Abstract: The present disclosure provides a method comprising identifying at least one of a characteristic and an identity of an item for delivery from an origin to a destination; identifying a plurality of possible routes between the origin and the destination using mapping information, the mapping information including for each of the plurality of possible routes, a characterization of each of a plurality of route segments comprising the possible route; evaluating the plurality of possible routes in view of the identified at least one of the item characteristic and the item identity to select one of the plurality of possible routes; and providing the selected one of the plurality of possible routes to a vehicle, wherein the vehicle delivers the item from the origin to the destination via the identified route.

Abstract: In general, the present disclosure is directed to a time of flight (ToF) sensor arrangement that may be utilized by a robot (e.g., a robot vacuum) to identify and detect objects in a surrounding environment for mapping and localization purposes. In an embodiment, a robot is disclosed that includes a plurality of ToF sensors disposed about a housing of the robot. Two or more ToF sensors may be angled/aligned to establish overlapping field of views to form redundant detection regions around the robot. Objects that appear therein may then be detected by the robot and utilized to positively identify, e.g., with a high degree of confidence, the presence of the object. The identified objects may then be utilized as data points by the robot to build/update a map. The identified objects may also be utilized during pose routines that allow the robot to orient itself within the map.

Abstract: The travel control device, when determining that the traffic congestion is occurred in the other lane, detects, behind another vehicle in the other lane, an approach space; determines whether the approach space meets a predetermined condition; when determining that the approach space meets the predetermined condition, sets the target posture of the own vehicle at the target position behind the other vehicle in the other lane based on the shape of the approach space; and generates a target traveling trajectory from a current position of the own vehicle to the target position. The travel control device controls the motion of the own vehicle so that the own vehicle tracks the target traveling trajectory.

Abstract: Systems and methods for vehicle spatial path sampling are provided. The method includes obtaining an initial travel path for an autonomous vehicle from a first location to a second location and vehicle configuration data indicative of one or more physical constraints of the autonomous vehicle. The method includes determining one or more secondary travel paths for the autonomous vehicle from the first location to the second location based on the initial travel path and the vehicle configuration data. The method includes generating a spatial envelope based on the one or more secondary travel paths that indicates a plurality of lateral offsets from the initial travel path. And, the method includes generating a plurality of trajectories for the autonomous vehicle to travel from the first location to the second location such that each of the plurality of trajectories include one or more lateral offsets identified by the spatial envelope.

Abstract: The present application relates to providing alert notifications of high-risk driving areas in a connected vehicle by calculating a first navigational route between a host vehicle location and a destination, transmitting the first navigational route via a wireless network, receiving via a wireless network an indication of a high-risk area in response to the first navigational route, generating a second navigational route in response to the high-risk area, presenting the second navigational route to a vehicle occupant via a user interface and prompting user action.

Abstract: A controller of a drone includes a storage unit that stores a scene information database containing a plurality of scene information sets arranged in time series of a video, in each of the scene information sets, a relative position with respect to a vehicle in capturing a scene of the video and a duration of the scene are associated with each other, a vehicle information acquisition unit that receives vehicle information from the vehicle, a traveling position estimation unit that estimates a future traveling position of the vehicle based on the vehicle information, and a flight path calculation unit that, based on the estimated traveling position and the scene information database, calculates, for each of the scenes, a flight path that passes through the relative position with respect to the vehicle.

Abstract: A robot moves about an environment and may interact with a user. A waypoint specifies where the robot is to move to with respect to the user while a proxemic cost map is used to plan the path to the waypoint. User input or preferences may be used to modify the waypoint or the proxemic cost map. The waypoint may specify a particular distance and bearing with respect to the user. The proxemic cost map may be oriented with respect to the user and specifies costs for particular areas. For example, an area immediately behind the user may have a very high cost while an area in front of the user may have a low cost. Based on the waypoint and the proxemic cost map, a path is selected and the robot moves along that path, avoiding the high cost areas in favor of the low cost areas if possible.

