Vehicle marshaling that combines onboard and infrastructure sensors

Abstract

The present disclosure provides "vehicle marshaling by fusing onboard sensors and infrastructure sensors". A method for marshaling vehicles includes: receiving signals from a set of infrastructure sensors associated with a vehicle management system; processing the signals from the set of infrastructure sensors and signals from one or more sensors on the vehicle; sending the processed signals as one or more vehicle commands to the vehicle; receiving signals from the one or more sensors on the vehicle; and processing the one or more vehicle commands and the signals from the one or more sensors on the vehicle to generate new commands, which are sent to the vehicle to marshall the vehicle to a certain location.

Description

Technical Field

[0001] The present disclosure relates to vehicle formation. More specifically, the present disclosure relates to vehicle formation that integrates onboard sensors and infrastructure sensors. Background Art

[0002] The statements in this section merely provide background information related to the present disclosure and may not constitute prior art.

[0003] In the case of including automatic vehicle marshaling into the manufacturing line off-line process, the vehicle automatically maneuvers between calibration stations without the assistance of a human driver. Sensors installed on the factory infrastructure are used to provide real-time accurate vehicle positioning and wireless communication between the infrastructure and the vehicle for closed-loop control. The infrastructure sensors provide vehicle direct control commands to control the movement of the vehicle along the path. The infrastructure sensing system can accurately determine the vehicle posture information (e.g., x and y position, yaw angle, and velocity) and calculate direct control commands to move the vehicle along the path. Since there may be obstructions around the vehicle, the infrastructure may require many sensors, which becomes a scaling challenge in large areas (e.g., in outdoor parking lots).

[0004] The present disclosure addresses these issues associated with automated teaming of vehicles. Summary of the invention

[0005] This section provides a general summary of the disclosure and is not a comprehensive disclosure of its full scope or all of its features.

[0006] In one form of the present disclosure, a method for marshaling vehicles includes: receiving signals from a set of infrastructure sensors associated with a vehicle management system; processing the signals from the set of infrastructure sensors and signals from one or more sensors on the vehicles; sending the processed signals as one or more vehicle commands to the vehicles; receiving signals from the one or more sensors on the vehicles; and processing the one or more vehicle commands and the signals from the one or more sensors on the vehicles to generate new commands, which are sent to the vehicles to marshall the vehicles to a certain location.

[0007] In a variation of the method that may be implemented individually or in any combination: the one or more vehicle commands and the signals from the one or more sensors on the vehicle are processed in the vehicle management system; the difference between the vehicle command and the new command is sent back to the vehicle management system for coordination to generate a subsequent vehicle command; the vehicle executes the subsequent vehicle command; the signal communicated with the vehicle management system includes a wireless signal; the one or more vehicle commands include at least one of the vehicle's rate of change, speed, torque, and steering; the one or more sensors on the vehicle include at least one of a camera, a lidar, a radar, and an ultrasonic sensor; and the set of infrastructure sensors includes at least one of a camera, a lidar, and a radar.

[0008] In another form, a method for marshaling of vehicles includes: processing one or more vehicle commands based on signals from one or more infrastructure sensors associated with a vehicle management control system; sending the one or more vehicle commands to the vehicle; generating signals from one or more sensors on the vehicle; and processing the one or more vehicle commands and the signals from the one or more sensors on the vehicle to generate new commands for the vehicle. The difference between the one or more vehicle commands and the new command is sent to the vehicle management control system via wireless communication for coordination to generate subsequent vehicle commands. The vehicle executes the subsequent vehicle command to marshall the vehicle to a certain location.

[0009] In a variation of the method that may be implemented individually or in any combination: the one or more vehicle commands and the signals from the one or more sensors on the vehicle are processed in the vehicle management system; the one or more vehicle commands include at least one of the rate of change of velocity, speed, torque, and steering of the vehicle; the one or more sensors on the vehicle include at least one of a camera, a lidar, a radar, and an ultrasonic sensor; and the one or more infrastructure sensors include at least one of a camera, a lidar, and a radar.

[0010] In yet another form, a system for marshaling a plurality of vehicles includes: a set of infrastructure sensors associated with a vehicle management system, signals from the set of infrastructure sensors being processed into one or more vehicle commands; and one or more sensors on each of the plurality of vehicles, the one or more sensors generating signals. The vehicle management system processes the one or more vehicle commands and the signals from the one or more onboard sensors on each of the plurality of vehicles to generate new commands that are sent to each vehicle to marshall each vehicle to a location.

