reference road profile), then new reference landmarks may be identified within the measurement road profile. These new reference landmarks may be added to the reference road profile in order to create an updated road profile that encompasses both the previous and new reference landmarks.

[0026]

[0033] Depending on the embodiment, the reference profile may include a two-dimensional mesh of reference landmarks rather than simply a linear series of reference landmarks. For example, a reference road profile for a multi-lane road encompassing multiple potential parallel paths may include a mesh of landmarks where the mesh dimension corresponds to the number of lanes in the road. In certain cases, the mesh dimension may even exceed the number of lanes in the road, for example, because vehicles may be traveling on two different paths within the same physical lane (for example, when some vehicles are preparing to exit a main road and others remain in those lanes to continue moving).

[0027]

[0034] Road features can correspond to any feature on the road surface that, when used herein, can be sensed by one or more sensors or systems that can generate a force input to a part of the vehicle, or otherwise provide an input to the vehicle's localization module. While this disclosure is not limited to any particular type of road feature, suitable types of road features that can be considered using any of the methods and systems disclosed herein include, but are not limited to, potholes, manhole covers, drainage grates, expansion joints, frost heave, hill crests, overall surface roughness of the road surface, cracks, road bulges, banked curves, drainage ditches, and / or any other suitable features on the road surface that generate a relevant force input to a part of the vehicle, or other road features that can be measured by a vehicle while passing over the road surface. Correspondingly, suitable types of sensors that can be used to sense one or more parameters associated with the road surface include, but are not limited to, accelerometers, height sensors, force sensors, outputs from the vehicle's suspension system, and non-contact distance sensors such as laser, lidar, or radar, or vision-based sensors such as stereoscopic cameras. Therefore, it should be understood that this disclosure is not limited to any particular type of road feature, nor is the method of detecting the presence of such road features described herein limited in this way.

[0028]

[0035] The systems and methods described herein can obtain information relating to upcoming portions of a road surface using information such as a road profile that includes multiple reference landmarks which may be included in a road map. For example, a road profile included in a road map may include information relating to both location and direction of travel across the road surface, in addition to information such as elevation changes, perceived acceleration applied to a vehicle while passing over the road surface, measured distance between vehicle components and the road surface, measured distance between vehicle components and external features such as road markings or signs, and / or any other suitable parameters which may be associated with the road surface. For example, elevation changes or expected acceleration along one or more lanes of travel on the road surface may be included in the road map. In addition, depending on the embodiment, the information included in the road profile may be provided in any number of different formats, including references to the spatial domain, the spatial frequency domain, the time domain, and / or reference information associated with a particular portion of the road, in any other suitable way which relates perceived information from a vehicle passing over the road.

[0029]

[0036] Regardless of the specific information contained within the road map, road maps can be provided to a vehicle in numerous ways. For example, in one embodiment, the road map may be stored in non-temporary processor-readable memory installed and included in the vehicle. Alternatively, the road map may be uploaded from a remote database to a buffer on the vehicle using any suitable wireless communication method. Thus, relevant portions of the road map surrounding the vehicle's location and / or along the vehicle's path may be included in the buffer for use by one or more processors of the vehicle. As the vehicle travels along the road surface, portions of the road map uploaded to the buffer may be updated accordingly to ensure that desired portions of the road surface along the upcoming portion of the road surface are included in the buffer.

[0030]

[0037] In light of the above, please understand that the types of information included in road maps, and / or the manner in which road maps are provided to vehicles, are not limited to any particular implementation.

[0031]

[0038] Information contained within road maps can also be collected in any suitable manner. For example, in some embodiments, data related to one or more reference landmarks, such as one or more reference profiles, can be recorded along the mapped road surface using real-time detection by on-board sensors. These sensors may include, but are not limited to, accelerometers and position sensors on the vehicle for recording input from the road surface. In some embodiments, other sensors may be used, such as lidar, radar, light-based sensors, and / or any other suitable sensors capable of measuring one or more parameters related to the road surface and / or the vehicle's location relative to the road surface. In addition, a location system capable of determining the vehicle's location on the road surface while recording parameters associated with the road surface to the vehicle may be used. For example, GNSS data, differential-based GNSS data, real-time kinematic GNSS data, terrain-based location systems, dead reckoning, Kalman filters, and / or any other suitable location systems may be used to determine the absolute location of the vehicle on the road surface associated with the detection information. Depending on the embodiment, the recorded information may come from a single vehicle or other sources, or the recorded information may come from a crowdsourced road map in which information related to a particular road surface is recorded by multiple vehicles passing over that road surface and aggregated to generate an aggregated road map. However, this disclosure is not limited to the use of road maps generated in this manner. Alternatively, depending on the embodiment, the road features and related information included in the road map may come from other information sources, including known or static road profiles. For example, road maps may be generated by any other suitable method, including, but not limited to, laser road scanning, camera-based road mapping, and ground-penetrating radar.

[0032]

[0039] Certain non-limiting embodiments are described in further detail with reference to the figures. Since this disclosure is not limited to the specific embodiments described herein, it should be understood that the various systems, components, features, and methods described in relation to these embodiments may be used individually and / or in any desired combination.

[0033]

[0040] Figure 1 shows a vehicle 100 traveling along a road surface 102 which may include multiple road features that can be characterized as one or more reference landmarks. Depending on the embodiment, the vehicle may include various sensors and control systems as shown in Figure 2. In the shown figure, the vehicle may include one or more processors, such as the illustrated processor 200. The processor may be operably coupled with an optional approximate location system, such as the illustrated GNSS system 202, which may be used to provide the approximate location of the vehicle. The system may also include one or more sensors 204, one or more vehicle systems 206, a non-transient processor-readable memory 208, and, depending on the embodiment, a wireless communication system 210, all operably coupled with the processor. Suitable types of sensors include, but are not limited to, the vehicle's speedometer output; speed sensors, shaft encoders; systems that, although not typically considered sensors, can output relevant information to a processor, including steering input, braking input, height output from the suspension system, speed measurement from the suspension system; non-contact displacement sensors such as accelerometers, lasers, lidar, or radar; and / or any other suitable types of sensors or devices contained within a vehicle that can output a desired signal to a processor for use in the methods and systems described herein. For example, one or more sensors may sense one or more parameters associated with the road surface on which the vehicle is traveling. In embodiments where information is communicated to the vehicle, such as a buffered road map, a wireless communication system may transmit information between the processor and one or more remote databases and / or servers. Memories associated with one or more processors may contain processor-executable instructions that, when executed, cause the processors and associated systems to perform any of the methods described herein. This disclosure is not limited to where the processor used to perform the disclosed method is located; therefore, depending on the embodiment, the processor may be a central processor in a vehicle, one or more processors associated with a location-specific system, one or more processors associated with separate systems contained within the vehicle, a combination of the above, and / or any other suitable processor.