Abstract: A lawn mower robot may include a plurality of distance sensor units. Each distance sensor unit detects distance information between the lawn mower robot and a fence for partitioning a region. A controller calculates adjacent direction information using each detected distance information. In addition, the lawn mower robot includes a position sensor module. The position sensor module detects position information related to the lawn mower robot. The controller detects whether the lawn mower has deviated from a preset region by using the position information. When the lawn mower robot has deviated, the lawn mower robot can be moved in a direction according to the calculated adjacent direction information and return along the shortest path.

Abstract: A vehicle computing system may identify a scenario in an environment that violates an operating constraint. The vehicle computing system may request remote guidance from a guidance system of a service computing device. The vehicle computing system may receive input from the guidance system including one or more waypoints and/or associated orientations for the vehicle to navigate through the scenario. The vehicle computing system may be configured to validate the input. A validation may include processing the input to determine whether the waypoint(s) and/or orientation(s) associated therewith may cause the vehicle to violate a safety protocol. Based on a determination that the input will not cause the vehicle to violate the safety protocol, the vehicle computing system may control the vehicle according to the input, such as by causing a drive system to operate the vehicle to each waypoint at the associated orientation.

Abstract: A robotic device including one or more proximity sensing systems coupled to various portions of a robot body. The proximity sensing systems detect a distance of an object about the robot body and the robotic device reacts based on the detected distance. The proximity sensing systems obtain a three-dimensional (3D) profile of the object to determine a category of the object. The distance of the object is detected multiple times in a sequence to determine a movement path of the object.

Abstract: Systems and methods for determining appropriate energy replenishment and controlling autonomous vehicles are provided. An example computer-implemented method can include obtaining one or more energy parameters associated with an autonomous vehicle. The method can include determining a refueling task for the autonomous vehicle based at least in part on the energy parameters associated with the autonomous vehicle. The refueling task comprises a first refueling task that is interruptible by a vehicle service assignment or a second refueling task that is not interruptible by the vehicle service assignment. The method can include communicating data indicative of the refueling task to the autonomous vehicle or to a second computing system that manages the autonomous vehicle. The method can include determining whether the refueling task for the autonomous vehicle has been accepted or rejected.

Abstract: The present application relates to a method and apparatus for controlling an ADAS equipped vehicle including a sensor configured for determining a first distance to a first proximate vehicle and a second distance to a second proximate vehicle, a user input operative to receive a user preference, a memory operative to store a map data, a processor operative to generate a current lane score and an adjacent lane score in response to the first distance, the second distance, the user preference, and the map data, the processor being further operative to generate a lane change control signal in response to the adjacent lane score exceeding the current lane score and a vehicle controller operative to perform a lane change operation from a current lane to an adjacent lane in response to the lane change control signal.

Abstract: A cart-based workflow system includes: a robot operating in a facility; a server, the server operably connected to the robot, the server configured to do one or more of send the robot a cart transfer location usable for transferring the cart and instruct the robot to specify the cart transfer location; a graphic user interface (GUI) comprising a map of the facility, the GUI operably connected to the server, the GUI configured to do one or more of receive input from a human user and provide output to the human user, the GUI further configured to be usable by the user to coordinate movement of one or more of robots and carts.

Abstract: A device and method for acquiring captured image data obtained by an unmanned aerial vehicle (UAV), identifying a direction that a target appearing in the captured image data faces, outputting an approach curve used to move the UAV from a current UAV position to a UAV position closer to the face of the person based on the identified direction that the face of the person faces, where the approach curve includes an arc portion connecting the current position to a straight line portion at an approach contact point located a predetermined distance in front of the face of the person, the straight line portion connecting the approach contact point to the position closer to the face of the person.