[0011] In a variation of the system that may be implemented individually or in any combination: the new command is processed in the vehicle management system; each of the plurality of vehicles executes its own modified command; the new command takes into account dynamic obstacles within the area; the one or more sensors on each of the plurality of vehicles include at least one of a camera, a lidar, a radar, and an ultrasonic sensor; the set of infrastructure sensors includes at least one of a camera, a lidar, and a radar; and the difference between the vehicle command and the new command is sent back to the vehicle management system for coordination to generate a subsequent vehicle command, and wherein each of the plurality of vehicles executes the subsequent vehicle command.

[0012] Further areas of applicability will become apparent from the description provided herein.It should be understood that the description and specific examples are intended for purposes of illustration only and are not intended to limit the scope of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order that the present disclosure may be better understood, various forms of the present disclosure will now be described by way of example with reference to the accompanying drawings, in which:

[0014] Figure 1 A system for marshaling vehicles according to the principles of the present disclosure is shown;

[0015] Figure 2 It shows that according to the principle of the present disclosure, Figure 1 An exemplary vehicle for marshaling by the system shown in FIG.

[0016] Figure 3 is a block diagram of a system for grouping of vehicles according to the principles of the present disclosure;

[0017] Figure 4A is a flow chart of a process for automatic grouping of vehicles according to the principles of the present disclosure; and

[0018] Figure 4B yes Figure 4A Continuation of the flowchart.

[0019] The drawings described herein are for illustration purposes only and are not intended to limit the scope of the present disclosure in any way. DETAILED DESCRIPTION

[0020] The following description is merely exemplary in nature and is not intended to limit the present disclosure, application, or uses.It should be understood that throughout the drawings, corresponding reference numerals indicate the same or corresponding parts and features.

[0021] The present disclosure describes a system and method for grouping vehicles (such as assigning low-speed autonomous and semi-autonomous vehicles) using a combination of infrastructure (IX) sensors and vehicle sensors (such as, for example, cameras, lidars, radars, ultrasonic devices) to enable low-speed autonomous or semi-autonomous movement of vehicles without a driver. The system can be deployed indoors and outdoors. One or more systems described herein use a wireless centralized fleet management system to provide control of vehicle movement without a driver to guide the movement of each vehicle at any time, thereby improving the efficiency of the entire logistics chain.

[0022] refer to Figure 1 , a system 10 for allocating vehicles 100 (such as autonomous and semi-autonomous vehicles 100) located, for example, in a parking lot is shown. The system 10 includes an IX server 12. The IX server 12 also includes a sensor component 14 that communicates with a set of IX sensors 18 (such as, for example, one or more of a camera, a lidar, a radar, and an ultrasonic device). As the vehicle 100 moves through, for example, a factory floor or a parking lot, the IX sensor 18 monitors the movement of the vehicle. The IX server 12 also includes a wireless communication component that provides communication between the IX server 12 and the vehicle 100.

[0023] Further references Figure 2 In various forms, the vehicle 100 can be different types of vehicles and powered in various known ways, such as with an electric motor and / or an internal combustion engine. The vehicle 100 can be a land vehicle, such as a car, a truck, etc., and / or a robot such as a drone. In some examples, the vehicle 100 includes a controller 110, one or more actuators 120, a plurality of sensors 130 on the vehicle 100, and a human-machine interface (HMI) 140. The vehicle 100 has a reference point 150, i.e., a designated point within the space defined by the vehicle body, for example, a geometric center point where the respective longitudinal and transverse center axes of the vehicle 100 intersect. The reference point 150 identifies the location of the vehicle, for example, a loading location of the vehicle 100 to be loaded onto a transport vehicle.

[0024] The controller 110 is configured to control the operation of the vehicle 100 in an autonomous or semi-autonomous mode. For the purposes of this disclosure, the autonomous mode is defined as a mode in which each of the propulsion and steering of the vehicle is controlled by the controller 110; in the semi-autonomous mode, the controller 110 controls one or both of the propulsion and / or steering of the vehicle 100.

