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: 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 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: 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 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: 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: 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.

Abstract: Disclosed are devices, systems and methods for the operational testing on autonomous vehicles. One exemplary method includes configuring a primary vehicular model with an algorithm, calculating one or more trajectories for each of one or more secondary vehicular models that exclude the algorithm, configuring the one or more secondary vehicular models with a corresponding trajectory of the one or more trajectories, generating an updated algorithm based on running a simulation of the primary vehicular model interacting with the one or more secondary vehicular models that conform to the corresponding trajectory in the simulation, and integrating the updated algorithm into an algorithmic unit of the autonomous vehicle.

Abstract: A fully floating contact redirecting device for a cleaning robot, wherein a contact unit is floatingly disposed on a surface of a robot body in a forward direction, and at least one sensing unit is respectively disposed on opposite sides of the contact unit in a direction opposite to the forward direction. An angle at which the robot body is retracted and turned to avoid a wall or an obstacle is determined by a position where the contact unit goes into contact with the sensing unit after the contact unit touches the wall or the obstacle, thereby solving the problem of going through multiple turns to move in an obstacle-free direction and improving the cleaning efficiency of the cleaning robot.

Abstract: An obstacle-avoidance control method comprises acquiring a distance between an unmanned aerial vehicle (UAV) and a front object in a flying direction of the UAV; and controlling a flying altitude of the UAV according to the distance between the UAV and the front object.

Abstract: The disclosure includes embodiments for generating improved anomaly maps. In some embodiments, a method for a connected vehicle includes detecting an occurrence of an anomaly in a roadway environment based on sensor data describing the roadway environment. The method includes creating, by the connected vehicle, an anomaly map that describes the anomaly. The method includes modifying an operation of a communication unit of the connected vehicle to receive one or more other anomaly maps describing the anomaly from one or more cooperation endpoints in the roadway environment. The method includes generating an updated anomaly map based on the anomaly map created by the connected vehicle and the one or more other anomaly maps created by the one or more cooperation endpoints so that an accuracy of the updated anomaly map is improved.

Abstract: A self-moving device, including: a housing, provided with a motor; a moving module, including a track, the track, driven by the motor, moving the self-moving device; a working module; a control module, configured to control movement of the moving module and working of the working module; and a first sensor and a second sensor, configured to detect an obstacle in a moving direction of the self-moving device. The first sensor is configured to detect a first area in the moving direction, the second sensor is configured to detect a second area in the moving direction, and the first area and the second area are arranged perpendicular to the moving direction. The control module controls a moving manner of the self-moving device according to sensing results of the first sensor and the second sensor.

Abstract: A first reference line representing a route from a first location to a second location associated with an autonomous driving vehicle (ADV). In response to the first reference line multiple sets of sample points are generated based on the first reference line. Each set of sample points includes a first subset of sample points and a second subset of sample points that are offset from the first subset of sample points. A plurality of segments is generated between the multiple sets of sample points. A path for the ADV is generated based on the plurality of segments. The path includes one sample point from each of the multiple sets of sample points.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining routing. An exemplary method comprises: inputting a plurality of to-be-optimized routing solution candidates to a Siamese neural network comprising a plurality of value prediction networks, each of the value prediction networks being trained to predict a cost associated with a to-be-optimized routing solution candidate; identifying one or more to-be-optimized routing solution candidates from the plurality of to-be-optimized routing solution candidates based on outputs of the Siamese neural network; inputting the one or more identified to-be-optimized routing solution candidates to a routing optimizer to obtain one or more optimized routing solution candidates; and determining an optimized routing solution with a lowest cost from the one or more optimized routing solution candidates.

Abstract: The invention relates to a method for assisting a user of a motor vehicle when driving the motor vehicle. A travel route is provided by a navigation apparatus, and a route actually being driven by the motor vehicle is ascertained. A comparison is made between the actual driving route ascertained and the travel route provided, and if a deviation criterion is met, it is ascertained that the motor vehicle has left the travel route provided. As a function of the ascertained departure from the travel route provided, at least one geo-object from a predefined category of geo-objects is established, the established geo-object is predefined as a geo-object having a user-specific interest and, as a function of the predefined geo-object, the established travel route is changed to an alternative route to the destination with the predefined geo-object as an intermediate destination.

