Vehicle control based on path lay status and location telemetry

Abstract

Vehicle control based on path laying status and location telemetry. A system for controlling operation of a vehicle includes a controller and a command unit. The command unit is adapted to generate respective laying states for the respective paths based on aggregated vehicle trajectories for the plurality of vehicles traversing the respective paths, including extracting respective coordinates and respective trajectories for the plurality of vehicles over a predefined period of time. The command unit is adapted to determine a respective lateral distance between the plurality of vehicles and the centerline in the respective path. When one or more predefined conditions based on the respective lateral distance are satisfied, the respective path is designated as an unlaid path. The unlaid path is defined by the absence of centerline indicia. The controller is adapted to retrieve a respective laying state and control operation of the vehicle while the vehicle is traversing the unlaid path.

Description

[0001] introduce

[0002] This disclosure generally relates to using aggregated vehicle trajectories of multiple vehicles traversing a given path to profile that path and control vehicle operations on that path. Autonomous vehicles can use sensors to navigate through their environment to detect objects and can be guided by a vehicle planning algorithm used to plan their trajectory. However, the complexity of vehicle movement on tertiary or underdeveloped roads can pose challenges to the navigation of autonomous vehicles. Summary of the Invention

[0003] This document discloses a system for controlling the operation of a vehicle. The system includes a controller having a processor and a tangible, non-transitory memory thereon for recording instructions. The vehicle is capable of operating in an automated driving mode. A command unit is adapted to generate a corresponding pave state for a given path based on aggregated vehicle trajectories of multiple vehicles traversing that path, including extracting the corresponding coordinates and trajectories of the multiple vehicles over a predefined time period. The command unit is adapted to determine corresponding lateral distances between the multiple vehicles and the centerline of the corresponding path. When one or more predefined conditions based on the corresponding lateral distance are met, the corresponding path is designated as an unpaved path. An unpaved path is defined by the absence of a centerline marker.

[0004] The controller is adapted to retrieve the corresponding paving status when a vehicle is traversing an unpaved path and to control the operation of the vehicle in part based on the corresponding paving status. Controlling the operation of the vehicle may include transmitting a takeover request to the user of the vehicle when the vehicle is traversing an unpaved path to switch from an automated driving mode to a manual driving mode.

[0005] The command unit may be adapted to transmit the corresponding paving status to a database, wherein the controller is adapted to retrieve the corresponding paving status from the database. The system may include a vehicle planning module, executable by the controller, to generate a trajectory plan constrained by a set of planning parameters for the vehicle. The controller may be adapted to generate at least one adjusted parameter from the planning parameter set when the vehicle is traversing an unpaved path. The vehicle planning module is adapted to generate a modified trajectory plan based on the adjusted parameters. The controller is adapted to use the modified trajectory plan when the vehicle is on an unpaved path and to discontinue the use of the modified trajectory plan when the unpaved path has been completely traversed.

[0006] The parameters to be adjusted may include the minimum lateral distance and / or minimum longitudinal clearance between vehicles and adjacent vehicles. The parameters to be adjusted may include the maximum speed limit, the maximum acceleration during vehicle maneuvering, and the minimum acceleration during maneuvering. The controller may be adapted to divide the planning parameter set into a primary list and a secondary list with corresponding weighting factors, with the primary list being adjusted over the secondary list.

[0007] A path is designated as unpaved when one or more predefined conditions based on a corresponding lateral distance are met. In one embodiment, the predefined conditions include: a predefined percentage of multiple vehicles crossing the centerline of the corresponding path at least once, and the average of the corresponding lateral distances being greater than a predetermined distance. In one example, the predefined percentage is 50%, and the predetermined distance is 0.80 meters.

[0008] In another embodiment, the predefined conditions include: the absolute value of the skewness factor of the distribution for the corresponding lateral distance is greater than a skewness threshold; the absolute value of the kurtosis factor of the distribution is greater than a kurtosis threshold; and the average value of the corresponding lateral distance is greater than a predetermined distance. In one example, the skewness threshold is 3, the kurtosis threshold is 3, and the predetermined distance is between approximately 0.80 meters and 1.0 meter.

[0009] This paper discloses a method for controlling the operation of a vehicle using a controller having a processor and a tangible, non-transitory memory thereon for recording instructions, and a command unit accessible to the controller. The method includes generating trajectory planning, partially based on a set of planning parameters, via execution of a vehicle planning module by the controller, enabling the vehicle to operate in an automated driving mode. The method further includes generating a corresponding paving state of a path based on aggregated vehicle trajectories of multiple vehicles traversing the path, via the command unit, including: extracting the corresponding coordinates and trajectories of the multiple vehicles over a predefined time period, and determining the corresponding lateral distances between the multiple vehicles and the centerline of the corresponding path.