[0034]

[0041] Figure 3 illustrates the concept of a common lane applicable to vehicles traveling across an exemplary road section. All numbers used in relation to Figure 3 are typical and illustrative only. In the illustrated example, the exemplary road section has two actual lanes, as indicated by a dashed lane divider extending between the two separate lanes as vehicles pass through the indicated road section. Furthermore, the left lane of the road section contains a pothole 308. Of the 100 vehicles passing through the road section, 54 begin in the left lane and 46 begin in the right lane. The paths taken were as follows: (i) 25 vehicles started in the left lane, remained in the left lane, and passed through the potholes; (ii) 15 vehicles started in the left lane, changed to the right lane to avoid the potholes, and then returned to the left lane; (iii) 10 vehicles started in the left lane, changed to the right lane to avoid the potholes, and then remained in the right lane; (iv) 46 vehicles started in the right lane and remained in the right lane. The remaining 4 vehicles took some random path that was not repeated by any of the other vehicles. Therefore, although the road section only contains two actual lanes, as shown in the diagram, there are four different common lanes corresponding to the first common lane 300 following the right lane, the second common lane 302 following the left lane, the third common lane 304 avoiding potholes by switching to the right lane and then back to the left lane, and the fourth common lane 306 avoiding potholes by switching to the right lane and then remaining within the right lane. Thus, although a two-lane road is shown in the diagram, it should be understood that a road containing any number of lanes extending across the width of the road can be associated with a number of different common lanes that may be greater than the number of lanes present on the road.

[0035]

[0042] In certain embodiments, common lanes may be individualized for a given vehicle. Therefore, for example, an appropriate common lane may be determined by evaluating 100 different instances in which the same vehicle traveled the same road section, rather than referring to 100 different vehicles in the example above. Alternatively, or in addition, common lanes may even be further individualized for a given driver, thereby being determined by evaluating the route taken by a particular driver.

[0036]

[0043] As described above, depending on the embodiment, a reference road profile associated with a particular section of road may include a mesh of multiple reference landmarks positioned at different locations along the road surface in both the lateral and longitudinal dimensions of the road surface. Figure 4 shows an exemplary road section, which may be the same road section described above with respect to Figure 3, with the corresponding reference road profiles superimposed. The reference road profile includes a two-dimensional mesh of reference landmarks labeled L1 to L8. The illustrated road section includes the aforementioned pothole 308 associated with reference landmark L5. For illustrative purposes only, the reference landmarks are shown as regularly spaced apart, but in practice, such constraints may not exist, as the reference landmarks may have arbitrary lateral and / or longitudinal spacings between them, corresponding to actual road features present on the road surface.

[0037]

[0044] In this exemplary case, each common lane shown in Figure 3 can be considered a "chain" that "links" several reference landmarks to each other. Referring to Figure 4, common lane 1 may be defined by the chain of reference landmarks L1-L3-L5-L7, common lane 2 by the chain L2-L4-L6-L8, common lane 3 by L1-L4-L6-L7, and common lane 4 by L1-L4-L6-L8. That is, in a particular embodiment, each reference landmark in the reference road profile may be linked to one or more other reference landmarks. These links may be established, for example, by evaluating past travel by the same vehicle, past travel by multiple vehicles, and / or past travel by the same driver, and determining a particular series of landmarks commonly passed by the paths of vehicles crossing the road surface.

[0038]

[0045] Figure 5 shows a reference road profile similar to that measured for an actual reference road profile of a real road section. The road profile was generated by measuring the road profiles of multiple vehicles traveling through the real road section. Reference landmarks 506 were identified within the road profile as described herein and in further detail in international application PCT / US2020 / 023610. The measured road profiles containing the identified reference landmarks were then merged together to form an aggregated road map, creating links 508 between consecutive landmarks associated with the actual travel paths of different vehicles. The lines between landmarks indicate links determined based on the reference landmarks sequentially passed along the travel path of each vehicle. Depending on the embodiment, links between reference landmarks may be identified based on the fact that any vehicle traveled a path containing two specific reference landmarks, that a threshold number of vehicles traveled a path between two reference landmarks, the probability distribution of vehicles traveling a path between reference landmarks, a statistical analysis of vehicle passages and encountered reference landmarks, and / or any other suitable method of relating two or more landmarks to each other.

[0039]

[0046] As can be seen in the figure, links extending between reference landmarks form common lanes. Notably, defining common lanes in this way allows for the identification of likely routes without requiring any prior data on the actual number of lanes a particular road section has. For example, as can be seen in the figure, the road section begins as a three-lane road with first, second, and third lanes 500, 502, and 504, respectively. The third lane ends, as indicated by links extending from reference landmark 506 located within the third lane to corresponding reference landmarks located within the first and second lanes, resulting in the road becoming a two-lane road. Thus, the reference road profile includes a mesh of multiple illustrated reference landmarks, each landmark linked to one or more other reference landmarks within the road profile. In some embodiments, the number of vehicles passing through a particular section of the road surface corresponding to a link between two adjacent reference landmarks can be recorded over a given period of time. The number of traversals of a given link can be used to strengthen or weaken the link between two reference landmarks, as further described below, based on an appropriate threshold or other appropriate parameter.

