Abstract: A control unit and method for an autonomous and/or semi-autonomous ego vehicle are provided. The control unit is configured to determine a course of an ego lane, referred to as the behavioral ego lane, within which the ego vehicle is driving, based on driving trajectories of a plurality of vehicles within an environment of the ego vehicle. The control unit is configured to operate an automated longitudinal and/or lateral guidance function of the ego vehicle in dependence of the course of the behavioral ego lane.

Abstract: A device may include one or more processors configured to receive sensor data from an external sensor associated with an autonomous driving zone; generate a map of the autonomous driving zone based on the sensor data; determine that a vehicle is entering the autonomous driving zone; and transmit a signal to the vehicle based on the vehicle entering the autonomous driving zone. The signal may cause the vehicle to begin operating in a full autonomous mode. The one or more processors may be configured further to determine an objective associated with the vehicle; receive first data obtained by one or more first sensors associated with the vehicle and second data obtained by the external sensor; determine a route based on the objective, the first data, and the second data; and transmit information identifying the route to the vehicle. The route may allow the vehicle to satisfy the objective.

Abstract: A method of predicting one or more road segment attributes corresponding to a road segment in a geographical area, the method including: providing trajectory data and satellite image of the geographical area; calculating one or more image channels based on the trajectory data; and using at least one processor, classifying the road segment based on the one or more image channels and the satellite image using a trained classifier into prediction probabilities of the road attributes A data processing system including one or more processors configured to carry out a the method of predicting road attributes. A computer executable code including instructions for predicting one or more road segment attributes according to the method.

Abstract: A method of operating an apparatus for predicting and redistributing a personal mobility vehicle (PM vehicle) demand for shared PM vehicles includes generating demand information for the PM vehicles for a plurality of areas according to time, generating current distribution information for the PM vehicles positioned in the plurality of areas, generating target distribution information based on the demand information and the current distribution information, and redistributing the PM vehicles according to the target distribution information.

Abstract: Systems, methods, and devices are disclosed for synchronizing map updates for a navigating autonomous vehicle. A management service on a managing node can receive an update to a portion of a first map, where a limited visibility map, which is a subset of the first map, can be determined based on a geographical area around an autonomous vehicle navigating a route. The limited visibility map can be synchronized among all the nodes while the autonomous vehicle is using the limited visibility map by the management service delivering, to a plurality of downstream nodes, the update to the limited visibility map when the update does not modify a portion of the limited visibility map, and by bypassing, to the plurality of downstream nodes, the update to the limited visibility map when the update modifies a portion of the limited visibility map.

Abstract: The present disclosure relates to lane-level map matching for a vehicle. The method includes receiving vehicle data including a geographical position of the vehicle, a heading of the vehicle, and a speed of the vehicle and receiving sensor data from a perception system of the vehicle. The sensor data includes information about a position of at least one road reference in a surrounding environment of the vehicle. Operations include receiving map data including a lane geometry of the surrounding environment of the vehicle, the lane geometry including a set of candidate lanes. Operations include forming a state space model including a set of states. Each state of the set of states represents a candidate lane of the set of candidate lanes, and defining a cost for going from each state to every other state of the set of states based on the received vehicle data and the received sensor data.

Abstract: Systems and methods are provided for autonomous vehicle passenger safety monitoring following an autonomous vehicle route. In particular, an autonomous vehicle waits for a selected time period after a passenger exits the vehicle. In some examples, the autonomous vehicle remains until the passenger has entered a building at the passenger's destination. In some examples, the autonomous vehicle remains until the passenger is no longer detectable by the vehicle's sensors. During the waiting period, the passenger may choose to re-enter the vehicle.

Abstract: A system for automated formation flight is disclosed. The system may include a formation commander sub-system including a task-based interface configured to receive a sequence of one or more task-based commands along with one or more sets of task-based options for each of the one or more task-based commands from an operator using one or more task-based selectable buttons of the task-based interface. The system may further include a formation manger sub-system communicatively coupled to the formation commander sub-system. Each vehicle of one or more vehicles within one or more teams may be configured to employ the formation manager sub-system. The formation manager sub-system may be configured to receive the one or more task-based commands along with the one or more sets of task-based options for each vehicle to perform.

Abstract: This disclosure is directed to a lane line positioning method and apparatus. The method includes obtaining inertial information, target traveling information, and first position information of a vehicle. The inertial information comprises information measured by an inertial measurement unit of the vehicle. The target traveling information comprises traveling information of the vehicle acquired at a first moment. The first position information comprises a position of the vehicle at the first moment. The method includes determining second position information according to the target traveling information and the first position information and determining third position information of the vehicle at a second moment based on the inertial information of the vehicle and the second position information. The method includes determining a position of a lane line in a map according to the third position information and relative position information.

Abstract: Techniques are disclosed for training one or more cost functions of an autonomous vehicle (“AV”) control system based on difference between data generated using the AV control system and manual driving data. In many implementations, manual driving data captures action(s) of a vehicle controlled by a manual driver. Additionally or alternatively, multiple AV control systems can be evaluated by comparing deviations for each AV control system, where the deviations are determined using the same set of manual driving data.

