System for controlling the operation of a vehicle

Abstract

System (10) for controlling the operation of a vehicle (12), comprising: a controller (C) having a processor (P) and a tangible, non-volatile memory (M) in which instructions are recorded, wherein the vehicle (12) is capable of an automated driving mode (22); an instruction unit (26) configured to generate a respective surface condition of a respective path (28) based on aggregated vehicle trajectories of a plurality of vehicles (V) traveling on the respective path (28), comprising: extracting the respective coordinates and respective trajectories of the plurality of vehicles (V) over a predefined time period; and determining the respective lateral distances (L1, L2, L3) between the plurality of vehicles (V) and a centerline (206) in the respective path (28);wherein the command unit (26) is configured to designate the respective path (28) as an unpaved path (28) when one or more predefined conditions based on the respective lateral distances (L1, L2, L3) are met, wherein the unpaved path (28) is defined by the absence of centerline markings; and wherein the control unit (C) is configured to retrieve the respective surface condition and to control the operation of the vehicle (12) partly based on the respective surface condition when the vehicle (12) travels on the unpaved path (28).

Description

introduction

[0001] The present disclosure relates generally to creating a profile for a given path using aggregated vehicle trajectories from a multitude of vehicles traveling on that path, and controlling the operation of a vehicle on that path. An autonomous vehicle can navigate through its environment by using sensors to detect objects and is guided by a vehicle planning algorithm to plan its trajectory. However, the complexity of vehicle movement on tertiary or underdeveloped roads can pose a challenge for autonomous vehicle navigation. Description

[0002] This document presents a system for controlling the operation of a vehicle. The system includes a controller with a processor and tangible, non-volatile memory in which instructions are recorded. The vehicle is capable of automated driving. A command unit is configured to generate the surface condition of a given path based on aggregated vehicle trajectories from a multitude of vehicles traveling on that path. This involves extracting the respective coordinates and trajectories of these vehicles over a predefined time period. The command unit is also configured to determine the lateral distances between these vehicles and a center line on the respective roadway. The path is designated as unpaved if one or more predefined conditions based on these lateral distances are met.The unpaved path is defined by the absence of center line markings.

[0003] The control system is configured to retrieve the current surface condition and partially control the vehicle's operation based on that condition when the vehicle is traveling on unpaved roads. Controlling the vehicle's operation may include sending a takeover request to a vehicle operator to switch from automated to manual driving mode when the vehicle is traveling on unpaved roads.

[0004] The command unit can be configured to transmit the current surface condition to a database, and the controller can be configured to retrieve the current surface condition from the database. The system can include a vehicle planning module that can be executed by the controller to generate a trajectory plan for the vehicle constrained by a set of planning parameters. The controller can be configured to generate at least one adapted parameter in the set of planning parameters when the vehicle travels on the unpaved road. The vehicle planning module is configured to generate a modified trajectory plan based on the adapted parameter. The controller is configured to use the modified trajectory plan while the vehicle is on the unpaved road and to cease using the modified trajectory plan once the unpaved road has been fully traversed.

[0005] The set parameter can specify a minimum lateral distance and / or a minimum longitudinal distance between the vehicle and an adjacent vehicle. The set parameter can also specify a maximum speed limit, a maximum acceleration during a maneuver, and a minimum acceleration during the maneuver. The control system can be configured to divide the set of planning parameters into a primary list and a secondary list, each with its own weighting factor, with the primary list taking precedence over the secondary list for adjustments.

[0006] A given path is designated as an unpaved path if one or more predefined conditions based on the respective lateral clearances are met. In one embodiment, the predefined conditions include: a predefined percentage of the multitude of vehicles that cross the centerline on the respective path at least once, and an average of the respective lateral clearances that is greater than a specified distance. In one example, the predefined percentage is 50% and the specified distance is 0.80 meters.

[0007] In another embodiment, the predefined conditions include: an absolute value of the skewness factor of a distribution of the respective lateral distances is greater than a skewness threshold; the absolute value of a kurtosis factor of the distribution is greater than a kurtosis threshold; and a mean value of the respective lateral distances 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 m and 1.0 m.