[0040]

[0047] As described above, in some embodiments, it may be desirable to update reference information associated with a particular portion of the road surface over time based on data provided by one or more vehicles passing over the road surface. For example, in some embodiments, lane data may be obtained via differential GNSS or generally from a special lane identification system including one or more special sensors, such as a vehicle-mounted camera, laser, radar, lidar, ground-penetrating scanner, or road-mounted transponder, which can identify lane markings and other waypoints. If a vehicle is equipped with both a road-based location system and a lane identification system capable of determining lane data, in certain embodiments, the vehicle may simultaneously measure its road profile and lane data (e.g., the lateral position of the vehicle on the road surface) as it passes through a given road section. The reference road profile corresponding to the road section may then be updated so that one or more reference landmarks in the reference road profile are associated with a particular lane in the road section. Exemplary methods for updating the reference road profile are given above. In this way, when a second vehicle without a lane identification system subsequently travels along the road, the location of the second vehicle's lane (i.e., the lane it is traveling in) can be determined solely using a road-based location system by matching its measured road profile with a reference landmark associated with a specific lane.

[0041]

[0048] Alternatively, or in addition, even when a differential GNSS and / or lane identification sensor system is unavailable, it may still be possible to determine, or at least estimate, the lateral position of a reference landmark by statistical analysis of historical (e.g., crowdsourced) data regarding which particular wheel encountered the reference landmark. For example, in certain embodiments, a vehicle may measure a road profile while traveling along a road by using multiple sensors (e.g., accelerometers, suspension position sensors, or other suitable sensors), each sensor associated with a particular wheel of the vehicle. In these embodiments, each wheel may measure a different road profile. For example, if the right wheel of the vehicle encounters a small pothole but the left wheel does not, then the road profile measured by the right wheel will be different from the road profile measured by the left wheel. If it is consistently observed that a particular reference landmark is encountered only by wheels on a particular side of the vehicle, or that a particular reference landmark is encountered more frequently by wheels on a particular side of the vehicle, then the lateral position data of the reference landmark can be assumed with greater confidence. Therefore, road profiles measured for multiple wheels of a vehicle can be used to provide information about the location of road features that may be reference landmarks relative to the vehicle.

[0042]

[0049] In certain embodiments, a single road surface may be traversed multiple times by a number of different vehicles (or a single road surface may be traversed multiple times by the same vehicle). In certain embodiments, each time a given vehicle traversing the road surface encounters (or "hits") a reference landmark, the specific wheel of the given vehicle that encountered the reference landmark may be recorded. As the reference landmark is repeatedly traversed, it is possible to determine the ratio of (a) the number of times the reference landmark is encountered by the vehicle's right wheel (referred to as "right hits") to (b) the number of times the reference landmark is encountered by the vehicle's left wheel (referred to as "left hits"). In certain embodiments, lateral position data and / or lane data associated with the reference landmark may be determined or estimated based at least in part on the ratio of right hits to left hits observed over a given period, or on other comparisons. This lateral position data and / or lane data may be associated with a particular reference landmark and stored in a reference road profile.

[0043]

[0050] As an example, Figure 6 shows an exemplary road with multiple reference landmarks 400–416 superimposed. Initially, the longitudinal position of each reference landmark may be known (e.g., in Week 0), but its lateral position (i.e., which particular lane the reference landmark is located in, or where it is located within a single lane) may not be known. For example, since reference landmark 406 is located in the rightmost part of the right-hand lane, when reference landmark 406 is encountered by any vehicle, it is likely to be encountered only by the right wheel of a given vehicle, and very rarely, if at all, by the left wheel of any vehicle. Over time, a comparison of the number of right-hand and left-hand hits for a particular reference landmark can be used to estimate the location of a reference landmark on the road surface. This can be done using ratios, relative proportions of hits, statistical analysis of the distribution of hits, and / or any other appropriate metric for comparing the number of hits on both sides of a vehicle passing over the road surface. For example, because the reference landmark is located on the right side of the rightmost lane, over time, the ratio of right hits to total hits for reference landmark 406 may approach 1, or equal to 1, or a number greater than 0.7 but less than 1, or a number greater than 0.8 but less than 1, or a number greater than 0.9 but less than 1. Conversely, the ratio of left hits to total hits for reference landmark 414 in Figure 6 may approach 1, or equal to 1, or a number greater than 0.7 but less than 1, or a number greater than 0.8 but less than 1, or a number greater than 0.9 but less than 1. For reference landmarks that span two lanes, such as reference landmark 416 in Figure 6, the ratio of right hits to total hits may approach a value around 0.5, and the ratio of left hits to total hits also approaches 0.5. As shown in the figure, the lateral position or lane data of a reference landmark can be estimated based at least in part on the historical ratio of right hits or left hits to total hits for a particular reference landmark.In any case, regardless of the specific metric used to perform the comparison, depending on the embodiment, a measured road profile measured by sensors associated with the wheels located on both sides of the vehicle may be used to determine the relative lateral locations of multiple reference landmarks on the road surface.

[0044]

[0051] Alternatively, or in addition, speed data may be used to determine which lane a reference landmark is located in. On certain types of roads, one lane may have a higher average speed than another lane on the same road (for example, the left lane of a highway generally has a higher average speed than the right lane of the same highway). In certain embodiments, a single road surface may be traversed multiple times by a number of different vehicles (or a single road surface may be traversed multiple times by the same vehicle). In certain embodiments, the vehicle's speed may be recorded each time a given vehicle encounters a reference landmark while traveling on the road surface. Lane data for both the first and second reference landmarks can be inferred by comparing the first average speed of a vehicle encountering a first reference landmark with the second average speed of a vehicle encountering a second reference landmark. For example, if the average speed of vehicles encountering landmark 404 in Figure 6 is 75 mph and the average speed of vehicles encountering landmark 410 is 55 mph, then it can be inferred that landmark 404 is located in the left lane (generally the "high-speed" lane on many main roads) and landmark 410 is located in the right lane. Therefore, lane data for landmarks can be determined at least in part on historical data of the speeds of vehicles encountering the landmarks. In some embodiments, when calculating the average speed of vehicles hitting a particular landmark, vehicles traveling below a predetermined threshold speed (e.g., 10%, 20%, or 30% of the speed limit) can be ignored to avoid counting vehicles when all traffic is moving at low speeds.