Abstract: The invention discloses a training system for autonomous driving control policy, which comprises a simulator construction module based on machine learning, a driving control policy search module based on confrontation learning, and a driving control policy model transfer module.

Abstract: A driving environment is perceived based on sensor data obtained from a plurality of sensors mounted on the ADV. In response to a request for changing lane from a first lane to a second lane, path planning is performed. The path planning includes identifying a first lane change point for the ADV to change from the first lane to the second lane in a first trajectory of the ADV, determining a lane change preparation distance with respect to the first lane change point, and generating a second trajectory based on the lane change preparation distance, where the second trajectory having a second lane change point delayed from the first lane change point. Speed planning is performed on the second trajectory to control the ADV to change lane according to the second trajectory with different speeds at different point in time.

Abstract: A conveyance amount controlling apparatus includes a control state detector, a road surface state detector, and at least one conveyance amount controller including a conveyance device conveying, to a driver, information representing a road surface state and a conveyance amount controlling device controlling a vibration conveyance amount as a conveyance amount of a vibration caused by a road surface irregularity. A second conveyance amount, as the vibration conveyance amount obtained when a road surface state amount less than a first threshold is detected by the road surface state detector, is less than a first conveyance amount, as the vibration conveyance amount obtained when execution of an automatic driving control is not detected by the control state detector. A third conveyance amount, as the vibration conveyance amount obtained when the road surface state amount equal to or greater than the first threshold is detected, is greater than the second conveyance amount.

Abstract: A method for controlling an autonomous construction vehicle may include defining a boundary of a construction site and automatically creating a site plan for navigating the autonomous construction vehicle within the boundary. The site plan includes a work area within the boundary, a maneuver area positioned between the work area and the boundary, a start point for the autonomous construction vehicle, and a path for the autonomous construction vehicle. A controller can then provide the site plan for review and activate autonomy mode to automatically control the autonomous construction vehicle according to the site plan.

Abstract: Transportation equipment includes a controller configured to perform at least steering, acceleration and deceleration to control traveling of the transportation equipment, a sight line detector for detecting a sight line of an occupant of the transportation equipment, and a display configured to display a sight line guidance pattern used to guide the sight line of the occupant. The controller causes the display to display the sight line guidance pattern while the transportation equipment is traveling, determines whether the sight line of the occupant detected by the sight line detector moves to a vicinity of a position at which the sight line guidance pattern is displayed, and continues or stops the traveling of the transportation equipment based on a result of the determination.

Abstract: A method for coordinating a plurality of vehicles (102, 104) comprising: defining, as a command vehicle (C), a vehicle in the plurality; storing, by one or more storage devices (204) located on one or more of the vehicles (102, 104), a list of capabilities of each vehicle (102, 104); receiving, by one or more processors (202) on the command vehicle (C), a specification of a goal; based on the stored vehicle capabilities, allocating, by the one or more processors (202), to one or more of the vehicles (102, 104), one or more tasks, the one or more tasks being such that, if each of those tasks was to be performed, the goal would be accomplished; and sending, from the command vehicle (C), to each vehicle (102, 104) to which a task has been allocated, a specification of the one or more tasks allocated to that vehicle (102, 104).

Abstract: A travel control apparatus is provided. The travel control apparatus includes: a travel control unit that controls the travel of the vehicle in the control state of one of the manual travel control state and the automatic travel control state in accordance with a selection by the driver; a concentration disturbing matter detection unit that detects an occurrence of a predetermined concentration disturbing matter set as a matter which disturbs a concentration of the driver with respect to the driving operation; and a control state switching unit that switches the control state from the manual travel control state to the automatic travel control state when the occurrence of the concentration disturbing matter is detected while the control state is the manual travel control state.

Abstract: There is provided an autonomous travel system with which a travel route of an autonomous travel device can be easily set. The autonomous travel system includes an autonomous travel device (2), a line (1) for guiding travel that is placed on a travel route traveled by the autonomous travel device (2), and a marker (3) that is placed on the travel route. To the marker (3), operation control information related to an operation of the autonomous travel device (2) is recorded so as to be readable. The autonomous travel device (2) includes a detection unit (line sensor (21)) that detects the line (1), an acquisition unit (detection sensor (22)) that acquires the operation control information from the marker (3), and a control unit (23) that controls an operation of the autonomous travel device (2) on the basis of a detection result from the detection unit and the operation control information acquired by the acquisition unit.