[0008] This document describes a method for controlling the operation of a vehicle with a controller comprising a processor, tangible non-volatile memory in which instructions are recorded, and an instruction unit accessible to the controller. The method involves generating a trajectory plan, based in part on a set of planning parameters, through the execution of a vehicle planning module by the controller, enabling the vehicle to operate in an automated driving mode.The method involves generating a respective surface condition of a respective path based on aggregated vehicle trajectories of a multitude of vehicles traversing the respective path, via the command unit, comprising: extracting respective coordinates and respective trajectories of the multitude of vehicles over a predefined period and determining respective lateral distances between the multitude of vehicles and a center line in the respective path.

[0009] The procedure involves determining the route as an unpaved roadway, based on the lateral distances and when one or more predefined conditions are met, via the control unit. The unpaved roadway is defined by the absence of center line markings. The procedure also involves retrieving the surface condition when the vehicle travels on the unpaved roadway via the control unit and controlling the vehicle's operation partly based on the surface condition.

[0010] This document describes a vehicle equipped with a controller, a processor, and tangible, non-volatile memory in which instructions are recorded. The vehicle is capable of automated driving. A vehicle planning module, executable by the controller, generates a trajectory plan for the vehicle constrained by a set of planning parameters. The controller is configured to retrieve the current road surface condition as the vehicle travels along a given path. This road surface condition is generated by an instruction unit using the aggregated vehicle trajectories of a multitude of vehicles traveling along the respective path.

[0011] The command unit is configured to designate a given path as an unpaved road when one or more predefined conditions are met. These conditions are based on the lateral distances between the vehicles and a center line on the path, with the unpaved surface being defined by the absence of center line markings. The control system is configured to retrieve the current surface condition and partially control the vehicle's operation based on this condition when the vehicle is traveling on the unpaved road. Controlling the vehicle's operation involves sending a takeover request to a vehicle operator to switch from automated to manual mode when the vehicle is traveling on the unpaved road.

[0012] The above features and advantages, as well as other features and advantages of the present disclosure, are readily apparent from the following detailed description of the best ways of carrying out the disclosure when considered in conjunction with the accompanying drawings. Brief description of the drawings Fig. Figure 1 is a schematic, fragmentary diagram of a system for controlling the operation of a vehicle with a controller; Fig. Figure 2 is a flowchart for a procedure to identify the surface condition of a road based on the telemetry of the connected vehicle; Fig. 3 is a flowchart for a procedure for controlling the operation of the vehicle of Fig. 1; Fig. Figure 4 is a schematic, fragmentary diagram showing an example vehicle traveling on a path / segment; Fig. Figure 5 is a schematic diagram showing an exemplary distribution of the respective lateral distances of a large number of vehicles on a roadway; and Fig. Figure 6 is a schematic diagram showing another example of the distribution of the respective lateral distances of a large number of vehicles on a roadway.

[0013] Representative embodiments of this disclosure are shown as non-limiting examples in the drawings and are described in more detail below. However, it should be understood that the new aspects of this disclosure are not limited to the specific forms shown in the drawings listed above. Rather, the disclosure is intended to cover modifications, equivalents, combinations, sub-combinations, permutations, groupings, and alternatives that fall within the scope of this disclosure, such as those encompassed by the attached claims. Detailed description

[0014] Referring to the drawings, where identical reference numbers refer to identical components, shows Fig. Figure 1 schematically shows a system 10 for controlling the operation of a vehicle 12. The vehicle 12 can be, but is not limited to, a passenger car, a sport utility vehicle, a light truck, a heavy goods vehicle, a minivan, a bus, a transit vehicle, a bicycle, a self-driving robot, agricultural equipment (e.g., a tractor), sports equipment (e.g., a golf cart), a boat, an aircraft, a train, or another moving platform. The vehicle 12 can be an electric vehicle. The vehicle 12 can be part of a fleet of autonomous vehicles. It is understood that the vehicle 12 can take many different forms and have additional components.