[0045]

[0052] In some embodiments, when the lateral position of a landmark is to be determined, the system may undergo a learning phase in which vehicle interactions with all such landmarks within a particular section of road are monitored. Table I shows a hypothetical outcome of such a learning phase. At the start of the learning process (WK0), there were 0 left hits and 0 right hits. By the end of the learning phase, all reference landmarks have been hit, and the total number of hits and the left-to-right hit ratio differ significantly for many of the reference landmarks. By considering these hits and / or statistics of the average speed at which each reference landmark was hit, it may be possible to determine the lateral position of one or more of the reference landmarks, and this lateral position information for various landmarks may be incorporated into a road profile stored in a road map associated with the section of road containing the reference landmarks. Thus, after the learning phase, the lateral location of a vehicle may be determined, at least in part, based on whether the vehicle's right and / or left wheels struck a given reference landmark.

[0046] [Table 1]

[0047]

[0053] In certain embodiments, GNSS or other known location systems (e.g., GPS) may be used to determine the road section on which a vehicle is traveling, but it may be impossible to provide specific lane data because the vehicle lacks a special lane identification system, or because environmental factors (e.g., poor visibility) prevent the use of such a lane identification system. In these cases, a road-based location system may be used to identify the common lane or actual lane on which the vehicle is traveling.

[0048]

[0054] In certain embodiments, the road section on which a vehicle is traveling may be identified using GNSS or some other known location system. In such embodiments, the road section may be known, but the exact location and lane may be unknown. In this case, the vehicle may measure a road profile as it travels through the road section, and the measured profile may be compared to a reference road profile that includes several reference landmarks. If the measured profile matches one of the reference landmarks, the vehicle may be located with an appropriate level of accuracy. In certain embodiments, a match may be considered to have occurred if the similarity between a portion of the measured road profile and one of the reference landmarks exceeds a threshold. In certain embodiments, a match may be considered to have occurred only if (i) the similarity between a portion of the measured road profile and one of the reference landmarks exceeds a first threshold, and (ii) the similarity between a portion of the measured road profile and any other reference landmark in the road section does not exceed a second threshold. Since this disclosure is not limited to any particular method for determining the similarity between a measurement profile and a reference profile, suitable types of comparisons based on thresholds include, but are not limited to, comparing relative correlations between road profiles using a correlation matrix, while calculating correlations for a range of alignment to allow for small errors in the raw position signals, and / or any other suitable comparison method.

[0049]

[0055] In certain embodiments, instead of searching for a match between the measured road profile and individual reference landmarks, the measured road profile may be compared to multiple series of reference landmarks, each series forming a previously identified portion of a common lane. By searching for a match with a series of reference landmarks within a common lane, a higher level of confidence can be obtained than when searching for a match against individual reference landmarks placed at arbitrary locations on the road surface. For example, referring again to Figure 4, a vehicle may be traveling along an exemplary road section while measuring the road profile on the road surface and comparing the measured road profile to an exemplary reference road profile. In one possible example, the measured road profile of a vehicle traveling on the illustrated road section may show a 60% similarity to landmark L3 and a 50% similarity to L8. Based solely on these values, it may not be possible to determine with sufficient confidence whether the vehicle is located at the position of L3 or L8. However, if it was previously determined that the measured road profile also showed a 70% similarity to L1 and a mere 10% similarity to L6. In this case, since L1-L3 form a previously identified common lane, the reliability that the vehicle is actually located at position L3 may be higher. Therefore, various methods and systems may use information about the links between different reference landmarks that form a common lane on the road surface to determine whether a particular measurement road profile corresponds to one or more reference landmarks on the road surface. As shown in the example above, this may be done by comparing the measurement profile with several reference profiles located on the road surface and selecting a reference profile based at least in part on both the overall similarity between the measurement road profile and the reference landmarks, and whether a particular reference landmark is linked to a reference profile previously encountered by the vehicle.

[0050]

[0056] In addition to the above, comparing a measured road profile with all reference landmarks within a given road section can be computationally intensive. Therefore, in certain embodiments, once the vehicle's location is determined to be sufficiently precise, only subsequent landmarks within the common lane of the identified location are compared with the measured road profile. As an example, returning to Figure 4, it may be determined that the vehicle recently passed reference landmark L6. In one embodiment, the road profile measured thereafter can be compared with all reference landmarks L1-L8. However, this can require considerable computational power. Alternatively, by considering the common lane including L6, it may be determined that L7 and L8 are the only subsequent reference landmarks located ahead of the vehicle's path, which are part of the common lane including L6. Therefore, comparing the road profile measured thereafter with only L7 and L8 may be more computationally efficient. Thus, it may be more efficient to compare the measured road profile only with reference landmarks that form part of the common lane including the previously matched reference profile, rather than comparing it with all nearby reference landmarks. In other words, depending on the embodiment, the comparison of one or more road surface measurement parameters, such as a measured road profile, may be limited to analyzing reference landmarks linked to one or more reference landmarks encountered by the vehicle. For example, the reference landmarks to be analyzed may be limited to those linked to the last reference landmark encountered by the vehicle. In this case, as before, this may help improve the computational efficiency and accuracy of the comparison process.

[0051]

[0057] In addition to the above, it may be desirable for one or more vehicle systems (e.g., active suspension system, semi-active suspension system, steering system, braking system, propulsion system) to know what lies ahead of the vehicle so that they can proactively prepare (e.g., by adjusting vehicle height, suspension damping parameters, brake pressure, engine speed, and / or any other operating parameters, etc.) before encountering various road features on the upcoming portion of the road surface. In certain embodiments, once the vehicle is located at the position of a given reference landmark, it may be predicted that the vehicle will follow one of the common lanes to which the given reference landmark belongs. By predicting the likely path the vehicle will take based on the previously identified common lanes, the vehicle system may proactively adjust various operating parameters of one or more systems on the vehicle, and / or the system may proactively act based on expected inputs from road features located along the predicted path of the vehicle. For example, in certain embodiments, the vehicle's path may be predicted and associated with a confidence level. In certain embodiments, this confidence level may be determined at least in part on (a) the number of common lanes to which a given reference landmark belongs, and / or (b) the number of other reference landmarks to which a given reference landmark is linked. For example, returning to Figure 4, landmark L2 belongs to only one common lane (L2-L4-L6-L8) and is linked to only one other reference landmark L4. On the other hand, landmark L6 belongs to several common lanes and is linked to two other reference landmarks L7 and L8. Therefore, the prediction that a vehicle located at landmark L2 will proceed to the location of landmark L4 may be associated with a higher confidence level than the prediction that a vehicle located at landmark L6 will proceed to the location of landmark L8. Thus, in certain embodiments, the control of the various vehicle systems referred to herein may be based in part on both the predicted path of the vehicle and the confidence level associated with such prediction. In certain embodiments, a vehicle system having the capability of proactive adjustment and / or operation may adjust one or more parameters only when the confidence level associated with the predicted path exceeds a threshold.