Abstract: Exemplary embodiments of the present disclosure provide a method and apparatus for determining road information data and a computer storage medium, which may be used for autonomous driving, road information prediction, and driving route planning. The method for determining road information data includes: determining, via a precision navigation device of a vehicle, a plurality of locations of the vehicle; acquiring, via a sensor of the vehicle, a plurality of image frames of a physical environment where the vehicle is located; determining, from the plurality of locations, a target location corresponding to at least one image frame among the plurality of image frames; and determining, based on the determined target location and a map related to the physical environment, road information data corresponding to the at least one image frame. According to the solution of the present disclosure, road information annotation data may be accurately and efficiently generated.

Abstract: This disclosure relates to a distributed data center that includes resources carried by a fleet of vehicles. Individual vehicles carry sensors configured to generate output signals conveying information related to the vehicles and/or the surroundings of the vehicles. The system includes a remote computing server configured to obtain executable code from a user, and subsequently transmit the executable code to individual vehicles in the fleet. Individual vehicles locally execute the executable code to produce local results, and subsequently transfer the results to the remote computing server for presentation to the user.

Abstract: A vehicle control system includes at least one detection device configured to capture detection data and a controller. The controller identifies a parking space for a vehicle in an operating area based on the detection data and identifies a travel path of the vehicle from a current position to a target position aligning the vehicle with the parking space. In response to the travel path, the controller calculates a travel zone occupied by the vehicle traversing the travel path and determines at least one viewing zone proximate to the travel zone. The controller further determines a location of a user based on the detection data and controls a navigation routine of the vehicle along the travel path in response to the location of the user relative to the at least one viewing zone.

Abstract: A vehicular control system includes a plurality of sensors disposed at a vehicle so as to have a combined field of sensing forward, rearward and sideward of the vehicle. Data captured by the sensors as the vehicle moves along a road is processed at a control for detecting objects present exterior the vehicle. The control designates a plurality of locations within the fields of sensing. As the vehicle moves along the road, the control increases a value for each designated location when an object is detected at that designated location, and decreases the value for each designated location when an object is not detected at that designated location, and generates an object map based on values for the designated locations. The greater the value for a particular designated location, the greater the probability an object is present at that particular designated location.

Abstract: A method for operating a brake system of a vehicle. A precontrol value for a brake pressure of the brake system is set by using an admission pressure value representing a admission pressure in the brake system and a processing specification representing a braking dynamics of the vehicle.

Abstract: The present disclosure discloses a method for route optimization based on dynamic window and redundant node filtering, comprising using an existing raster map data set to determine the coordinate information of a starting position and a destination position of movement, and to mark a destination node and an obstacle node in the raster map; using A* algorithm to plan a global route; globally optimizing the global route planned by A* algorithm, and filtering redundant nodes out; combining a dynamic window algorithm to perform the local optimization section by section on the optimized global route so as to obtain a final global route. According to the present disclosure, the combination of algorithms reduces a single movement duration of a mobile robot and improves the smoothness of the movement route curve. At the same time, the problems of the robot occurring on the route during the static driving are alleviated.

Abstract: In a parking assistance device, a target parking position calculation unit calculates a target parking position of a subject vehicle based on a position of a corner point of a parking space. A constraint condition setting unit sets a constraint condition regarding a target parking route for guiding the subject vehicle to the target parking position based on a position and a posture angle of the subject vehicle, peripheral information of the subject vehicle, and the position of the corner point of the parking space. The constraint condition includes a condition that a curvature change rate of the target parking route is continuous. A target parking route calculation unit calculates the target parking route based on the position and the posture angle of the subject vehicle, the position of the corner point of the parking space, the target parking position, and the constraint condition.

Abstract: A parking assistance apparatus for aiding a driver of a motor vehicle with a parking process, having an environment recording unit configured to record environment data of the motor vehicle at least during a parking process, having a storage unit configured to at least temporarily store the parking trajectory performed by the driver during the parking process and the recorded environment data, and having a processing unit configured to determine a trained parking trajectory, wherein in order to determine the trained parking trajectory, the processing unit is configured to check the driver-performed parking trajectory for a more efficient parking trajectory.

Abstract: Presented is a method for predicting the energy consumption of electric motors and using these predictions as one of the factors in planning tasks that are carried out with the assistance of the motors. The method can be used for assigning tasks to robots in an automatic system for picking and placing boxes on shelves in a warehouse. Another application of the method is selecting the most energetically efficient route from several alternative routes for passenger and commercial vehicles comprising battery powered propulsion systems that include electric motors and on-board computers.

Abstract: A method for controlling a parked vehicle includes receiving vehicle identification information from a first terminal, specifying a target vehicle to be controlled based on the vehicle identification information, waking up the target vehicle to be controlled and transitioning the target vehicle to be controlled to a movable state, and transmitting a moving direction to the target vehicle to be controlled.