[0015] As in Fig. As shown in Figure 1, the vehicle 12 has one or more sensors S for perceiving its surroundings. The sensors S may include a radar / LiDAR unit 14 and a camera 16. The sensors S may also include a navigation sensor (e.g., GPS) and an inertial measurement unit. It is understood that the sensors S may also include other types of technologies available to those skilled in the art. When the vehicle 12 is in operation, data from the sensors S are transmitted to a vehicle planning module 18, which generates a trajectory plan 20 for the vehicle 12.

[0016] As in Fig. As shown in Figure 1, the vehicle 12 is capable of an automated driving mode 22 and / or a manual driving mode 24. As shown in Fig. As shown in Figure 1, vehicle 12 has a control unit C that executes the automated driving mode 22 for vehicle 12 based on the trajectory plan 20. The trajectory plan 20 guides the movement of vehicle 12 and determines the appropriate steps for navigating through traffic signs, intersections, and various road and traffic conditions.

[0017] As in Fig. As shown in Figure 1, the controller C is in communication with a remote cloud computing service or a command unit 26. As shown in Fig. As shown in Figure 1, the command unit 26 is configured to create a profile of a road or path 28 (the term is used interchangeably with map segment). The command unit 26 is configured to create the surface condition of a path 28 based on the aggregated vehicle trajectories of a large number of vehicles V traveling on the path 28 over a predefined period. A path 28 is designated as an unpaved path if one or more predefined conditions are met. An unpaved path is defined by the absence of centerline markings or painted markings indicating the center of a path or road. A paved path is characterized by the presence of centerline markings. The surface condition of many different paths can be stored in a database 30.

[0018] The command unit 26 has an integrated processor and a memory (or a non-volatile, physical, computer-readable storage medium) on which instructions for a method 100 for identifying the surface condition of a road 28 based on the telemetry of the connected vehicle are recorded, which is referred to below as Fig. 2 is described. Command Unit 26 can have one or more remote servers hosted on the internet to store, manage, and process data. Command Unit 26 can be managed, at least partially, by personnel at different locations.

[0019] Control unit C is configured to retrieve the installation status from database 30 when vehicle 12 is about to enter a road / path. With reference to Fig. 1 The control unit C has at least one processor P and at least one memory M (or a non-volatile, physical, computer-readable storage medium) in which instructions for executing a procedure 150 for controlling the operation of the vehicle 12 are recorded, which is described below with reference to Fig. 3 is described. The operation of the vehicle 12 is controlled based on the surface condition of the road 28, which is determined by the instruction unit 26. The memory M can store executable instruction sets, and the processor P can execute the instruction sets stored in memory M.

[0020] As described in detail below, the command unit 26 is configured to determine the lateral offset from the centerline of path 28 in order to derive the surface condition. For example, if the aggregated lateral behavior indicates that the multitude of vehicles V are traveling on or over the centerline, the map segment or path 28 is marked as "unpaved"; otherwise, the map segment is marked as "paved." The data can be validated on paved and unpaved roads using scientific telemetry data. Map segments with increased lateral offset and lateral offset variations are marked as unpaved, under the assumption that drivers without centerline markings are unable to maintain a consistent lateral distance from the centerline.System 10 offers an efficient way to perform map update functions on underdeveloped or tertiary roads.

[0021] As in Fig. As shown in Figure 1, the vehicle 12 contains a telematics module 32 for establishing two-way communication with the in Fig. The telematics module 32, shown in Figure 1, is configured to acquire telemetry data, such as location, speed, powertrain data, maintenance requirements, and service activity, via interfaces to various internal subsystems of the vehicle 12. The telematics module 32 can enable vehicle-to-vehicle (V2V) and / or vehicle-to-everything (V2X) communication.

[0022] In Fig. Figure 2 shows a flowchart of an exemplary procedure 100 for determining the surface condition of a selected path 28. The procedure 100 can be executed as computer-readable code or as instructions stored on the command unit 26 and at least partially executable by it. The procedure 100 need not be applied in the order shown here. Furthermore, some blocks or steps can be omitted.

[0023] From block 102 onwards, command unit 26 is configured to retrieve telemetry data on vehicle position from database 30 in order to obtain detailed information about route 28. Command unit 26 is configured to extract the respective coordinates and trajectories of a large number of vehicles V traveling on route 28.