[0052]

[0058] In some embodiments of fully active or semi-active suspension systems, information about the road ahead of the vehicle may be used to prevent collisions with the damper's extension and / or compression end stops. For example, based on information about the road profile ahead of the vehicle, it may be determined that at the speed the vehicle is moving forward, the expected vertical motion distance of the damper may be greater than its available range of motion. In this case, the controller may instruct various controlled valves or actuators to modify specific operating parameters of the damper to avoid collisions with one or more of the end stops. Alternatively, or in addition, the vehicle's ground clearance may be adjusted to increase the available range of motion of the damper on the side where an additional range is required (compression or extension).

[0053]

[0059] In certain embodiments, a lane change or common lane change may be determined in one or more ways when a vehicle leaves the common lane it is currently traveling in. In certain embodiments, information from one or more sensors or vehicle systems may be used to detect a deviation from the path corresponding to the actual lane or common lane. This information may include, for example, GNSS; vehicle yaw rate and / or steering information that exceeds the yaw rate and / or steering input for the expected route along a particular common lane (e.g., exceeding the difference in magnitude of the threshold between the expected and actual yaw rate and / or steering input); camera information, where present, to see how lane markings are being crossed; and / or deviation from the path given by any other suitable method having the ability to determine when the vehicle has left a particular common lane. Alternatively, or in addition, a lane change may be assumed when the measured road profile does not match a threshold number of expected reference landmarks. In certain embodiments, when a lane change or common lane change is suspected for any of these reasons, the road-based location system may restart the location process, and optionally, proactive adjustments by the vehicle system may be prevented until a new common lane is identified.

[0054]

[0060] Figure 7 shows one method for implementing a mapping module for providing a road map with desired reference landmarks and associated links. Depending on the embodiment, the mapping module may be stored and executed in various locations, such as by a processor associated with a central database and / or server located remotely from the vehicle using the resulting road map. For example, a central database may be used to aggregate information for compiling a road map that can then be delivered to individual vehicles in order to implement the method described herein. However, the disclosure is not limited thereto, and embodiments in which the mapping module is implemented on a processor mounted in an individual vehicle are also contemplated.

[0055]

[0061] In the illustrated method, at 600, one or more parameters associated with the road surface can be sensed for locations on the road surface. As described above, road surface parameters and location data can be obtained in several different ways. For example, information can be aggregated from one or more vehicles that pass over the road surface multiple times. Alternatively, information can be collected using a dedicated sensing system as described above. In either case, an appropriate dataset containing sensed parameters and location information can be provided. After obtaining the desired information, at 602, multiple reference landmarks and their locations on the road surface can be identified using one or more road surface parameters and associated location information. As described above, this identification of reference landmarks can be done using any appropriate method, including, but not limited to, calculating correlations between sections of road profiles and landmarks for a number of road profiles at different location offsets, and identifying those with the highest correlations within distance offsets below a predetermined threshold. Next, at 604, a mesh, such as a multidimensional mesh, corresponding to the longitudinal and transverse dimensions of the road surface, can be generated using the identified multiple reference landmarks and their associated locations. For example, a multidimensional mesh may include a number of dimensions greater than or equal to the number of lanes on a road at a particular location, as described above. The mesh may include information related to a reference landmark, and corresponding location information associated with each reference landmark.

[0056]

[0062] In 606, links between reference landmarks included in the mesh can be determined using information associated with multiple vehicles passing over the mapped road surface. This information may correspond to a measured road profile, including appropriate sensed road input from vehicle sensors, which may correspond to one or more parameters used to characterize the reference road profile of that particular portion of the road surface. This information may be sensed and used on a single vehicle, and / or the information may be transmitted from one or more vehicles to one or more remotely located servers and / or databases. Regardless of where or how the information is aggregated, the measured road profiles from multiple passes over the road surface can be analyzed, as described above, to identify which reference landmarks were encountered by vehicles and in what order those reference landmarks were encountered. As described above, each vehicle pass between two landmarks may be used to reinforce the relationship between those two landmarks. For example, if the correlation between two reference landmarks, e.g., the number of vehicle passes exceeds a threshold, a link between two consecutively placed reference landmarks may be included in the mesh. Correspondingly, in embodiments where the road map is updated based on actual usage data, if the number of vehicles passing through a road segment between two reference landmarks falls below a threshold over a given period of time, and / or if the threshold number of vehicles fails to identify one or both of those landmarks, links and / or reference landmarks may be removed from the mesh. However, a mesh may be provided that includes multiple reference landmarks and links extending between those reference landmarks, regardless of how particular links are generated and / or maintained over time.

[0057]

[0063] In 608, a reference road profile may be generated that includes a mesh of linked reference landmarks and their locations on the road surface. In some cases, the reference road profile may simply include one or more road surface parameters associated with each of the reference landmarks. However, embodiments may also be envisioned in which portions of road parameters associated with portions of the road surface extending between the reference landmarks are included in the reference road profile. Once the reference road profile is generated, in 610, the road map containing the reference road profile may be stored in non-temporary processor-readable memory for future retrieval and / or use by the methods and systems described herein.