[0025] The controller 110 includes programming to operate one or more of the following: propulsion of the land vehicle (e.g., controlling the rate of change of speed of the vehicle by controlling one or more of an internal combustion engine, an electric motor, a hybrid engine, etc.), steering, climate control, interior and / or exterior lights, etc., and to determine if and when the controller 110 (rather than a human operator) controls such operations. In addition, the controller 110 is programmed to determine if and when a human operator controls such operations.

[0026] The controller 110 includes or may be communicatively coupled to more than one processor (e.g., via a vehicle communication bus as further described below), including, for example, controllers in the vehicle 100 for monitoring and / or controlling various vehicle controllers, such as a powertrain controller, a steering controller, etc. The controller 110 is typically arranged to communicate over a vehicle communication network, which may include a bus in the vehicle 100 (such as a controller area network (CAN), etc.), and / or other wired and / or wireless mechanisms.

[0027] The controller 110 transmits messages to and / or receives messages from various devices (e.g., actuators 120, HMI 140, etc.) in the vehicle 100 via the vehicle network. Alternatively or additionally, where the controller 110 includes multiple devices, the vehicle communication network is used for communication between the devices represented in this disclosure as the controller 110. In addition, as described below, various other controllers and / or sensors provide data to the controller 110 via the vehicle communication network.

[0028] In addition, the controller 110 is configured to communicate with other traffic objects (e.g., vehicles, IX, pedestrians, etc.) through a wireless vehicle communication interface, for example, via a vehicle-to-vehicle communication network and / or a vehicle-to-IX communication network, such as using the wireless communication component 16 of the IX server 12. The vehicle communication network represents one or more mechanisms by which the controller 110 of the vehicle 100 can communicate with other traffic objects, and can be one or more of the wireless communication mechanisms, including any desired combination of wireless (e.g., cellular, wireless, satellite, microwave, and radio frequency) communication mechanisms and any desired network topology (or multiple topologies when multiple communication mechanisms are used). Examples of vehicle communication networks include cellular, IEEE 802.11, Dedicated Short Range Communications (DSRC), and / or Wide Area Networks (WANs) (including the Internet).

[0029] The vehicle actuator 120 is implemented via a circuit, chip or other electronic and / or mechanical component that can actuate various vehicle subsystems according to appropriate control signals. The actuator 120 can be used to control the stopping, speed change rate, speed, torque and steering of the vehicle 100. The controller 110 can be programmed to actuate the vehicle actuator 120 based on the planned speed change rate, including propulsion, steering and / or stopping.

[0030] The vehicle sensors 130 include a variety of devices that provide data to the controller 110. For example, the vehicle sensors 130 may include object detection sensors, such as a lidar sensor disposed on or in the vehicle 100, which provides the relative position, size, and shape of one or more targets (e.g., a second vehicle, a bicycle, a pedestrian, a robot, a drone, etc.) traveling beside, in front of, or behind the vehicle around the vehicle 100. As another example, one or more of the sensors 130 may be a radar sensor fixed to the vehicle bumper, which may provide the position of the target relative to the position of each vehicle 100.

[0031] The sensor 130 configured as an object detection sensor may include a camera sensor that provides images from the area surrounding the vehicle 100, such as to provide a front view, a side view, etc. For example, the controller 110 may be programmed to receive image data from the camera sensor and implement image processing techniques to detect roads, IX elements, etc. The controller 110 may also be programmed to determine the current vehicle position based on position coordinates (e.g., GPS coordinates) received from the position of the vehicle 100 from a GPS sensor.

[0032] The HMI 140 is configured to receive information from a user, such as a human operator, during operation of the vehicle 100. Additionally, the HMI 140 is configured to present information to a user, such as an occupant of one or more of the vehicles 100. In some variations, the controller 110 is programmed to receive destination data, such as location coordinates, from the HMI 140.

[0033] Thus, the vehicle 100 has advanced driver assistance system (ADAS) sensors (e.g., cameras, radars, ultrasonic sensors, etc.) that can facilitate more accurate vehicle positioning, thereby reducing the number of sensors that need to be installed in the infrastructure. Thus, in order to park the vehicle 100 tightly with maximum efficiency, the number of infrastructure sensors required is reduced. For example, the present disclosure describes utilizing on-board sensors to more accurately determine the vehicle's position relative to vehicles in front, behind, or to the right / left to provide assistance in tight parking areas.