Abstract: A system, method, infrastructure, and vehicle for performing automated valet parking enable an unmanned vehicle to autonomously move to and park at an empty parking space by communicating with a parking infrastructure. The system, method, infrastructure, and vehicle enable an unmanned vehicle to autonomously move from a parking space to a pickup zone by communicating with a parking infrastructure.

Abstract: A method and apparatus is provided for controlling the operation of an autonomous vehicle. According to one aspect, the autonomous vehicle may track the trajectories of other vehicles on a road. Based on the other vehicle's trajectories, the autonomous vehicle may generate a pool of combined trajectories. Subsequently, the autonomous vehicle may select one of the combined trajectories as a representative trajectory. The representative trajectory may be used to change at least one of the speed or direction of the autonomous vehicle.

Abstract: Disclosed herein is an artificial intelligence cleaner. The artificial intelligence cleaner includes a memory configured to store a simultaneous localization and mapping (SLAM) map for a cleaning space; a driving unit configured to drive the artificial intelligence cleaner; and a processor configured to collect a plurality of cleaning logs for the cleaning space, divide the cleaning space into a plurality of cleaning areas using the SLAM map and the collected plurality of cleaning logs, determine a cleaning route of the artificial intelligence cleaner in consideration of the divided cleaning areas, and control the driving unit according to the determined cleaning route.

Abstract: An automatic diversion management system on-board an aircraft is provided. The diversion management system is configured to automatically detect a need for the aircraft to divert from a primary airport to a diversion airport; automatically initiate diversion planning to a suitable diversion airport responsive to detecting conditions that can cause a need for diversion; automatically create a diversion flight plan; automatically send a clearance request to air traffic control (ATC) for a first type of conditions causing a need for diversion and send a clearance request to ATC, responsive to flight crew action, for a second type of conditions causing a need for diversion; and automatically activate the diversion flight plan after receipt of ATC clearance for the first type of conditions causing a need for diversion and activate the diversion flight plan, responsive to flight crew action, for the second type of conditions causing a need for diversion.

Abstract: A parking space can be identified. A lateral clearance can be identified when a vehicle is parked in the parking space based on identifying a first door of the vehicle to be provided the lateral clearance when the vehicle is parked. A parking position of the vehicle in the parking space can be determined, including a parking bias angle ? between a vehicle longitudinal axis and a parking space longitudinal center axis, and a lateral offset of the vehicle with respect to the parking space longitudinal center axis, based on dimensions of the parking space and the lateral clearance.

Abstract: Methods and systems for controlling a vehicle are herein disclosed. A method includes receiving vehicle data and external data from a vehicle control system of a vehicle and generating an environment representation of an area of the transportation network proximate to the vehicle location. The method includes displaying the environment representation in a GUI and receiving a solution path via the graphical user interface, the solution path indicating a route and one or more stop points. The method includes transmitting the route to the vehicle including a respective geolocation of each of the one or more stop points. The vehicle receives the route and begins traversing the transportation network based on the solution path. The method includes receiving updated vehicle data and/or updated external data from the vehicle and updating the environment representation based thereon. The method includes displaying, the updated environment representation via the graphical user interface.

Abstract: In one embodiment, a lateral drifting error is determined based on at least a current location of an ADV. The lateral drifting error is segmented into a first drifting error and a second drifting error using a predetermined segmentation algorithm. A planning module plans a path or trajectory for a current driving cycle (e.g., planning cycle) to drive the ADV from the current location for a predetermined period of time. The planning module performs a first drifting error correction on the trajectory by modifying at least a starting point of the trajectory based on the first drifting error to generate a modified trajectory. A control module controls the ADV to drive according to the modified trajectory, including performing a second drifting error correction based on the second drifting error.

Abstract: Embodiments of the present disclosure relate to a method and apparatus for controlling vehicle driving. The method includes: generating a global path of a driving site of a vehicle; executing following controlling: generating a local path of a site in front of a current position of the vehicle based on the global path, the local path following a direction of the global path, controlling the vehicle to drive along the local path until reaching an end point of the local path, determining whether the vehicle reaches an end point of the global path, and terminating the controlling if the vehicle reaches the endpoint of the global path; and continuing, in response to determining the vehicle failing to reach the end point of the global path, executing the controlling.