[0058]

[0064] While the embodiments shown in the figures illustrate a linear process for generating a road map containing a desired reference profile with multiple linked reference landmarks, it should be understood that embodiments are also contemplated in which the reference profile associated with one or more sections of the road map is updated over time. For example, as described above, in some embodiments, information perceived by vehicles passing through various sections of roads included in the road map may be used to update either the reference landmarks and / or the links extending between the reference landmarks over time to ensure that the road map is up-to-date with the actual conditions present on the road surface. Therefore, it should be understood that the disclosure is not limited in that way, and is not limited to any particular way in which road maps are generated and / or maintained over time.

[0059]

[0065] Figure 8 shows one embodiment of a method that may be implemented by a location-finding module that can be used to determine the location of a vehicle on the road surface using linked reference landmarks contained within a road map. Depending on the embodiment, the location-finding module may be used solely to determine the location of a vehicle on the road surface. However, embodiments are also envisioned in which the location-finding module, or the output from the location-finding module, is used to control one or more operating parameters and / or operations of systems installed on the vehicle, as will be further detailed below. Depending on the particular embodiment, the location-finding module may be stored and executed at various locations on the vehicle. This disclosure is not limited to where or how these processes are implemented, and this may include a central processor in the vehicle, a dedicated processor for the location-finding module, distributed processors associated with various systems in the vehicle, a combination of the above, and / or any other suitable mechanism.

[0060]

[0066] In the illustrated embodiment, at 700, the location and path of the vehicle along the road surface can be identified. For example, information from a location system, such as a Global Navigation Satellite System (GNSS), a terrain-based location system, and / or any other suitable location system, together with information from a suitable system, such as an autonomous vehicle control system, may be used by the processor to identify the approximate location of the vehicle on the road. Next, at 702, the processor can obtain a road map containing information such as a reference road profile relating to the portion of the road being traversed by the vehicle. Depending on a particular embodiment, the processor may obtain a desired road map by retrieving it from memory, loading it into a buffer from data downloaded to the vehicle from a remote database and / or server, and / or any other suitable method for obtaining a road map containing a desired portion of the road surface.

[0061]

[0067] In 704, the vehicle may sense one or more parameters relating to the road surface of the road on which the vehicle is traveling. As stated above, one or more parameters may correspond to any suitable parameters having the ability to characterize the road surface. These may include parameters such as acceleration, force input, height variation, combinations thereof, and / or any other suitable types of parameters that may be used to characterize the road surface. In addition, one or more parameters may be sensed using sensors, outputs from various systems of the vehicle, and / or any other suitable devices that can provide a processor with a desired input. Regardless of how one or more parameters are sensed, in 706, one or more sensed parameters that may correspond to the measurement road profile may be compared to a reference road profile to identify one or more reference landmarks encountered by the vehicle. This comparison may be made using any of the previously disclosed methods for comparing the measurement road profile with a reference road profile or other suitable information that may be used to characterize reference landmarks on the road surface. After identifying the reference landmarks encountered by the vehicle, in 708, one or more related reference landmarks linked to the last reference landmark encountered by the vehicle may be identified. For example, one or more common lanes containing the last encountered reference landmark can be identified using links contained within a mesh of reference landmarks contained on the road surface. This may involve identifying linked reference landmarks positioned ahead of the vehicle along one or more common lanes relative to the vehicle's direction of travel on the road surface. These common lanes can then be used to predict the vehicle's path on the road surface based on the linked reference landmarks. The confidence level associated with one or more predicted paths may be a function of the number of common lanes linked to the vehicle's current position and the corresponding reference landmarks.

[0062]

[0068] In some cases, in 710, one or more systems of a vehicle may be controlled based on the predicted path of the vehicle using a road profile extending along the predicted path to the next identified reference landmark. For example, one or more operating parameters of a system may be changed based on one or more incoming road features contained within a portion of the road extending along a common lane in which the vehicle is positioned. Alternatively, one or more systems may be made to act in a way that proactively responds to one or more incoming road features. Specific methods for operating various systems of a vehicle based on the predicted path of the vehicle along one or more common lanes on the road surface are described in further detail above.

[0063]

[0069] In some embodiments, it may be desirable to reduce computational costs and / or improve the accuracy associated with the use of linked reference landmarks. Therefore, in 712, the location module may continue to sense one or more parameters related to the road surface to provide, for example, a measurement road profile. In 714, one or more sensed parameters of the road surface, e.g., a measurement road profile, may be compared to a reference road profile extending along one or more predicted paths of a vehicle (e.g., one or more common lanes). For example, a measurement road profile may be compared to one or more reference road profiles associated with one or more reference landmarks linked to a reference landmark, such as the last reference landmark encountered by the vehicle. This can improve both computational costs and accuracy by limiting the comparison of the measurement road profile to those reference road profiles associated with one or more linked reference landmarks.

[0064]

[0070] In addition to the foregoing, in some embodiments, in 716, the system may also determine whether a lane change has occurred from the common lane the vehicle was traveling in. For example, as described above, a yaw rate greater than a threshold for a given portion of the road surface, a line sensor, a steering input greater than a threshold for a given portion of the road surface, and / or any other suitable system and / or method may be used to determine whether the vehicle has left the common lane the vehicle was traveling in.

[0065]

[0071] In step 718, it may be determined whether the measured road profile matches the expected reference road profile along the predicted route, or whether a lane change has been detected. Assuming that the measured and predicted reference road profiles match and no lane change has been detected, the process may continue to identify any reference landmarks encountered thereafter and predict the vehicle's route using reference landmarks linked to the encountered reference landmarks. However, if the measured and predicted reference road profiles do not match and / or a lane change has been detected, the process may return to step 704, where, in step 706, the approximate location of the vehicle may be determined by identifying reference landmarks encountered by the vehicle using a rougher comparison with the reference road profile of the section of road in which the vehicle is located. The process may then continue as described above.