[0024] In Block 104, Method 100 involves processing the trajectory data to determine a corresponding lateral distance between a centerline of path 28 and the plurality of vehicles V. The centerline can be defined as the centerline or the centerline of the segment and can be designated or determined using satellite imagery. In one embodiment, the trajectory data is converted into a format in which the respective coordinates are represented as a line, for example, a format for line strings using Structured Query Language (SQL). SQL is a domain-specific language for processing structured data, i.e., data that contains relationships between entities and variables.

[0025] In Fig. Figure 4 shows an example route 200, which is traveled by vehicle 12. As in Fig. As shown in Figure 4, the road 200 comprises a first lane 202, which adjoins a second lane 204 on the opposite side and is separated by a center line 206. The vehicle 12 travels in the first lane 202. At an initial time T1, the vehicle 12 is at a first lateral distance L1 from the center line 206, which can be an imaginary center line (for unpaved roads) or actual center line markings (for paved roads). At the subsequent times T2 and T3, the vehicle 12 is at the respective lateral distances L2 and L3 from the center line 206.

[0026] System 10 aggregates telemetry data on the vehicle's position (e.g., high-speed telemetry data reported every 3 seconds) and compares the calculated trajectory with the centerline of the path from the map database. Vehicle trajectories can align with the road shape if lane markings are present (e.g., on paved roads) and deviate from them if lane markings are absent (e.g., on unpaved roads).

[0027] In Block 106, Command Unit 26 is configured to determine whether a threshold for vehicle trajectories has been reached, i.e., whether a statistically sufficient number of vehicle trajectories are available for data analysis. If the threshold has not been reached (Block 106=NO), Procedure 100 returns to Block 102. If the threshold has been reached (Block 106=YES), Procedure 100 proceeds to Block 108 to compare the extracted trajectories of the multitude of vehicles V.

[0028] In Block 110, Procedure 100 specifies performing an analysis to determine the condition of path 28. If one or more predefined conditions are met (Block 110=YES), Procedure 100 proceeds to Block 112, where path 28 is marked as "unpaved". If the conditions are not met (Block 110=NO), Procedure 100 proceeds to Block 114 and path 28 is marked as "paved".

[0029] In one embodiment, the predefined conditions include: (1) a predefined percentage or a predefined majority (aggregate) of the vehicles V crosses the centerline (e.g., the centerline 206 of path 200) at least once; and (2) an average of the respective lateral distances of the plurality of vehicles V (from the centerline) is greater than a predetermined distance. In one example, the predefined percentage is approximately 50% and the predetermined distance is approximately 0.80 meters.

[0030] Fig. Figure 5 is a schematic diagram showing an exemplary distribution 300 of the respective lateral distances of the multitude of vehicles V on a map segment or a path. Here, line 310 indicates the mean of the distribution, line 320 the midpoint of the path, line 330 the 25th percentile mark, and line 340 the 75th percentile mark. Fig. Figure 5 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 greater the skewness factor of the distribution, the more likely it is that the road is unpaved.

[0031] Quantifying the skewness or asymmetry of a distribution in a dataset can be done using Pearson's first or second skewness coefficients, or with other formulas. Pearson's first skewness coefficient calculates the difference between the mean and the mode of a dataset, divided by the standard deviation, while Pearson's second skewness coefficient calculates the difference between the mean and the median, multiplied by three, and then divided by the standard deviation.

[0032] Fig. Figure 6 is a schematic diagram showing another example distribution 350 of the respective lateral distances of the multitude of vehicles V on a path. Fig. Figure 6 illustrates a distribution with excessive kurtosis. Excessive kurtosis indicates that, compared to a normal Gaussian distribution, there are more extreme regions on both sides of the center of the distribution. Here, line 360 ​​shows the center of the distribution, line 370 the 25th percentile, and line 380 the 75th. A normal distribution can have a kurtosis factor of 3. A distribution with an increased kurtosis factor (>3) can be represented as a thin "bell" with a high peak, while a decreased kurtosis factor corresponds to a broadening of the peak and a "thickening" of the tails.