[0010] The method includes designating a corresponding path as an unpaved path via a command unit when one or more predefined conditions based on a corresponding lateral distance are met; the unpaved path is defined by the absence of a centerline marker. The method also includes retrieving the corresponding paving status via a controller when a vehicle is traversing the unpaved path, and controlling the operation of the vehicle in part based on the corresponding paving status.

[0011] This paper discloses a vehicle with a controller having a processor and a tangible, non-transitory memory thereon for recording instructions, the vehicle being capable of operating in an automated driving mode. A vehicle planning module, executable by the controller, generates a trajectory plan constrained by a set of planning parameters for the vehicle. The controller is adapted to retrieve the corresponding paving state as the vehicle traverses the corresponding path. The corresponding paving state is generated by a command unit using aggregated vehicle trajectories from multiple vehicles traversing the corresponding path.

[0012] The command unit is adapted to designate a corresponding path as an unpaved path when one or more predefined conditions are met, said predefined conditions being based on corresponding lateral distances between multiple vehicles and the centerline of the corresponding path, where an unpaved path is defined by the absence of a centerline marker. The controller is adapted to retrieve the corresponding paving status when a vehicle is traversing an unpaved path and to control the operation of the vehicle in part based on the corresponding paving status. Controlling the operation of the vehicle includes transmitting a takeover request to the user of the vehicle when the vehicle is traversing an unpaved path to switch from an automated driving mode to a manual driving mode.

[0013] A system for controlling the operation of a vehicle includes: a controller having a processor and a tangible non-transitory memory thereon storing instructions, the vehicle being capable of operating in an automated driving mode; a command unit adapted to generate a corresponding paving state of a corresponding path based on aggregated vehicle trajectories of multiple vehicles traversing a corresponding path, including: extracting corresponding coordinates and corresponding trajectories of the multiple vehicles over a predefined time period; and determining corresponding lateral distances between the multiple vehicles and centerlines in the corresponding path; wherein the command unit is adapted to designate a corresponding path as an unpaved path when one or more predefined conditions based on the corresponding lateral distance are met, the unpaved path being defined by the absence of centerline markings; and wherein the controller is adapted to retrieve the corresponding paving state while the vehicle is traversing an unpaved path and to control the operation of the vehicle in part based on the corresponding paving state.

[0014] The operation of controlling the vehicle includes transmitting a takeover request to the user of the vehicle when the vehicle is traversing an unpaved path, in order to switch from automated driving mode to manual driving mode.

[0015] The command unit is adapted to transmit the corresponding laying status to the database, and the controller is adapted to retrieve the corresponding laying status from the database.

[0016] Further comprising: a vehicle planning module, executable by a controller to generate a trajectory plan constrained by a set of planning parameters for the vehicle; wherein the controller is adapted to generate at least one adjusted parameter from the planning parameter set when the vehicle is traversing an unpaved path, the vehicle planning module is adapted to generate a modified trajectory plan based on the at least one adjusted parameter; and the controller is adapted to use the modified trajectory plan when the vehicle is on an unpaved path and to discontinue the use of the modified trajectory plan when the unpaved path has been completely traversed.

[0017] Among them, at least one of the adjusted parameters includes the minimum lateral distance and / or minimum longitudinal clearance between the vehicle and adjacent vehicles.

[0018] Wherein: at least one of the adjusted parameters includes a maximum speed limit, a maximum acceleration during vehicle maneuvering, and a minimum acceleration during maneuvering; and the controller is adapted to divide the planning parameter set into a primary list and a secondary list with corresponding weighting factors, wherein the primary list is adjusted in priority over the secondary list.

[0019] One or more predefined conditions include: a predefined percentage of multiple vehicles crossing the centerline of the corresponding path at least once; and the average of the corresponding lateral distances being greater than a predetermined distance.

[0020] The predefined percentage is 50%, and the predefined distance is 0.80 meters.

[0021] One or more predefined conditions include: the absolute value of the skewness factor of the distribution of the corresponding lateral distance is greater than the skewness threshold; the absolute value of the kurtosis factor of the distribution is greater than the kurtosis threshold; and the average value of the corresponding lateral distance is greater than a predetermined distance.