[0066]

[0072] The embodiments of the technology described herein can be implemented in any of many ways. For example, embodiments can be implemented using hardware, software, or a combination thereof. When implemented in software form, the software code can run on any suitable processor or group of processors, whether provided within a single computing device or distributed across multiple computing devices. Such a processor can be implemented as an integrated circuit having one or more processors within an integrated circuit component, including commercially available integrated circuit components known in the art by names such as CPU chips, GPU chips, microprocessors, microcontrollers, or coprocessors. Alternatively, the processor can be implemented in the form of a custom circuit mechanism, such as an ASIC, or a quasi-custom circuit mechanism obtained from constituting a programmable logic device. As a further alternative, the processor can be part of a larger circuit or semiconductor device, whether commercial, quasi-custom, or custom. Specifically, some commercial microprocessors have multiple cores, so that one or a subset of those cores can constitute a processor. However, the processor can be implemented using a circuit mechanism of any suitable format.

[0067]

[0073] Furthermore, a processor may be associated with one or more input and output devices. These devices can, among other things, be used to present a user interface. Examples of output devices that can be used to provide a user interface include display screens for visual presentation of output and speakers or other sound-generating devices for audible presentation of output. Examples of input devices that can be used for a user interface include keyboards, individual buttons, and pointing devices such as mice, touchscreens, touchpads, and digitizing tablets. As another example, a processor may receive input information through speech recognition or in other audible formats.

[0068]

[0074] Such processors may be interconnected by one or more networks of any preferred form, such as local area networks or wide area networks, including enterprise networks or the Internet. Such networks may be based on any preferred technology, operate according to any preferred protocol, and may include wireless networks, wired networks, or fiber optic networks.

[0069]

[0075] Furthermore, the various methods or processes outlined herein may be coded as software executable on one or more processors utilizing any of the various operating systems or platforms. In addition, such software may be written using any of the many suitable programming languages ​​and / or programming or scripting tools, and may be compiled as executable machine language code or intermediate code that runs on a framework or virtual machine.

[0070]

[0076] In this regard, the embodiments described herein may be embodied as a processor-readable storage medium (or a group of processor-readable media) (for example, computer memory, one or more floppy disks, compact discs (CDs), optical discs, digital video discs (DVDs), magnetic tape, flash memory, RAM, ROM, EEPROM, field-programmable gate arrays or circuit configurations in other semiconductor devices, or other tangible computer storage media) that encodes one or more programs that perform the methods for carrying out the various embodiments described above when executed on one or more computers or other processors. As is evident from the examples above, the processor-readable storage medium may retain information for a sufficient amount of time to provide non-temporary processor-executable instructions. Such a processor-readable storage medium or group of media may be portable so that the programs or groups of programs stored thereon may be loaded onto one or more different computing devices or other processors to carry out the various embodiments of the present disclosure as described above. As used herein, the terms “processor-readable storage medium” or “processor-readable memory” encompass only non-transient processor-readable mediums that can be considered as products (i.e., manufactured goods) or machines. Alternatively, or in addition, the Disclosure may be embodied in processor-readable mediums other than processor-readable storage mediums, such as propagating signals.

[0071]

[0077] The terms “program” or “software” are used herein in a general sense to mean any type of computer code or set of processor-executable instructions that can be used to program a computing device or other processor to perform the various aspects of the Disclosure as described above. In addition, it should be understood that, according to one aspect of this embodiment, one or more computer programs that perform the methods of the Disclosure when executed do not need to reside on a single computing device or processor, but can be modularly distributed among many different computers or processors to perform the various aspects of the Disclosure.

[0072]

[0078] Processor-executable instructions can take many forms, such as program modules, that are executed by one or more processors or other devices. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. Typically, the functionality of program modules can be combined or distributed as desired in various embodiments.

[0073]

[0079] The embodiments described herein may be embodied as methods, with examples provided. The actions performed as part of the method may be ordered in any preferred manner. Thus, embodiments may be constructed in which the actions are performed in an order different from that exemplified. This may include performing some actions simultaneously, even if they are shown as sequential actions in the exemplary embodiments.

[0074]

[0080] Furthermore, some actions are described as being taken by the “User.” It should be understood that the “User” does not necessarily have to be a single individual; depending on the embodiment, actions attributed to the “User” may be performed by a team of individuals, and / or individuals in combination with computer-aided tools or other mechanisms.

[0075]

[0081] Although this instruction has been described in relation to various embodiments and examples, it is not intended to be limited to such embodiments or examples. On the contrary, as will be understood by those skilled in the art, this instruction encompasses various alternatives, modifications, and equivalents. Accordingly, the above description and drawings are merely illustrative examples.

Claims

1. A method for determining the location of a vehicle, wherein the method is Sensing one or more parameters associated with the road surface of the road the vehicle is traveling on, Using one or more of the sensed parameters, identify a first reference landmark on the road encountered by the vehicle. Identifying a second reference landmark on the road linked to the first reference landmark, It is predicted that the vehicle will pass through the portion of the road surface extending between the first reference landmark and the second reference landmark, A method that includes this.

2. The method according to claim 1, further comprising comparing one or more of the parameters with a reference road profile to identify the first reference landmark.

3. The method according to claim 2, further comprising obtaining the aforementioned reference road profile.

4. The method according to claim 3, wherein the reference profile includes a mesh of a plurality of reference landmarks arranged on the road surface, and each reference landmark in the mesh is linked to at least one other reference landmark in the mesh.

5. The method according to claim 1, further comprising determining the lateral position of the vehicle on the road surface based at least partially on the location of the first reference landmark.

6. The method according to claim 1, further comprising sensing one or more of the parameters and comparing the one or more of the parameters with a reference road profile extending between the first reference landmark and the second reference landmark.

7. The method according to claim 1, further comprising controlling the vehicle's system at least partially based on the characteristics of the second reference landmark and one or more selected from a group of reference road profiles extending inclusively between the first reference landmark and the second reference landmark, before the vehicle encounters the second reference landmark.

8. The method according to claim 7, further comprising determining a confidence level associated with the prediction, wherein the confidence level is determined at least in part on the total number of reference landmarks linked to the first reference landmark, and the system of the vehicle is controlled at least in part on the determined confidence level.