[0033] In another embodiment, the predefined conditions include: (1) the mean of the respective lateral distances of the plurality of vehicles V is greater than a predetermined distance; (2) the absolute value of the skewness of a distribution of the respective lateral distances is greater than a threshold, referred to as the skewness threshold; and (3) the absolute value of the curvature of the distribution is greater than a threshold, referred to as the curvature threshold. In an example, the predetermined distance is between approximately 0.8 meters and 1.0 meter, the skewness threshold is 3, and the curvature threshold is 3.

[0034] Command Unit 26 can be configured to refine the analysis by specifying uniform lateral distances or defining thresholds for standard deviations. This aids in the detection of patterns and anomalies in vehicle movement. Furthermore, Command Unit 26 is configured to detect overlapping lateral trajectories. For example, it identifies centerline intersections, which indicate potential traffic flow overlap and proximity between vehicles.

[0035] With reference to Fig. 2. Procedure 100 moves from blocks 112 and 114 to block 116, where the output of the distribution analysis is transferred to a database 30, which stores these parameters (and their corresponding trajectories) as a training dataset for future use by vehicle 12 and other connected vehicles. Next, procedure 100 can be terminated, or the identification number for the next selected map segment or the next route to be profiled is retrieved, and the process is repeated.

[0036] In Fig. Figure 3 shows a flowchart of an exemplary procedure 150 for controlling the operation of the vehicle 12. The procedure 150 can be executed as computer-readable code or as instructions stored on the controller C and at least partially executable by it. The procedure 150 need not be applied in the order shown here. Furthermore, some blocks or steps may be omitted. The procedure 150 can be executed in real time, continuously, systematically, sporadically, and / or at regular intervals, e.g., every 10 milliseconds during the normal and ongoing operation of the vehicle 12.

[0037] Starting with block 152 of Fig. 3. Automated driving mode 22 is initiated for a vehicle 12 that is about to travel along a route 28. Control unit C is set up in block 154 to obtain data about route 28, including detailed information about traffic patterns (e.g., the presence of roundabouts) for that route 28 and other contextual information (e.g., time of day, weather).

[0038] Continuing with block 156, control C is configured to retrieve the current surface condition of road 28, for example, from database 30. If road 28 is paved (block 156=YES), procedure 100 ends. If road 28 is not paved (block 156=NO), procedure 150 proceeds to block 158 to determine whether adjustments to the parameters used by vehicle planning module 18 are necessary. As part of determining the trajectory plan 20, each level of vehicle planning module 18 has different sets of parameters or constraints that limit the set of feasible solutions available to vehicle planning module 18. The adjustable parameters include minimum lateral clearance and / or minimum longitudinal clearance between the vehicle and an adjacent vehicle 208 (see Fig. 4) an acceptable distance between vehicles, a permissible speed range, a maximum acceleration during a vehicle maneuver (e.g. turning), a minimum acceleration during a vehicle maneuver, a minimum lateral distance between vehicles and a minimum distance to obscured objects.

[0039] Control C can be configured to divide the set of planning parameters into a primary list of adjustment parameters and a secondary list of adjustment parameters, with weighting factors to prioritize parameter adjustments. The primary list of adjustment parameters is adjusted first, before the secondary set. The primary list of adjustment parameters may have a lower performance cost. For example, on a muddy, unpaved road, maintaining a minimum distance from other vehicles may take precedence.

[0040] Continuing with block 160, the operation of vehicle 12 is controlled based on the surface condition of the road 28. Controlling the operation of vehicle 12 may involve transmitting a takeover request to a user of vehicle 12 to switch from automated driving mode 22 to manual driving mode 24 when vehicle 12 is traveling on the unpaved road.

[0041] Controlling the operation of vehicle 12 may involve using the adapted parameter set (from block 158 onwards) to update the vehicle planning module 18 and generate a modified vehicle trajectory. Control C is configured to generate at least one adapted parameter in the set of planning parameters when vehicle 12 travels on a corresponding path 28, designated as an unpaved road. Based on this at least one adapted parameter, vehicle planning module 18 is configured to generate a modified trajectory plan. Automated driving mode 22 is executed based on the modified vehicle trajectory. For example, vehicle 12 may reduce its speed on unpaved roads or change its navigation route to avoid the unpaved road. This change may be based on the vehicle type.For example, if vehicle 12 is carrying a load or a trailer, the speed reduction on the unpaved road is greater.