[0034] It may be challenging to fuse sensor information from the vehicle sensors 130 and the IX sensors 18. Therefore, one or more examples of the present disclosure include sharing raw sensing information from the vehicle sensors 130 and the IX sensors 18 over a wireless communication channel. For example, a combination of sensing information from different sources is utilized to control a formation of vehicles 100.

[0035] refer to Figure 3 , further details of the system 10 for marshaling vehicles by fusing sensor information from vehicle sensors 130 and IX sensors 18 are shown. The IX server 12 and the vehicle 100 also communicate with the vehicle manufacturing cloud 204 via wireless communications. In addition to the vehicle sensors 130, the vehicle 100 also includes wireless communication modules such as a telematics control unit (TCU) 208 that communicates with a marshaling sensor fusion algorithm 216 and / or other marshaling controllers, a vehicle central gateway module 210, and a vehicle infotainment module 210.

[0036] The group sensor fusion algorithm 216 has a central algorithm 120, an input component 218, and an output component 222. The group sensor fusion algorithm 216 sends and receives signals from a vehicle global navigation satellite system (GNSS) 224 (which includes GPS), a vehicle control area network (CAN) bus 228, a vehicle battery 226, and a vehicle navigation map 215, thereby allowing fusion of sensor data or information.

[0037] Thus, instead of fusing the onboard sensors 130 and the IX sensors 18 at the sensor level (i.e., calculating control actions), the system 10 is configured to fuse the sensors at the controller 110 level utilizing the grouped sensor fusion algorithm 216. Thus, the IX server 12 calculates vehicle commands (e.g., speed rate, velocity, torque, and steering) as if it were the only available sensor array, and transmits those commands to the vehicle 100 for execution.

[0038] Within the controller 110, the vehicle 100 processes both the IX-based commands and the information from the onboard sensors 130 to generate new commands with additional information for the vehicle 100. Any changes to the original commands (e.g., commands based on the fused sensor data) are transmitted back to the IX server 12 for coordination, e.g., to provide any corresponding updated control operations. When the fleet is properly equipped with onboard sensors 130, the system 10 is thus used to effectively fuse the signals from the onboard sensors 130 and the IX sensors 18.

[0039] A specific control implementation of system 10 is described in Figure 4A and Figure 4B300. In operation 306, the IX server 12 calculates the initial vehicle command u based on the information received from the vehicle management system (e.g., fleet manager system) at operation 302 and the information received from operation 304 that provides information from the IX sensor 18. o . For example, the IX server 12 obtains or receives sensor information or data from different sources. Next, at operation 308, the vehicle 100 receives one or more vehicle commands calculated at operation 306. The process 300 then moves to operation 312, which receives the vehicle commands from operation 310 (which include signals from the vehicle sensors 130) and formulates a control obstacle function (CBF). For example, the vehicle commands are processed to generate a CBF, where it is determined at operation 316 whether the vehicle 100 requires evasive action. If it is determined at operation 316 that evasive action is required, the process 300 executes a subsequent vehicle command u in operation 320 and returns to operation 314, so that the vehicle command u is transmitted from the vehicle 100 to the IX server 12, which processes the vehicle command at operation 306. If evasive action is not required (as determined at operation 316), the process 300 continues to execute the initial vehicle command u. o At operation 318, the initial vehicle command is merged with the vehicle command u at operation 324 (e.g., the merged command is based on the fused sensor data). Process 300 then moves to operation 326, where the vehicle 100 follows the command (e.g., controls the vehicle according to one or more new commands based on the fused data).

[0040] Therefore, the IX server 12 calculates the region u o，i The controller 110 of each vehicle 100 processes both the nominal control inputs based on IX for all vehicles and the data from its own sensors 18 to generate new commands u for all vehicles in the area that are considered dynamic obstacles. i . Each vehicle 100 then executes the corresponding modified command for the specific vehicle 100 (e.g., each vehicle 100 executes its own modified command). In this way, each vehicle 100 acts as if the vehicle 100 is a centralized controller that is aware of the nominal control commands for each surrounding vehicle / object, while only executing its own control commands in various examples. In some examples, the process 300 may require additional communication bandwidth to each vehicle 100, but this may result in increased control coordination for the entire fleet.