9. A method for determining the location of a vehicle, wherein the method is Sensing one or more parameters associated with the road surface of the road the vehicle is traveling on, Identifying a first reference landmark on the road encountered by the vehicle, based at least partially on one or more of the sensed parameters, As the vehicle passes over the road surface, it continues to sense one or more of the parameters, The position of the vehicle on the road surface is determined by comparing one or more of the parameters with information relating only to the portion of the road surface that extends implicitly between the first reference landmark and at least one reference landmark linked to the first reference landmark, A method that includes this.

10. The method according to claim 9, further comprising comparing one or more of the parameters with a reference road profile to identify the first reference landmark.

11. The method according to claim 10, further comprising obtaining the aforementioned reference road profile.

12. The method according to claim 1, wherein the reference profile includes a mesh of a plurality of reference landmarks arranged on the road surface, each reference landmark in the mesh is linked to at least one other reference landmark in the mesh, and the first reference landmark and the at least one reference landmark linked to the first landmark are a portion of the plurality of reference landmarks.

13. The method according to claim 9, further comprising determining the lateral position of the vehicle on the road surface.

14. The method according to claim 9, further comprising controlling the vehicle's system at least partially based on the features of the at least one reference landmark and one or more selected from a group of reference road profiles extending inclusively between the first reference landmark and the at least one reference landmark, before the vehicle encounters the at least one reference landmark linked to the first reference landmark.

15. The method according to claim 9, further comprising identifying the at least one reference landmark linked to the first reference landmark based at least in part on one or more sensed parameters.

16. The method according to claim 15, further comprising predicting that the vehicle will pass through a portion of the road surface extending between the first reference landmark and the at least one reference landmark linked to the first reference landmark.

17. It is a vehicle, One or more sensors configured to sense one or more parameters associated with the road surface on which the vehicle is traveling, A processor operably coupled to one or more of the aforementioned sensors, The processor is equipped with, As the vehicle travels along the road, it senses one or more parameters associated with the road surface, Using one or more of the sensed parameters, identify a first reference landmark on the road encountered by the vehicle. Identifying a second reference landmark on the road linked to the first reference landmark, It is predicted that the vehicle will pass through the portion of the road surface extending between the first reference landmark and the second reference landmark, A vehicle configured to perform the following actions.

18. The vehicle according to claim 17, wherein the processor is further configured to compare the one or more parameters with a reference road profile and to identify the first reference landmark.

19. The vehicle according to claim 18, wherein the processor is further configured to obtain the reference road profile.

20. The vehicle according to claim 19, wherein the reference profile includes a mesh of a plurality of reference landmarks arranged on the road surface, and each reference landmark in the mesh is linked to at least one other reference landmark in the mesh.

21. The vehicle according to claim 17, wherein the processor is further configured to determine the lateral position of the vehicle on the road surface based at least partially on the location of the first reference landmark.

22. The vehicle according to claim 17, wherein the processor is further configured to continuously sense the one or more parameters and to compare the one or more parameters with a reference road profile extending between the first reference landmark and the second reference landmark.

23. The vehicle according to claim 17, wherein the processor is configured to control the vehicle's systems at least partially based on the characteristics of the second reference landmark and one or more selected from a group of reference road profiles extending inclusively between the first reference landmark and the second reference landmark, before the vehicle encounters the second reference landmark.

24. The vehicle according to claim 23, wherein the processor is further configured to determine a confidence level associated with the prediction, the confidence level being determined at least in part on the total number of reference landmarks linked to the first reference landmark, and the processor is configured to control the system of the vehicle at least in part on the determined confidence level.

25. It is a vehicle, One or more sensors configured to sense one or more parameters associated with the road surface on which the vehicle is traveling, A processor operably coupled to one or more of the aforementioned sensors, The processor is equipped with, Sensing one or more parameters associated with the road surface of the road the vehicle is traveling on, Identifying a first reference landmark on the road encountered by the vehicle, based at least partially on one or more of the sensed parameters, As the vehicle passes over the road surface, it continues to sense one or more of the parameters, The position of the vehicle on the road surface is determined by comparing one or more of the parameters with information relating only to the portion of the road surface that extends implicitly between the first reference landmark and at least one reference landmark linked to the first reference landmark, A vehicle configured to perform the following actions.

26. The vehicle according to claim 25, wherein the processor is further configured to compare the one or more parameters with a reference road profile and to identify the first reference landmark.

27. The vehicle according to claim 26, wherein the processor is further configured to obtain the reference road profile.

28. The vehicle according to claim 27, wherein the reference profile includes a mesh of a plurality of reference landmarks arranged on the road surface, each reference landmark in the mesh is linked to at least one other reference landmark in the mesh, and the first reference landmark and the at least one reference landmark are parts of the plurality of reference landmarks.

29. The vehicle according to claim 25, wherein the processor is further configured to determine the lateral position of the vehicle on the road surface.

30. The vehicle according to claim 25, wherein the processor is further configured to control the vehicle's system at least partially based on the features of the at least one reference landmark and one or more selected from a group of reference road profiles extending inclusively between the first reference landmark and the at least one reference landmark, before the vehicle encounters the at least one reference landmark linked to the first reference landmark.

31. The vehicle according to claim 25, wherein the processor is further configured to identify the at least one reference landmark linked to the first reference landmark based at least in part on one or more sensed parameters.

32. The vehicle according to claim 31, wherein the processor is further configured to predict that the vehicle will pass through a portion of the road surface extending between the first reference landmark and the at least one reference landmark linked to the first reference landmark.

33. A method for generating a road map, wherein the method is To determine whether each of the multiple vehicles traveling on the road surface encountered multiple reference landmarks, The process involves determining the route each vehicle takes with respect to the aforementioned multiple reference landmarks, and identifying the links between the aforementioned multiple reference landmarks. To generate a mesh of the plurality of reference landmarks and the links extending between the plurality of reference landmarks, The mesh is stored in non-temporary processor-readable memory for future recall and / or use. A method that includes this.

34. The method according to claim 33, wherein each of the plurality of reference landmarks is linked to at least one other reference landmark of the mesh.

35. The method according to claim 33, wherein the road map includes a reference profile of the road surface extending between the linked reference landmarks.

36. The method according to claim 33, further comprising determining a confidence level associated with the progression path extending between the linked reference landmarks, at least in part on the number of links associated with each reference landmark.

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