[0042] In summary, System 10 uses a combination of onboard sensors and data analysis to identify and analyze vehicle movements on secondary roads in order to determine the road surface condition (paved / unpaved). Command Unit 26 is configured to use location data from connected vehicles (e.g., aggregated vehicle trajectories) to create map segments. These aggregated vehicle trajectories are compared to the road centerlines of the map segments to determine the road surface condition. For example, an aggregated analysis of the average distance traveled by a group of vehicles might indicate that they travel at nearly the same distance from the centerline in both directions. This consistent behavior is reflected in the individual vehicle trajectories of the group, suggesting that Road 28 is paved.An overall analysis of the mean distance of another group of vehicles may indicate that their lateral distance from the center line is greater in both directions compared to paved roads, with the trajectories of individual vehicles scattered across the roadway. This suggests that Route 28 is unpaved and lacks center line markings.

[0043] As in Fig. As shown in Figure 1, a 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 or a long-range network. The wireless network 34 can be a communication bus, which can take the form of a serial Controller 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 Area Network (CAN), a Controller Area Network with Flexible Data Rate (CAN-FD), Ethernet, Bluetooth, Wi-Fi, and other data forms.The wireless network 34 can be a wireless local area network (LAN) that connects several devices via a wireless distribution method, a metropolitan area wireless network (MAN) that connects several wireless LANs, or a wide area wireless network (WAN) that covers large areas such as neighboring cities. Other types of network technologies or communication protocols available to a person skilled in the art may be used.

[0044] The control C of Fig.1. A computer-readable medium (also called a processor-readable medium) comprises a non-volatile (e.g., tangible) medium involved in providing data (e.g., instructions) that can be read by a computer (e.g., by a computer's processor). Such a medium can take many forms, including, but not limited to, non-volatile and volatile media. Non-volatile media include, for example, optical or magnetic disks and other permanent storage devices. Volatile media 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 cable, copper wire, and fiber optic cable, including the lines comprising a system bus connected to a computer's processor.For example, some forms of computer-readable media include a flexible disk, a hard disk, a magnetic tape, another magnetic medium, a CD-ROM, a DVD, another optical medium, a physical medium with hole patterns, a RAM, a PROM, an EPROM, a FLASH EEPROM, another memory chip, or a cartridge or other medium from which a computer can read.

[0045] Lookup tables, databases, data stores, or other data storage devices described herein may have various types of mechanisms for storing, accessing, and querying different types of data, including a hierarchical database, a group of files in a rechargeable energy file storage system, an application database in a proprietary format, a relational database management system (RDBMS), and so on. Each of these data stores may be contained in a device set up with a computer operating system such as one of those mentioned above and may be accessed over a network in one or more different ways. A file system may be accessible from a computer operating system and may contain files stored in various formats.An RDBMS can use the Structured Query Language (SQL) in addition to a language for creating, storing, editing and executing stored procedures, such as the PL / SQL language mentioned above.

[0046] The flowcharts illustrate an architecture, functionality, and operation of possible implementations of systems, procedures, and computer program products of various embodiments of the present disclosure. In this respect, each block in the flowcharts or block diagrams can represent a module, segment, or part of the code comprising one or more executable instructions for implementing the specified logical function(s). It is also noted that each block of the block diagrams and / or flowchart illustrations, and combinations of blocks in the block diagrams and / or flowchart illustrations, can be implemented by special hardware-based storage systems that perform the specified functions or actions, or by combinations of special hardware and computer instructions.These computer program instructions can also be stored in a computer-readable medium that can instruct a controller or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer-readable medium produce a manufactured item that has instructions for carrying out the function / action specified in the flowchart and / or block diagram blocks.