[0022] The skewness threshold is 3, the kurtosis threshold is 3, and the predetermined distance is between approximately 0.80 meters and 1.0 meters.

[0023] A method for controlling the operation of a vehicle using a controller, the controller having a processor and a tangible non-transitory memory thereon storing instructions, and a command unit accessible to the controller, the method comprising: generating a trajectory plan, in part based on a set of planning parameters, via the controller using a vehicle planning module, wherein the vehicle is capable of operating in an automated driving mode; generating a corresponding paving state of a corresponding path via the command unit based on aggregated vehicle trajectories of multiple vehicles traversing the corresponding path, including: extracting corresponding coordinates and corresponding trajectories of the multiple vehicles over a predefined time period; and determining corresponding lateral distances between the multiple vehicles and centerlines in the corresponding path; designating the corresponding path as an unpaved path via the command unit when one or more predefined conditions based on the corresponding lateral distance are met, the unpaved path being defined by the absence of a centerline marker; and retrieving the corresponding paving state via the controller while the vehicle is traversing the unpaved path, and controlling the operation of the vehicle in part based on the corresponding paving state.

[0024] Further includes: generating at least one adjusted parameter from a planning parameter set via a controller when the vehicle is traversing a corresponding path designated as an unpaved path; generating a modified trajectory plan via a vehicle planning module based on the at least one adjusted parameter; and an automated driving mode based on the modified trajectory plan.

[0025] Further includes: selecting at least one adjusted parameter to include the minimum lateral distance and / or minimum longitudinal clearance between the vehicle and adjacent vehicles.

[0026] Further includes: selecting at least one adjustable parameter to include a maximum speed limit, a maximum acceleration during vehicle maneuvering, and a minimum acceleration during maneuvering.

[0027] One or more predefined conditions include: a predefined percentage of multiple vehicles crossing the centerline of the corresponding path at least once; and the average of the corresponding lateral distances being greater than a predetermined distance.

[0028] Further options include: selecting a predefined percentage of 50% and a predetermined distance of 0.80 meters.

[0029] One or more predefined conditions include: the absolute value of the skewness factor of the distribution of the corresponding lateral distance is greater than the skewness threshold; the absolute value of the kurtosis factor of the distribution is greater than the kurtosis threshold; and the average value of the corresponding lateral distance is greater than a predetermined distance.

[0030] Further includes: selecting a skewness threshold of 3, a kurtosis threshold of 3, and a predetermined distance between approximately 0.80 meters and 1.0 meters.

[0031] A vehicle includes: a controller having a processor and a tangible non-transitory memory thereon storing instructions, the vehicle being capable of operating in an automated driving mode; a vehicle planning module executable by the controller to generate trajectory planning constrained by a set of planning parameters for the vehicle; wherein the controller is adapted to retrieve a corresponding paving state when the vehicle is traversing a corresponding path, the corresponding paving state being generated by a command unit using aggregated vehicle trajectories of multiple vehicles traversing the corresponding path; wherein the command unit is adapted to designate the corresponding path as an unpaved path when one or more predefined conditions are met, the one or more predefined conditions being based on corresponding lateral distances between the multiple vehicles and a centerline in the corresponding path, the unpaved path being defined by the absence of a centerline marker; wherein the controller is adapted to retrieve the corresponding paving state when the vehicle is traversing an unpaved path and to control the operation of the vehicle in part based on the corresponding paving state; and wherein controlling the operation of the vehicle includes transmitting a takeover request to the user of the vehicle to switch from an automated driving mode to a manual driving mode when the vehicle is traversing an unpaved path.

[0032] One or more predefined conditions include: the absolute value of the skewness factor of the distribution of the corresponding lateral distance is greater than the skewness threshold; the absolute value of the kurtosis factor of the distribution is greater than the kurtosis threshold; and the average value of the corresponding lateral distance is greater than a predetermined distance.

[0033] The foregoing features and advantages, as well as other features and advantages of this disclosure, will become readily apparent when considered in conjunction with the accompanying drawings, based on the following detailed description of the best mode for carrying out this disclosure. Attached Figure Description

[0034] Figure 1 It is a schematic partial diagram of a system for controlling the operation of a vehicle with a controller;

[0035] Figure 2 This is a flowchart of a method for identifying the laying status of a path based on the telemetry of the location of connected vehicles;

[0036] Figure 3 It is control Figure 1 A flowchart of the operation method of a means of transportation;

[0037] Figure 4 It is a schematic partial view illustrating an example vehicle traveling on a path / segment;

[0038] Figure 5 This is a schematic diagram illustrating an example distribution of the corresponding lateral distances of multiple modes of transportation along a path; and

[0039] Figure 6This is a schematic diagram illustrating another example of the distribution of the corresponding lateral distances of multiple modes of transportation along a path.