[0041] As described above, process 300 utilizes CBF, which is an algorithmic tool for imposing constraints on dynamic systems, such as, for example where x is the state of the dynamic system and u is the control input to the functions f(x) and g(x). Specifically, the obstacle constraint h(x) is expressed as an inequality: h(x)>0. Thus, the state x includes elements of the dynamic model, such as vehicle lateral and longitudinal position, forward velocity, and yaw orientation. In the case of vehicle interaction, the state may additionally include elements of multiple dynamic bicycle models.

[0042] Note that operation 312 is such that violating one or more of the obstacle constraints means that evasive action must be taken to prevent the vehicle from being encountered given the obstacle. CBF is generated by means of first-order barrier constrained contact, where L0 is a configurable parameter.

[0043] In some examples, operation 312 also develops a quadratic program (QP) that is executed in the controller 110 to minimize the difference between the nominal (IX-based) control input u0 and the vehicle-computed control input u to prevent contact based on the obstacle constraint given by: Its L f h(x)+L g h(x)u+α h (h(x))≥0 restriction, where L f and L g represents the directional derivative.

[0044] In operation, if the vehicle sensors 130 do not indicate any issues with the command u0 calculated by the IX, no control modification is required and the vehicle executes u0. If the vehicle sensors 130 indicate that action is required compared to what was calculated from the IX server 12, a new control command is executed that ensures contactless operation of the vehicle 100. The new control command is additionally transmitted back to the IX for inclusion in its future control schemes.

[0045] Among other advantages and benefits, the system 10 utilizes non-collocated sensors (i.e., vehicle sensors 130 and IX sensors 18) at the control algorithm level to prevent high bandwidth wireless communications and precise time stamping of data. The system 10 works seamlessly in heterogeneous fleets. IX-based commands are the primary control source, and if the vehicle 100 has additional sensors to enhance the marshaling efficiency of the vehicle 100, all sensors can be directly used in CBF formulation. If all vehicles 100 in the fleet have vehicle sensors 130 fused with IX sensors 18, the number of IX sensors 18 can be greatly reduced, thereby increasing scalability in large spaces (such as, for example, outdoor parking lots).

[0046] Other advantages and benefits include utilizing on-board sensors as a second layer of defense to maximize contactless operation, even if the IX server 12 calculates and transmits an erroneous command, including, for example, variance factors such as wireless communication delays, interference from vulnerable road users, and traffic environment conditions. Thus, the system 10 takes into account situations with moving objects (e.g., pedestrians, cyclists, and other vehicles or equipment).

[0047] Unless otherwise expressly indicated herein, all numerical values ​​indicating mechanical / thermal properties, composition percentages, dimensions and / or tolerances or other characteristics when describing the scope of the present disclosure should be understood to be modified by the word "about" or "approximately". Such modifications are desirable for a variety of reasons, including: industrial practice; material, manufacturing and assembly tolerances; and testing capabilities.

[0048] As used herein, the phrase at least one of A, B, and C should be construed to mean a logical (A or B or C), using a non-exclusive logical "or", and should not be construed to mean "at least one of A, at least one of B, and at least one of C."

[0049] In this application, the terms "controller" and / or "module" may refer to, be part of, or include: an application-specific integrated circuit (ASIC); a digital, analog, or mixed analog / digital discrete circuit; a digital, analog, or mixed analog / digital integrated circuit; a combinatorial logic circuit; a field programmable gate array (FPGA); a processor circuit (shared, dedicated, or group) that executes code; a memory circuit (shared, dedicated, or group) that stores code executed by the processor circuit; other suitable hardware components that provide the described functionality (e.g., an operational amplifier circuit integrator as part of a heat flux data module); or a combination of some or all of the above, such as in a system on a chip.

[0050] The term memory is a subset of the term computer-readable medium. The term computer-readable medium as used herein does not encompass transient electrical or electromagnetic signals propagated through a medium (such as on a carrier wave); therefore, the term computer-readable medium may be considered to be tangible and non-transitory. Non-limiting examples of non-transitory tangible computer-readable media are non-volatile memory circuits (such as flash memory circuits, erasable programmable read-only memory circuits, or mask read-only circuits), volatile memory circuits (such as static random access memory circuits or dynamic random access memory circuits), magnetic storage media (such as analog or digital tape or hard drives), and optical storage media (such as CDs, DVDs, or Blu-ray discs).

[0051] The apparatus and methods described in this application may be implemented partially or completely by a special-purpose computer, which is created by configuring a general-purpose computer to perform one or more functions embodied in a computer program. The functional blocks, flow chart components, and other elements described above are used as software specifications, which can be translated into a computer program by routine work of a technician or programmer.