[0047] The numerical values ​​of parameters (e.g., of quantities or conditions) in this specification, including the appended claims, are to be understood as being modified by the term "approximately," regardless of whether "approximately" actually precedes the numerical value. "Approximately" means that the stated numerical value permits a certain degree of inaccuracy (with some approximation to the accuracy of the value; approximately or reasonably close to the value; almost). If the inaccuracy indicated by "approximately" is not understood in this ordinary sense in the technical community, then "approximately," as used here, at least indicates deviations that may arise from ordinary methods of measuring and using such parameters. Furthermore, the disclosure of ranges includes the disclosure of each value and further subdivided ranges within the entire range.Each value within a range and the endpoints of a range are hereby disclosed as separate embodiments.

[0048] The detailed description and the drawings or figures support and describe the disclosure, but the scope of the disclosure is defined exclusively by the claims. While some of the best modes and other embodiments for carrying out the claimed disclosure have been described in detail, various alternative designs and embodiments for carrying out the disclosure exist, which are defined in the accompanying claims. Furthermore, the embodiments shown in the drawings or the features of different embodiments mentioned in this description are not necessarily to be understood as independent embodiments.Rather, it is possible that each of the features described in one of the exemplary embodiments can be combined with one or a multitude of other desired features of other embodiments, leading to other embodiments that are not described in words or by reference to the drawings. Accordingly, such other embodiments fall within the scope of the appended claims.

Claims

[1] System for controlling the operation of a vehicle, comprising: a control system that has a processor and a tangible, non-volatile memory in which instructions are recorded, enabling the vehicle to operate in an automated driving mode; a command unit that is set up to generate a respective surface condition of a respective path based on aggregated vehicle trajectories of a large number of vehicles traveling on the respective path, comprising: Extracting the respective coordinates and trajectories of the multitude of vehicles over a predefined time period; and Determining the respective lateral distances between the multitude of vehicles and a center line in the respective path; wherein the command unit is configured to designate the respective path as an unpaved path when one or more predefined conditions based on the respective lateral distances are met, wherein the unpaved path is defined by the absence of centerline markings; and the control system is set up to retrieve the respective surface condition and to partially control the operation of the vehicle based on the respective surface condition when the vehicle travels on the unpaved road. [2] System according to claim 1, wherein controlling the operation of the vehicle comprises transmitting a takeover request to a user of the vehicle to switch from automated driving mode to manual driving mode when the vehicle travels on the unpaved road. [3] System according to claim 1, wherein the command unit is configured to transmit the respective coating state to a database, and the control unit is configured to retrieve the respective coating state from the database. [4] System according to claim 1, further comprising: a vehicle planning module that can be executed by the controller to generate a trajectory plan for the vehicle constrained by a set of planning parameters; wherein the control system is configured to generate at least one adapted parameter in the set of planning parameters when the vehicle travels on the unpaved road, wherein the vehicle planning module is configured to generate a modified trajectory plan based on the at least one adapted parameter; and The control system is set up to use the modified trajectory plan when the vehicle is on the unpaved road, and to stop using the modified trajectory plan when the unpaved road has been fully traversed. [5] System according to claim 4, wherein the at least one set parameter has a minimum lateral distance and / or a minimum longitudinal distance between the vehicle and an adjacent vehicle. [6] System according to claim 4, wherein: which has at least one set parameter: a maximum speed limit, a maximum acceleration during a vehicle maneuver, and a minimum acceleration during the maneuver; and The control system is set up to divide the set of planning parameters into a primary list and a secondary list with respective weighting factors, with the primary list being prioritized over the secondary list for adjustment. [7] System according to claim 1, wherein one or more of the predefined conditions are: a predefined percentage of the multitude of vehicles that cross the center line at least once on the respective path; and an average of the respective lateral distances is greater than a predetermined distance. [8] System according to claim 7, wherein the predefined percentage is 50% and the predetermined distance is 0.80 meters. [9] System according to claim 1, wherein one or more of the predefined conditions are: an absolute value of a skewness factor of a distribution of the respective lateral distances is greater than a skewness threshold; the absolute value of a kurtosis factor of the distribution is greater than a kurtosis threshold; and an average of the respective lateral distances is greater than a predetermined distance. [10] System according to claim 9, wherein the skewness threshold is 3, the hull threshold is 3 and the predetermined distance is between about 0.80 m and 1.0 m.

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