[0040] Representative embodiments of this disclosure are shown by way of non-limiting example in the accompanying drawings and are described below in additional detail. However, it should be understood that the novel aspects of this disclosure are not limited to the specific forms illustrated in the drawings listed above. Rather, this disclosure will cover modifications, equivalents, combinations, sub-combinations, substitutions, groupings, and alternatives that fall within the scope of this disclosure, as contained in the appended claims, for example. Detailed Implementation

[0041] Referring to the accompanying drawings, the same reference numerals refer to the same parts. Figure 1 A system 10 for controlling the operation of a vehicle 12 is schematically illustrated. The vehicle 12 may include, but is not limited to, passenger cars, SUVs, light trucks, heavy vehicles, minivans, buses, transport vehicles, bicycles, mobile robots, agricultural implements (e.g., tractors), sports-related equipment (e.g., golf carts), boats, airplanes, trains, or other mobile platforms. The vehicle 12 may be an electric vehicle. The vehicle 12 may be part of a fleet of autonomous vehicles. It will be understood that the vehicle 12 may take many different forms and have additional components.

[0042] refer to Figure 1 The vehicle 12 includes one or more sensors S for sensing the surrounding environment. The sensors S may include a radar / lidar unit 14 and a camera 16. The sensors S may include navigation sensors (e.g., GPS) and an inertial measurement unit. It will be understood that the sensors S may be combined with other types of technologies available to those skilled in the art. When the vehicle 12 is in operation, data from the sensors S is transmitted to a vehicle planning module 18, which generates a trajectory plan 20 for the vehicle 12.

[0043] refer to Figure 1 The vehicle 12 can operate in automated driving mode 22 and / or manual driving mode 24. (See reference) Figure 1 The vehicle 12 includes a controller C, which executes an automated driving mode 22 of the vehicle 12 based on trajectory planning 20. Trajectory planning 20 guides the movement of the vehicle 12 and determines appropriate steps for navigating traffic signs, intersections, various roads, and traffic conditions.

[0044] refer to Figure 1 Controller C communicates with the remotely located cloud computing service or command unit 26. (See reference) Figure 1Command unit 26 is adapted to depict a road or path 28 (this term is interchangeable with map segment). Command unit 26 is adapted to generate the paving status of path 28 using aggregated vehicle trajectories of multiple vehicles V traversing path 28 over a predefined time period. Path 28 is designated as an unpaved path when one or more predefined conditions are met. An unpaved path is defined by the absence of a centerline marker or painted markings indicating the center of the path or road. A paved path is defined by the presence of a centerline marker. The paving status of many different paths can be stored in database 30.

[0045] Command unit 26 has an integrated processor and a memory (or a non-transitory tangible computer-readable storage medium) thereon recording instructions for method 100, which is used to identify the laying status of path 28 based on connected vehicle location telemetry, as described below. Figure 2 Description. Command unit 26 may include one or more remote servers hosted on the Internet for storing, managing, and processing data. Command unit 26 may be managed at least in part by personnel at various locations.

[0046] Controller C is adapted to retrieve the paving status from database 30 when vehicle 12 is about to cross a road / path. (Reference) Figure 1 The controller C has at least one processor P and at least one memory M (or a non-transitory tangible computer-readable storage medium) thereon recording instructions for executing method 150, which is used to control the operation of vehicle 12, as described below. Figure 3 The operation of the vehicle 12 is controlled based on the laying status of path 28 obtained by command unit 26. Memory M can store an executable instruction set, and processor P can execute the instruction set stored in memory M.

[0047] As described in detail below, for the purpose of inferring paving status, command unit 26 is adapted to determine the lateral offset from the centerline of path 28. For example, if aggregated lateral behavior indicates that multiple vehicles V are traveling on or across the centerline, the map segment or path 28 is marked as "unpaved"; otherwise, the map segment is marked as "paved." Data can be validated on paved and unpaved roads using naturalistic telemetry data. Under the assumption of no centerline marking, map segments with increased lateral offset and lateral offset variation are marked as unpaved, and drivers cannot maintain a consistent lateral distance from the centerline. System 10 provides an efficient way to perform map update functions on underdeveloped or tertiary roads.