Abstract: An unmanned aerial vehicle may include a flight control circuit configured to control flight of the unmanned aerial vehicle and to provide a flight path based at least on an actual position of the unmanned aerial vehicle and a desired target position for the unmanned aerial vehicle; and at least one sensor configured to monitor an environment of the unmanned aerial vehicle and to detect one or more obstacles in the environment; wherein the flight control circuit is further configured to determine a local flight path to avoid a collision with one or more detected obstacles, and to superimpose the flight path with the local flight path, thereby generating a flight path to the desired target position avoiding a collision with the one or more detected obstacles.

Abstract: Systems and methods are disclosed for dynamically adjusting effective sensor coverage coordinates of a sensor used to assist in navigating an autonomous driving vehicle (ADV) in response to environmental conditions that may affect the ideal operation of the sensor. An ADV includes a navigation system and a safety monitor system that monitors some, or all, of the navigation system, including monitoring: dynamic adjustment of effective sensor coverage coordinates of a sensor and localization of the ADV within a high-definition map. The ADV safety monitor system further determines safety-critical objects surrounding the ADV, determines safe areas to navigate the ADV, and ensures that the ADV navigates only to safe areas. An automated system performance monitor determines whether to pass-through ADV navigation control commands, limit one or more control commands, or perform a fail-operational behavior, based on the ADV safety monitor systems.

Abstract: The disclosure relates to a method for operating a piloted motor vehicle, comprising the following steps carried out by a control device: determining a parking time period and a parking location of the motor vehicle on the basis of an appointment calendar signal received from a mobile terminal, which appointment calendar signal describes at least one appointment and a waiting location of the motor vehicle associated with the appointment, and creating an operating plan for the motor vehicle in accordance therewith. In accordance with at least one task signal, each of which describes a travel destination to which the motor vehicle should drive, a linking route for linking at least one travel destination to the parking location and a corresponding travel time are determined.

Abstract: Disclosed are methods and systems for environment detection in which a first vehicle detects its vehicle environment with at least one sensor, wherein the first vehicle transmits sensor data of the sensor pertaining to its vehicle environment to an off-board server device; at least one second vehicle with at least one sensor transmits sensor data of the sensor pertaining to its vehicle environment to the off-board server device; the off-board server device merges the transmitted sensor data of the vehicles and generates an environmental model of the vehicle environment of the first vehicle on the basis thereof; the environmental model that is generated is subsequently transmitted by the off-board server device to the first vehicle.

Abstract: A method of navigational path planning for a mobile automation apparatus includes: obtaining an apparatus localization in a common frame of reference and a localization confidence level; detecting an obstacle boundary by one or more apparatus sensors; obtaining an obstacle map indicating the obstacle boundary in the frame of reference; generating a dynamic perimeter region of the obstacle boundary defining obstruction probabilities for respective distances from the obstacle boundary according to the localization confidence level; obtaining an environmental map indicating a predefined obstacle boundary; generating, for the predefined obstacle boundary, a static perimeter region defining obstructed space; identifying an obstructed portion of the dynamic perimeter region based on the obstruction probabilities and the apparatus localization; generating a navigational path traversing unobstructed space, that excludes the obstructed portion of the dynamic perimeter region, and the static perimeter region; and contr

Abstract: According to one embodiment, a method, computer system, and computer program product for cloud integration for autonomous vehicles is provided. An embodiment may include receiving a location for the autonomous vehicle from a global positioning system, may also include determining a rule area in which the autonomous vehicle is located based on the received location, may include identifying a traffic rule set associated with the determined rule area, may also include, in response to determining that the identified traffic rule set is not available for the determined rule area, transmitting a manual mode alert to a user, and may include enabling a manual mode in the autonomous vehicle.

Abstract: A method for providing data for a first trajectory and a second trajectory where trajectory data relating to the first and second trajectories are captured. Trajectory database data are generated for the first and second trajectories based on the captured trajectory data, and the trajectory database data are stored in a non-volatile way. A trajectory comparison of the first and second trajectories is carried out based on the captured trajectory data, and at least one common section is determined during the trajectory comparison based on the first and second trajectories. The common section is stored as a common data structure for the first and second trajectories. Also disclosed is a system for providing data for a first trajectory and a second trajectory having a trajectory capture unit, a computing unit, and a memory unit.