Abstract: A method for determining an idealized passing maneuver includes receiving first data values that represent a passing maneuver of a first vehicle to pass a second vehicle, requesting and receiving surroundings data values that represent instantaneous and/or future surroundings of the first vehicle and/or of the second vehicle, determining a surroundings model of the first vehicle based on the surroundings data values and on a digital map that represents the instantaneous and/or future surroundings of the first vehicle and/or of the second vehicle, determining an idealized passing maneuver for the first vehicle to carry out the passing maneuver based on the surroundings model, and providing the idealized passing maneuver in the form of second data values for receipt by the first vehicle.

Abstract: Autonomous vehicles are capable of executing missions that abide by on-street rules or regulations, while also being able to seamlessly transition to and from “zones,” including off-street zones, with their our set(s) of rules or regulations. An on-board memory stores roadgraph information. An on-board computer is operative to execute commanded driving missions using the roadgraph information, including missions with one or more zones, each zone being defined by a sub-roadgraph with its own set of zone-specific driving rules and parameters. A mission may be coordinated with one or more payload operations, including zone with “free drive paths” as in a warehouse facility with loading and unloading zones to pick up payloads and place them down, or zone staging or entry points to one or more points of payload acquisition or placement. The vehicle may be a warehousing vehicle such as a forklift.

Abstract: Localization error handling using output is described. A computing system associated with a vehicle can receive sensor data from a sensor associated with vehicle. The computing system can determine, based at least partly on the sensor data, a first instruction for controlling the vehicle during a first period of time and a difference in pose information associated with a pose of the vehicle. Based at least partly on determining the difference, the computing system can retrieve a second instruction for controlling the vehicle during a second period of time prior to the first period of time and, based at least partly on comparing the first instruction and the second instruction, the computing system can determine whether the vehicle is to follow the first instruction or perform an alternate operation.

Abstract: A system is disclosed for providing rerouting information based, in part, on a probability of route acceptance. In accordance with further embodiments, the rerouting information is based, in part, on decision tree analyses involving decisions to request and decisions to not request a reroute.

Abstract: A method for controlling an unmanned aerial vehicle (UAV) to track a monitored person is provided. The method includes directing the UAV toward a target location the target location being based on past or present location information provided by a personal monitoring device attached to a monitored person, the location information representing the location of the personal monitoring device; assuming with the UAV a surveillance position relative to the target location; and determining that the monitored device is proximate to the target location by receiving signals from the personal monitoring device and/or observing the monitored person through a camera on the UAV.

Abstract: A control apparatus of a work vehicle includes a course data acquisition unit acquiring course data indicating a traveling condition of a work vehicle that includes a travel route, a travel range data acquisition unit acquiring travel range data indicating a travel range of the work vehicle that is defined with a preset travel width based on the travel route, a detection data acquisition unit acquiring detection data of a detection device that has detected a travel direction of the work vehicle, a prediction unit predicting, based on the detection data, a prescribed position distant from a current position of the work vehicle traveling according to the course data, a determination unit determining whether the prescribed position exists within the travel range, and a drive control unit stopping traveling of the work vehicle when it is determined that the prescribed position does not exist within the travel range.

Abstract: Aspects of the disclosure provide for localizing a vehicle. In one instance, a weather condition in which the vehicle is currently driving may be identified. A plurality of sensor inputs including intensity information, elevation information, and radar sensor information may be received. For each of the plurality of sensor inputs, an alignment score is determined by comparing the intensity information, elevation information, and radar sensor information to a corresponding pre-stored image for each of the intensity information, the elevation information, and the radar sensor information. A set of weights for the plurality of sensor inputs may be determined based on the identified weather condition. The alignment scores may then be combined using the set of weights in order to localize the vehicle.