[0048] refer to Figure 1The vehicle 12 includes a telematics module 32 for establishing two-way communication with the command unit 26. Figure 1 As shown in the diagram, the telematics module 32 is adapted to collect telemetry data, such as location, speed, power system data, maintenance requirements, and services, by interfacing with various internal subsystems of the vehicle 12. The telematics module 32 enables vehicle-to-vehicle (V2V) and / or vehicle-to-everything (V2X) communication.

[0049] Now for reference Figure 2 The diagram illustrates a flowchart of an example method 100 for identifying the laying status of the selected path 28. Method 100 may be embodied as computer-readable code or instructions stored on and at least partially executable by command unit 26. Method 100 does not need to be applied in the specific order described herein. Furthermore, it will be understood that some boxes or steps may be omitted.

[0050] Beginning at box 102, command unit 26 is adapted to retrieve vehicle location telemetry data from database 30 to obtain detailed information about path 28. Command unit 26 is adapted to extract the corresponding coordinates and trajectories of multiple vehicles V traversing path 28.

[0051] Proceeding to box 104, method 100 includes processing trajectory data to determine the centerline of path 28 and the corresponding lateral distances between multiple vehicles V. The centerline may be defined as the midline or center line of the road segment and may be specified or determined using satellite imagery. In one embodiment, the trajectory data is converted into a format in which the corresponding coordinates are represented as rows, for example, using a line string format of Structured Query Language (SQL). SQL is a domain-specific language for processing structured data, i.e., data that combines relationships between entities and variables.

[0052] refer to Figure 4 This shows an example path 200 traversed by vehicle 12. (Reference) Figure 4 Path 200 includes a first lane 202, which is adjacent to an opposing second lane 204 and separated by a centerline 206. Vehicle 12 is traversing the first lane 202. At an initial time T1, vehicle 12 is separated from the centerline 206 by a first lateral distance L1, which can be an imaginary centerline (for an unpaved path) or an actual centerline marker (for a paved path). At subsequent times T2 and T3, vehicle 12 is separated from the centerline 206 by corresponding lateral distances L2 and L3.

[0053] System 10 aggregates vehicle location telemetry (e.g., high-speed vehicle telemetry reported every 3 seconds) and compares the calculated trajectory with the centerline of the path obtained from a map database. When lane markings are present (i.e., in a paved path), the vehicle trajectory can be aligned with the road shape, and when lane markings are absent (i.e., in an unpaved path), the vehicle trajectory exhibits alignment discrepancies.

[0054] Proceeding to box 106, command unit 26 is adapted to determine whether a vehicle trajectory threshold has been met, i.e., whether there is a statistically sufficient number of vehicle trajectories for data analysis. If the threshold is not met (box 106 = No), method 100 loops back to box 102. If the threshold is met (box 106 = Yes), method 100 proceeds to box 108 to compare the extracted trajectories of multiple vehicles V.

[0055] Proceeding to box 110, method 100 includes performing analysis to specify the state of path 28. If one or more predefined conditions are met (box 110 = Yes), method 100 proceeds to box 112, where path 28 is marked as "unpaved". If the conditions are not met (box 110 = No), method 100 proceeds to box 114, and path 28 is marked as "paved".

[0056] In one embodiment, the predefined conditions include: (1) a predefined percentage or predefined majority (aggregation) of vehicles V crossing the centerline (e.g., centerline 206 of path 200) at least once; and (2) the average of the corresponding lateral distances (from the centerline) of the multiple vehicles V is greater than a predetermined distance. In one example, the predefined percentage is approximately 50% and the predetermined distance is approximately 0.80 meters.

[0057] Figure 5 This is a schematic diagram of an example distribution 300 of the lateral distances of multiple vehicles V on a map segment or path. Here, line 310 indicates the average value of the distribution, line 320 indicates the path center, line 330 indicates the 25th percentile marker, and line 340 indicates the 75th percentile marker. Figure 5 The diagram illustrates a relatively skewed distribution. Skewness is a statistical measure of how asymmetrical a distribution is or how much it deviates from a symmetrical distribution. The larger the skewness factor of the distribution, the more likely the road is to be unpaved.

[0058] The skewness or asymmetry of the distribution in a dataset can be quantified using Pearson's first or second skewness coefficient or other formulas. Pearson's first skewness coefficient calculates the difference between the mean and mode of the dataset, divided by the standard deviation, while Pearson's second skewness coefficient calculates the difference between the mean and median, multiplied by three, and then divided by the standard deviation.