[0052] The description of the present disclosure is merely exemplary in nature, and thus, variations that do not depart from the essence of the present disclosure are intended to be within the scope of the present disclosure. Such variations should not be regarded as a departure from the spirit and scope of the present disclosure.

[0053] According to the present invention, a method for marshaling vehicles includes: processing one or more vehicle commands based on signals from one or more infrastructure sensors associated with a vehicle management control system; sending the one or more vehicle commands to the vehicle; generating signals from one or more sensors on the vehicle; and processing the one or more vehicle commands and the signals from the one or more sensors on the vehicle to generate new commands for the vehicle, wherein the difference between the one or more vehicle commands and the new commands is sent to the vehicle management control system via wireless communication for coordination to generate subsequent vehicle commands, and wherein the vehicle executes the subsequent vehicle commands to marshall the vehicles to a certain location.

[0054] In one aspect of the invention, said one or more vehicle commands and said signals from said one or more sensors on said vehicle are processed in said vehicle management system.

[0055] In one aspect of the invention, the one or more vehicle commands include at least one of a rate of change of speed, a speed, a torque and a steering of the vehicle.

[0056] In one aspect of the invention, the one or more sensors on the vehicle include at least one of a camera, a lidar, a radar, and an ultrasonic sensor.

[0057] In one aspect of the invention, the one or more infrastructure sensors include at least one of a camera, a lidar, and a radar.

[0058] According to the present invention, a system for marshaling a plurality of vehicles is provided, the system having: a set of infrastructure sensors associated with a vehicle management system, signals from the set of infrastructure sensors being processed into one or more vehicle commands; and one or more sensors on each of the plurality of vehicles, the one or more sensors generating signals, wherein the vehicle management system processes the one or more vehicle commands and the signals from the one or more sensors on each of the plurality of vehicles to generate new commands, the new commands being sent to each of the plurality of vehicles to marshall each vehicle to a certain location.

[0059] According to an embodiment, the new command is processed in the vehicle management system.

[0060] According to an embodiment, each vehicle of the plurality of vehicles executes its own modified command.

[0061] According to an embodiment, the new command takes into account dynamic obstacles within the area.

[0062] According to an embodiment, the one or more sensors on each of the plurality of vehicles include at least one of a camera, a lidar, a radar, and an ultrasonic sensor.

[0063] According to an embodiment, the set of infrastructure sensors includes at least one of a camera, a lidar, and a radar.

[0064] According to an embodiment, the difference between the vehicle command and the new command is sent back to the vehicle management system for coordination to generate a subsequent vehicle command, and wherein each vehicle of the plurality of vehicles executes the subsequent vehicle command.

Claims

1. A method for marshaling vehicles, the method comprising: receiving signals from a set of infrastructure sensors associated with a vehicle management system; processing the signals from the set of infrastructure sensors and signals from one or more sensors on the vehicle; transmitting the processed signal as one or more vehicle commands to the vehicle; receiving signals from the one or more sensors on the vehicle; as well as The one or more vehicle commands and the signals from the one or more sensors on the vehicle are processed to generate new commands that are sent to the vehicle to marshal the vehicle to a location. 2 . The method of claim 1 , wherein the one or more vehicle commands are processed in the vehicle management system. 3 . The method of claim 1 , wherein the signals from the one or more sensors on the vehicle are processed in the vehicle management system. 4 . The method of claim 1 , wherein the difference between the vehicle command and the new command is sent back to the vehicle management system for coordination to generate a subsequent vehicle command. The method of claim 4 , wherein the vehicle executes the subsequent vehicle command. The method of claim 4 , wherein the signal communicated with the vehicle management system comprises a wireless signal. 7 . The method of claim 1 , wherein the one or more vehicle commands include at least one of a rate of change of speed, a speed, a torque, and a steering of the vehicle.

8. The method of claim 1, wherein the one or more sensors on the vehicle include at least one of a camera, a lidar, a radar, and an ultrasonic sensor.

9. The method of claim 1, wherein the set of infrastructure sensors includes at least one of a camera, a lidar, and a radar.

10. The method of claim 1, wherein the new command is processed in the vehicle management system.

11. The method of claim 1 , wherein the new command takes into account dynamic obstacles within the area.

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