Abstract: Provided is a multi-information provider system of a guidance robot and a method thereof. The multi-information provider system of a guidance robot may include a user database configured to receive and store user information transmitted from a terminal of a user, a robot database configured to receive pieces of robot information from one or more guidance robots and store the pieces of robot information, a valid robot list generator configured to list pieces of information of guidance robots located within a predetermined effective distance from a location of the user, a service matcher configured to match the user information and each of the pieces of robot information included in a valid robot list, and an outputter configured to output matched service information to the user terminal.

Abstract: Embodiments of the present disclosure relate to a method and apparatus for generating a driving path. The method includes acquiring a two-dimensional image of a driving site obtained by a camera provided on an unmanned aerial vehicle through aerial photography, and a two-dimensional image of a site in front of a vehicle photographed by a camera provided on the vehicle; generating a global map based on the two-dimensional image of the driving site, and generating a local map based on the two-dimensional image of the site in front of the vehicle; and performing path planning based on the global map and the local map, to generate a global path and a local path, the local path following a direction of the global path.

Abstract: A method and system for automatically controlling a vehicle is provided. The method includes generating an original route of travel for a first vehicle for travel from an original location to a destination location. The vehicle is directed from the original location to the destination location such that the vehicle initiates motion and navigates the original route of travel towards the destination location in accordance with the original route of travel. Monitored vehicular attributes of the first vehicle are received and environmental attributes associated with the original route of travel are monitored with respect the first vehicle. Navigational issues associated with the vehicle traveling along the original route of travel are determined based on the monitored vehicular attributes and results of monitoring the environmental attributes. The navigational issues are used to determine if the vehicle should continue to travel along the original route of travel.

Abstract: The invention relates to a method for the at least partially automated operation of a motor vehicle. The method includes ascertaining a planned trajectory to be traversed by the motor vehicle. The method further includes transmitting plan data relating to the planned trajectory from the motor vehicle to a central device on the infrastructure side and evaluating a release condition, the meeting of which depends on the plan data, by means of the central device. The method also includes transmitting a release message from the central device to the motor vehicle if the release condition has been met, and transmitting a modification message from the central device to the motor vehicle if the release condition has not been met. The planned trajectory is ascertained again on the motor vehicle side upon receiving a modification message in order to determine another planned trajectory.

Abstract: A vehicle control system includes: an information acquiring unit that acquires an index value relating to easiness of merging which is evaluated on the basis of at least one of vehicle information relating to an operation of another vehicle that has advanced from a merging lane to a main lane before a subject vehicle and external system information acquired near a merging point using the other vehicle in a case in which the subject vehicle is running in the merging lane merging into the main lane; and an automated driving control unit that executes automated driving of the subject vehicle on the basis of the index value acquired by the information acquiring unit.

Abstract: The autonomous driving ECU includes a first communication unit that transmits and receives autonomous driving data to and from the plurality of data ECUs, and a vehicle control unit that controls a vehicle on the basis of the autonomous driving data transmitted from the plurality of data ECUs. Each data ECU includes a data construction unit that performs a construction of the autonomous driving data transmitted to the autonomous driving ECU, and a second communication unit that transmits and receives the autonomous driving data to and from the autonomous driving ECU. If a predetermined event occurs, among the data ECUs, the data construction unit of the data ECU in which the predetermined event occurs constructs the autonomous driving data so that a total amount of the autonomous driving data transmitted from the data ECU in which the predetermined event occurs is not greater than a predetermined amount of data.

Abstract: In some examples, a first set of image data is received, the first set of image data corresponding to images of a first type and being of a person in an environment of a vehicle and including a first plurality of images of the person over a time interval. In some examples, a second set of image data is received, the second set of image data corresponding to images of a second type and being of the person in the environment of the vehicle and including a second plurality of images of the person over the time interval. In some examples, the first set of image data and the second set of image data are processed to determine a recognized action of the person, which includes using a first neural network to determine the recognized action of the person.