[0059] Figure 6 This is another example of a distribution 350 illustrating the corresponding lateral distances of multiple vehicles V along a path. Figure 6 The diagram illustrates a distribution with excessive kurtosis. Excessive kurtosis, relative to a normal Gaussian distribution, indicates a larger presence of extreme regions on either side of the center at 350. Here, line 360 ​​indicates the path center, line 370 indicates the 25th percentile, and line 380 indicates the 75th percentile. A standard distribution may have a kurtosis factor of 3. A distribution with an increased kurtosis factor (>3) can be visualized as a thin “bell” with peaks, while a decreased kurtosis factor corresponds to a broadening of the peaks and a “thickening” of the tails.

[0060] In another embodiment, the predefined conditions include: (1) the average of the corresponding lateral distances of the multiple vehicles V is greater than a predetermined distance; (2) the absolute value of the skewness of the distribution of the corresponding lateral distances is greater than a threshold, referred to as the skewness threshold; and (3) the absolute value of the kurtosis of the distribution is greater than a threshold, referred to as the kurtosis threshold. In one example, the predetermined distance is between approximately 0.8 meters and 1.0 meters, the skewness threshold is 3, and the kurtosis threshold is 3.

[0061] Command unit 26 can be adapted to refine the analysis by establishing consistent lateral distances or defining standard deviation thresholds. This helps identify patterns and anomalies in vehicle movement. Additionally, command unit 26 is adapted to identify overlapping lateral trajectories. For example, it can identify instances of centerline crossovers, signaling potential traffic flow overlap and approaching vehicles.

[0062] refer to Figure 2 From boxes 112 and 114, method 100 proceeds to box 116, where the output of the distribution analysis is transmitted to database 30, which stores these parameters (and their corresponding trajectories) as a learning dataset for future use by vehicle 12 and other connected vehicles. Method 100 may then terminate, or retrieve the identifier of the next selected map segment or path to be mapped and repeat the process.

[0063] Now for reference Figure 3A flowchart of an example method 150 for controlling the operation of vehicle 12 is shown. Method 150 may be embodied as computer-readable code or instructions stored on and at least partially executable by controller C. Method 150 does not need to be applied in the specific order described herein. Furthermore, it will be understood that some boxes or steps may be omitted. Method 150 may be executed in real time, continuously, systematically, occasionally, and / or at regular intervals, such as every 10 milliseconds during normal and ongoing operation of vehicle 12.

[0064] exist Figure 3 Beginning at box 152, automated driving mode 22 is initiated for vehicle 12 that is about to begin traversing path 28. Proceeding to box 154, controller C is adapted to acquire data related to path 28, including detailed information about traffic patterns on the corresponding path 28 (e.g., the presence of roundabouts) and other contextual information (e.g., time of day, weather).

[0065] Proceeding to box 156, controller C is adapted, for example, to retrieve the corresponding paving status of path 28 from database 30. If path 28 is paved (box 156 = Yes), method 100 terminates. If path 28 is not paved (box 156 = No), method 150 proceeds to box 158 to determine whether adjustments to the parameters adopted by the vehicle planning module 18 are appropriate. As part of determining trajectory planning 20, each level of the vehicle planning module 18 incorporates different sets of parameters or constraints that limit the set of feasible solutions available to the vehicle planning module 18. Adjustable parameters include the minimum lateral distance and / or minimum longitudinal clearance between the vehicle and adjacent vehicles 208 (see [link to relevant documentation]). Figure 4 Acceptable headway distance between vehicles, permissible speed range, maximum acceleration during vehicle maneuvering (e.g., turning), minimum acceleration during vehicle maneuvering, minimum lateral distance between vehicles, and minimum distance to the obscured object.

[0066] Controller C can be adapted to divide the planning parameter set into a primary list of adjusted parameters and a secondary list of adjusted parameters, where weighting factors create priorities based on parameter adjustments. The primary list of adjusted parameters is adjusted first, before the secondary set. The primary list of adjusted parameters may have a lower cost to performance. For example, in a muddy, unpaved path scenario, maintaining a minimum distance from other vehicles may be a priority.

[0067] Proceeding to box 160, control the operation of vehicle 12 based on the paving status of path 28. Controlling the operation of vehicle 12 may include transmitting a takeover request to the user of vehicle 12 when vehicle 12 is traversing an unpaved path, to switch from automated driving mode 22 to manual driving mode 24.