Abstract: Disclosed are a vehicle capable of projecting visual information used to guide driving or parking on a road and a control method therefor. The method of displaying information on a road for a vehicle includes recognizing a traveling state, determining at least one of a location or a curvature of a laser assistance line that is to be projected on a road from a front laser projector or a rear laser projector based on the recognized traveling state and a steering angle of the vehicle, and projecting the laser assistance line based on a result obtained from the determining.

Abstract: Disclosed herein are systems and methods for providing supplemental identification abilities to an autonomous vehicle system. The sensor unit of the vehicle may be configured to receive data indicating an environment of the vehicle, while the control system may be configured to operate the vehicle. The vehicle may also include a processing unit configured to analyze the data indicating the environment to determine at least one object having a detection confidence below a threshold. Based on the at least one object having a detection confidence below a threshold, the processor may communicate at least a subset of the data indicating the environment for further processing. The vehicle is also configured to receive an indication of an object confirmation of the subset of the data. Based on the object confirmation of the subset of the data, the processor may alter the control of the vehicle by the control system.

Abstract: A method and system for guiding a self-driving vehicle. The vehicle comprises an ultrasound-based proximity sensing system. The method comprises determining a location and an orientation of the vehicle in a predetermined coordinate system; in the vehicle, receiving a predetermined route from the traffic control unit; by a vehicle control unit, controlling the vehicle to travel along the predetermined route while estimating a vehicle travel path; receiving an ultrasound signal from a beacon having a known location in the predetermined coordinate system, wherein the ultrasound signal transmitted by the beacon uniquely identifies the beacon location; determining a relative position of the vehicle in relation to the beacon by means of ultrasound signals transmitted between the beacon and the vehicle; and determining a location of the vehicle in the predetermined coordinate system based on the determined relative position of the vehicle and the known location of the beacon.

Abstract: An automatic driving system includes at least one electronic control unit configured to: generate a traveling plan so as to moderate a change in behavior of a vehicle at a time when an automatic driving control of the vehicle is started by an automatic engagement compared to a change in the behavior of the vehicle at a time when the automatic driving control is started by a triggered engagement, the automatic engagement being an engagement in which the automatic driving control is automatically started when an automatic engagement condition is satisfied, the triggered engagement being an engagement in which the automatic driving control is started when an automatic driving start condition is satisfied and an automatic driving start trigger is input by an occupant; and execute the automatic driving control by controlling the behavior of the vehicle based on the traveling plan, using an actuator equipped in the vehicle.

Abstract: Methods and systems are provided for reducing bleed emissions and exhaust emissions from a vehicle that may be operated autonomously as well as part of a car-sharing model. A parking location of the vehicle is selected at the end of a vehicle event requested by an operator as a function of fuel system and evaporative emissions system variables such that the solar loading of the parking location enables reduced emissions. The parking location selection is further coordinated with the pick-up time and location of a subsequent vehicle event requested by another vehicle operator.

Abstract: Systems and methods for controlling the motion of an autonomous vehicle are provided. In one example embodiment, one or more computing devices on-board an autonomous vehicle receive one or more constraint files including constraint data descriptive of one or more geographic identifiers (e.g., a polygon) and an application type (e.g., partial inclusion, complete inclusion, partial exclusion, complete exclusion) associated with each of the one or more geographic identifiers. Map data descriptive of the identity and location of different travel ways within the surrounding environment of the autonomous vehicle is accessed. A travel route for navigating the autonomous vehicle is determined, wherein the travel route is determined at least in part from the map data evaluated relative to the constraint data. Motion of the autonomous vehicle can be controlled based at least in part on the determined travel route.

Abstract: Systems and methods for guiding autonomous vehicles by monitoring the entire planned path and sending alert messages to a vehicle management system for delays, reroute, or emergency stop to avoid collision with an obstruction. The system initiates alternative paths when the primary path is blocked and is capable of reporting a vehicle identifier and the current positions of the vehicle and any obstruction along the planned path of the autonomous vehicle.