Abstract: A path planning device includes: data acquisition means for acquiring position data of an obstacle; storage means for storing the position data of the obstacle; and path setting means for setting, based on an environmental map, the acquired position data of the obstacle and the position data of the obstacle stored in the storage means, a moving path to a target position, and regularly updating the moving path. The path setting means sets, when the path setting means determines that the acquired obstacle is positioned on a first moving path to the target position after the first moving path is set, a second moving path in which there is no obstacle on a moving path. The storage means stores the position data of the obstacle on the first moving path when the moving load along the second moving path is larger than the moving load along the first moving path.

Abstract: A driver assistance system (10) for a vehicle includes a control unit (11), and a communication device (12) for receiving data from a server (30). The control unit (11) is configured to calculate a trajectory (T) for the vehicle on the basis of sensor data. The control unit (11) is also configured to replace the calculated trajectory (T) for the vehicle (20) with an offboard trajectory (T1) received from the server (30) under certain circumstances.

Abstract: An autonomous mobile robot includes a drive system to support the robot above a surface, a sensor system configured to generate a signal indicative of a location of the robot on the surface, and a controller operably connected to the drive system and the sensor system. The drive system is operable to navigate the robot about the surface. The controller is configured to execute instructions to perform operations including establishing a behavior control zone on the surface, controlling the drive system, in response to establishing the behavior control zone on the surface, to maneuver the robot to a location of the behavior control zone on the surface, and maneuvering, using the drive system, the robot about the surface and initiating a behavior in response to determining, based on the signal indicative of the location of the robot, that the robot is proximate the behavior control zone.

Abstract: An autonomous cart includes an obstacle detecting member, a driving member, a storing section, and a control section. The obstacle detecting member outputs detection information including an obstacle position and obstacle luminance within a planar obstacle-detection region. The storing section stores designated area map information indicating a position of an obstacle within a designated area. At least one command member to which a command for the control section is assigned is included in the obstacle and is disposed within the designated area at a position where execution of the command is desired. The control section controls the driving member based on the designated area map information and a current position of the autonomous cart to cause the autonomous cart to autonomously travel while avoiding the obstacle within the designated area. The control section follows the command detected by the control section based on the obstacle luminance in the detection information.

Abstract: A method includes selecting a landing waypoint on a runway and selecting a starting waypoint based on a location/heading of an aircraft relative to the runway. The method includes selecting additional waypoints between the starting waypoint and the landing waypoint. The starting and additional waypoints include latitude, longitude, and altitude variables. A sequence of waypoints from the starting waypoint to the landing waypoint via the additional waypoints indicates a desired location for the aircraft to traverse. The method includes generating location constraints for the starting and additional waypoints and generating an objective function for optimizing at least one of the variables. Additionally, the method includes generating a solution for the objective function subject to the location constraints. The solution includes latitude, longitude, and altitude values for the variables.

Abstract: The disclosure provides an early notification system to alert a driver of an approaching unsafe autonomous or semi-autonomous driving zone so that a driver may switch vehicle to a non-autonomous driving mode and navigate safely through the identified location. In response, to a determination of an upcoming unsafe autonomous or semi-autonomous driving zone, the driver or system may take appropriate actions in response to the early notification.

Abstract: In various embodiments, methods, systems, and vehicles are provided for executing a lane change for a host vehicle. In various embodiments, one or more sensors obtain sensor data pertaining to target vehicles in proximity to the host vehicle; and a processor at least facilitates: obtaining, using the sensor data, predictions as to future positions and movement of the target vehicle; identifying a plurality of gaps through which the host vehicle may accomplish the lane change, based on the predictions; calculating a cost for each of the plurality of gaps; selecting, a selected gap of the plurality of gaps, having a minimized cost; and executing the lane change for the host vehicle via the selected gap.