[0068] Controlling vehicle 12 may include updating vehicle planning module 18 and generating a modified vehicle trajectory using an adjusted set of parameters (from box 158). Controller C is adapted to generate at least one adjusted parameter from the planning parameter set when vehicle 12 is traversing a corresponding path 28 designated as an unpaved path. Vehicle planning module 18 is adapted to generate a modified trajectory plan based on at least one adjusted parameter. An automated driving mode 22 is implemented based on the modified vehicle trajectory. For example, vehicle 12 may reduce speed on an unpaved path or change its navigation route to avoid it. This modification may be based on vehicle type. For example, if vehicle 12 is carrying a load or trailer, the speed reduction on an unpaved path will be greater.

[0069] In summary, system 10 employs a hybrid approach of onboard sensing and data analysis to identify and analyze vehicle movement on tertiary roads to determine the path paving status (paved / unpaved). Command unit 26 is adapted to depict map segments using connected vehicle location data (e.g., aggregated vehicle trajectories). The aggregated vehicle trajectories are compared to the centerline of the map segment to infer the road paving status. For example, aggregated analysis of the average distance of a set of vehicles may indicate that they travel at nearly equidistant distances from the centerline in both traffic directions. This consistent behavior will be reflected in the individual vehicle trajectories of that set, thus indicating that path 28 is paved. Aggregated analysis of the average distance of different sets of vehicles may indicate that they have a higher lateral offset from the centerline compared to paved roads in both directions, where individual vehicle trajectories are dispersed across the path. This indicates that path 28 is unpaved and lacks centerline markings.

[0070] refer to Figure 1The wireless network 34 can be used for communication between the controller C and the command unit 26. The wireless network 34 can be a short-range network or a long-range network. The wireless network 34 can be a communication bus, which can be in the form of a serial controller local area network (CAN bus). The wireless network 34 can be a serial communication bus in the form of a local area network. The local area network can include, but is not limited to, a controller local area network (CAN), a controller local area network with flexible data rates (CAN-FD), Ethernet, Bluetooth, WIFI, and other forms of data. The wireless network 34 can be a wireless local area network (LAN) that uses a wireless distribution method to link multiple devices, a wireless metropolitan area network (MAN) that connects several wireless LANs, or a wireless wide area network (WAN) that covers a large area such as neighboring towns and cities. Other types of network technologies or communication protocols available to those skilled in the art can be employed.

[0071] Figure 1 The controller C includes computer-readable media (also known as processor-readable media), including non-transitory (e.g., tangible) media involved in providing data (e.g., instructions) that can be read by a computer (e.g., by the computer's processor). Such media can take many forms, including but not limited to non-volatile and volatile media. Non-volatile media can include, for example, optical discs or magnetic disks and other permanent storage. Volatile media can include, for example, dynamic random access memory (DRAM), which can constitute main memory. Such instructions can be transmitted via one or more transmission media, including coaxial cables, copper wires, and optical fibers, including wires containing a system bus coupled to the computer's processor. Some forms of computer-readable media include, for example, flexible disks, hard disks, magnetic tapes, other magnetic media, CD-ROMs, DVDs, other optical media, physical media with perforated patterns, RAM, PROMs, EPROMs, FLASH-EEPROMs, other memory chips or cassette tapes, or other media from which a computer can read them.

[0072] The lookup tables, databases, data repositories, or other data stores described herein can include various mechanisms for storing, accessing, and retrieving various types of data, including hierarchical databases, filegroups in file rechargeable energy storage systems, application databases in proprietary formats, relational database management systems (RDBMS), etc. Each such data store can be contained within a computing device employing a computer operating system such as one of those mentioned above and can be accessed via a network in one or more ways. File systems can be accessible from the computer operating system and can include files stored in various formats. In addition to languages ​​used for creating, storing, editing, and executing stored procedures, RDBMS can also employ Structured Query Language (SQL), such as the PL / SQL language mentioned above.

[0073] The flowcharts illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each box in a flowchart or block diagram may represent a module, segment, or portion of code, including one or more executable instructions for implementing one or more specified logical functions. It will also be noted that each box in the block diagrams and / or flowcharts, and combinations of boxes in the block diagrams and / or flowcharts, may be implemented by a dedicated hardware-based storage system or a combination of dedicated hardware and computer instructions that perform the specified functions or actions. These computer program instructions may also be stored in a computer-readable medium that can direct a controller or other programmable data processing apparatus to operate in a particular manner, such that the instructions stored in the computer-readable medium produce an article of art including instructions for implementing the functions / actions specified in the boxes of the flowcharts and / or block diagrams.

[0074] Numerical values ​​of parameters (e.g., numerical values ​​of quantities or conditions) in this specification, including the appended claims, should be understood to be modified by the term "about" in each corresponding instance, regardless of whether "about" actually appears before the numerical value. "About" indicates that the numerical value allows for some slight imprecision (by some method to make the value precise; about or reasonably close to the value; nearly). If the imprecision provided by "about" is not otherwise understood in the art in this ordinary sense, then "about" as used herein at least indicates variations that may arise from common methods of measuring and using such parameters. Furthermore, the disclosure of ranges includes disclosure of each value throughout the range and of further subdivided ranges. Each value within the range and the endpoints of the range are disclosed herein as separate embodiments.

[0075] The detailed description and accompanying drawings are supporting and illustrating this disclosure, but the scope of this disclosure is defined solely by the claims. While some best modes and other embodiments for implementing the claimed disclosure have been described in detail, various alternative designs and embodiments exist to practice the disclosure as defined in the appended claims. Furthermore, the features of the embodiments shown in the drawings or the various embodiments mentioned in this specification are not necessarily to be construed as embodiments independent of each other. Rather, it is possible that each feature described in one example of an embodiment may be combined with one or more other desired features from other embodiments, resulting in other embodiments not described in words or with reference to the drawings. Therefore, such other embodiments fall within the framework of the appended claims.

Claims

1. A system for controlling the operation of a vehicle, comprising: The controller, with a processor and a tangible, non-transitory memory on which instructions are recorded, enables the vehicle to operate in an automated driving mode. The command unit, adapted to generate the corresponding paving status of a path based on the aggregated vehicle trajectories of multiple vehicles traversing the corresponding path, includes: Extract the corresponding coordinates and trajectories of multiple modes of transportation within a predefined time period; and Determine the corresponding lateral distances between multiple modes of transport and the centerlines of their respective routes; The command unit is adapted to designate a corresponding path as an unpaved path when one or more predefined conditions based on the corresponding lateral distance are met; an unpaved path is defined by the absence of a centerline marker. The controller is adapted to retrieve the corresponding paving status when a vehicle is traversing an unpaved path and to control the operation of the vehicle in part based on the corresponding paving status.

2. The system according to claim 1, wherein, Controlling a vehicle involves transmitting a takeover request to the vehicle's user when the vehicle is traversing an unpaved path, in order to switch from automated driving mode to manual driving mode.

3. The system according to claim 1, wherein, The command unit is adapted to transmit the corresponding laying status to the database, and the controller is adapted to retrieve the corresponding laying status from the database.

4. The system according to claim 1, further comprising: The vehicle planning module can be executed by the controller to generate trajectory planning constrained by a set of planning parameters for the vehicle. The controller is adapted to generate at least one adjusted parameter from the planning parameter set when the vehicle is traversing an unpaved path, and the vehicle planning module is adapted to generate a modified trajectory plan based on the at least one adjusted parameter; and The controller is adapted to use modified trajectory planning when the vehicle is on an unpaved path and to discontinue the use of modified trajectory planning when the unpaved path has been completely traversed.

5. The system according to claim 4, wherein, At least one parameter to be adjusted includes the minimum lateral distance and / or minimum longitudinal clearance between the vehicle and adjacent vehicles.

6. The system according to claim 4, wherein: At least one of the parameters to be adjusted includes the maximum speed limit, the maximum acceleration during vehicle maneuvering, and the minimum acceleration during maneuvering; and The controller is suitable for dividing the planning parameter set into a primary list and a secondary list with corresponding weighting factors, with the primary list being adjusted before the secondary list.

7. The system according to claim 1, wherein, One or more predefined conditions include: The predefined percentage of multiple modes of transport crossing the centerline of the corresponding path at least once; and The average value of the corresponding lateral distance is greater than the predetermined distance.

8. The system according to claim 7, wherein, The predefined percentage is 50%, and the predefined distance is 0.80 meters.

9. The system according to claim 1, wherein, One or more predefined conditions include: The absolute value of the skewness factor of the corresponding lateral distance distribution is greater than the skewness threshold; The absolute value of the kurtosis factor of the distribution is greater than the kurtosis threshold; and The average value of the corresponding lateral distance is greater than the predetermined distance.

10. The system according to claim 9, wherein, The skewness threshold is 3, the kurtosis threshold is 3, and the predetermined distance is between approximately 0.80 meters and 1.0 meters.

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