Abstract: A state machine controller to dynamically plan a robot's path. An industrial robot such as a multi-arm articulated robot operates in a workspace according to a program. A sensor or camera monitors the workspace and detects any object, such as a person, approaching or entering the workspace. The sensor provides input to the state machine controller, which includes states of; track current path, change speed, and replan path. When an object approaches or enters the workspace, the state machine determines if a transition to the change speed state is necessary. After reducing robot speed in the change speed state, the state machine can resume the original path and speed if the object has cleared the workspace, further reduce speed to zero if necessary to avoid a collision, or transition to the replan path state to compute a new path to the goal position which avoids the object in the workspace.

Abstract: A system, including: a non-transitory memory; and one or more hardware processors coupled to the non-transitory memory and configured to read instructions from the non-transitory memory to cause the system to perform operations including: detecting a first automobile; determining that the first automobile is a self-driving automobile; and in response to determining that the first automobile is a self-driving automobile, causing a second automobile to emulate a motion of the first automobile.

Abstract: An integrated intelligent system includes a first intelligent electronic device, a second intelligent electronic device, a transferable intelligent control device (TICD) and a cross product bus. The first intelligent electronic device performs a first function and the second intelligent electronic device performs a second function. The cross product bus couples the first intelligent electronic device to the transferable intelligent control device. The TICD partially controls behaviors of the intelligent electronic device by sending commands over the cross product bus to the first intelligent electronic device and the TICD partially controls behaviors of the second intelligent electronic device to perform the second function. The TICD is first attached to the first intelligent electronic device to partially control the behaviors of the first electronic device, then detached from the first electronic device, and then attached to the second intelligent electronic device to perform the second function.

Abstract: The present invention relates to an XR device and a method for controlling the same, and more particularly, is applicable to the fields of 5G communication technology, robot technology, autonomous driving technology, and artificial intelligence (AI) technology. The method for controlling an XR device comprises executing a home appliance arrangement application in the XR device by a user, displaying an indoor space on a screen of the XR device, displaying at least one home appliance on the screen of the XR device, selecting the at least one home appliance and a specific space in the indoor space by the user, and guiding at least one of a capacity of the at least one home appliance and an arrangement position of the specific space to the user based on the specific space.

Abstract: A system and method to guide an autonomous vehicle through an area along a path. The area has path markers that define a guidance row. The vehicle has a steering system controlling a steerable wheel to move the vehicle along the path, a control system transmitting steering instructions to the steering system, a guidance system having a data gathering device engaging the path markers and a guidance computer, connected to the control system having a guidance program that calculates the position of the guidance row, the position of the vehicle, the location where the vehicle should be to be on the path and the necessary steering instructions to get on or stay on the path. The path markers can be the trunk of a plant, a post or other upwardly extending member and the data gathering devices can be a LIDAR, radar, camera or other object identification system.

Abstract: In an embodiment, a learning-based dynamic modeling method is provided for use with an autonomous driving vehicle. A control module in the ADV can generate current states of the ADV and control commands for a first driving cycle, and send the current states and control commands to a dynamic model implemented using a trained neural network model. Based on the current states and the control commands, the dynamic model generates expected future states for a second driving cycle, during which the control module generates actual future states. The ADV compares the expected future states and the actual future states to generate a comparison result, for use in evaluating one or more of a decision module, a planning module and a control module in the ADV.

Abstract: Techniques are described herein for improving road safety use cases in a vehicle-to-everything (V2X) communication environment. The techniques include assigning of a plurality of calculated/precalculated geofencing areas on a projected path of a responding emergency vehicle. With the assigned geofencing areas, a remote management network such as a V2X communications server may identify the V2X components (user equipment, traffic lights, vehicle embedded devices, etc.) and send notifications to the identified V2X components in each assigned geofencing area and at different timing periods. The identification of the V2X components and the sending of the notifications at different timing periods improve the traffic awareness between the V2X components in the V2X communication environment.