Abstract: At least one object is detected, via a sensor, in a direction of movement ahead of a host vehicle. A current sensor range is determined based on the detected at least one object. A maximum sensor range is determined based on the sensor. The current sensor range is compared with the maximum sensor range. Upon determining the current sensor range is less than the maximum sensor range by at least a predetermined threshold, driving parameters of the host vehicle are updated based on the current sensor range.

Abstract: A traveling lane planning device has a processor configured to assess whether or not an approach zone exists on an adjacent lane between an event location and the current location of a vehicle, when the traveling lane plan includes a lane change from the traveling lane to the adjacent lane before the event location, to create a lane change plan in which the vehicle moves from the traveling lane to the adjacent lane after the vehicle has passed along the approach zone of the adjacent lane when it has assessed that the approach zone exists and to cause the vehicle to carry out a notification action which gives notice to the surrounding area of the vehicle that the vehicle will make a lane change from the traveling lane to the adjacent lane while the vehicle is traveling in the traveling lane along the approach zone of the adjacent lane.

Abstract: An Aerial Robotics Network (ARN) Management Infrastructure (MI) (also referred to as ARNMI) that provides a mechanism for the management of aerobots.

Abstract: A system for evaluating behavior of vehicles is provided. The system includes an input device configured to receive a request for evaluation of behavior of vehicles, one or more processors, one or more memory modules communicatively coupled to the one or more processors; and machine readable instructions stored in the one or more memory modules. The machine readable instructions, when executed by the one or more processors, cause the system to: collect log files related to vehicles from a plurality of sources, a format of log files from one source being different from a format of log files from another source, extract one or more parameters for the vehicles from the collected log files based on the request for evaluation, and evaluate behavior of the vehicles based on the extracted one or more parameters, wherein the one or more parameters include time series and time intervals.

Abstract: Methods, devices and systems enable controlling an autonomous vehicle by identifying a vehicle that is within a threshold distance of the autonomous vehicle, determining an autonomous capability metric (ACM) the identified vehicle, determining whether the ACM of the identified vehicle is greater than a first threshold, determining whether the ACM of the identified vehicle is less than a second threshold, and adjusting a driving parameter of the autonomous vehicle so that the autonomous vehicle is more or less reliant on the capabilities of the identified vehicle based on whether the ACM of the identified vehicle exceeds the thresholds.

Abstract: A method for controlling an unmanned aerial vehicle (“UAV”) includes obtaining depth data of one or more obstacles in a flight space. The method also includes determining information of an obstacle that triggers an obstacle avoidance operation based on the depth data. The method further includes transmitting the information of the obstacle to a control terminal of the UAV.

Abstract: A collision avoidance support device comprises target detection unit, target type determination unit, relative position determination unit, target track prediction unit, and vehicle track prediction unit, obstacle determination unit. The vehicle track prediction unit is configured to enlarge the width of a vehicle predicted track compared with a case where an enlargement condition is not satisfied when the enlargement condition is satisfied. The enlargement condition is satisfied when the relative position determination unit detects that a target determined to be a pedestrian by the target type determination unit is positioned on a travel lane at least once.

Abstract: A method of determining a target lateral acceleration of a vehicle for use in autonomous control of the vehicle to drive along a road, comprising: evaluating each of a plurality of scalar velocity functions at a plurality of key lateral positions predefined with respect to a model of the road to generate a respective set of scalar velocity values; combining the velocity values calculated for each key lateral position to generate a respective target lateral velocity value, the velocity values calculated for each of the key lateral positions being combined by adding the greatest of zero and the velocity values, to the smallest of zero and the velocity values; generating a lateral velocity field by interpolating between the target lateral velocity values; and determining the target lateral acceleration of the vehicle using the lateral velocity field and a measured lateral velocity of the vehicle.

Abstract: A method for depicting location attributes in a map environment. The method includes receiving a request for parameters about a first type of location. The method includes determining a first set of directional arrows, where each directional arrow is associated with a location and has a first set of properties based on the parameters about the first type of location. The method further includes determining a selection of a first directional arrow, which is associated with a first location, from the first set of directional arrows. Modifications to the first set of directional arrows are made based on the selection of the first directional arrow.

Abstract: A vehicle control device recognizes an intersection present in front of a vehicle proceeding in a first direction on a first road, a first another vehicle proceeding in a second direction opposite to the first direction on the first road to approach the intersection, and a second another vehicle traveling after the first another vehicle, controls the vehicle based on a first relative relation between the first another vehicle and the vehicle and a second relative relation between the second another vehicle and the vehicle, determines, when the first and second another vehicles are expected to enter the second road, whether the vehicle enters the second road after the first another vehicle and before the second another vehicle or after the second another vehicle based on relative relations between a basis position and the vehicle, the first and second another vehicles, and controls the vehicle based on a determining result.

Abstract: A method of controlling a vehicle includes obtaining, by a camera, an image of a road ahead; recognizing, by a controller, a curvature of a front lane from the road image and obtaining position and speed information of another vehicle based on obstacle information detected by an obstacle detector; periodically storing, by a storage, driving speed information, yaw rate information, and steering angle information while driving; recognizing, by the controller, a curvature of a rear lane based on the driving speed information, yaw rate information, and steering angle information in response to determining that a lane change is necessary; determining, by the controller, a lane change possibility based on the curvature of the front lane, the curvature of the rear lane, and the position speed information of the other vehicle; and controlling, by the controller, at least one of steering, deceleration, and acceleration based on the lane change possibility.

Abstract: A lane change planning device has a processor configured to assess whether or not it has been planned to carry out multiple lane changes within a single road, based on a traveling lane plan that represents a lane on which a vehicle is scheduled to travel within a predetermined zone of a traveling route toward the destination location of the vehicle, and to create a lane change plan such that a first scheduled lane change zone that the vehicle has been assigned for a lane change to be carried out afterwards, is shorter than a second scheduled lane change zone that has been assigned for a lane change to be carried out beforehand, when it has been planned to carry out multiple lane changes within a single road.

Abstract: A reactive pedal algorithm is used to modify an accelerator pedal output (APO)-to-torque conversion to produce more deceleration for the same accelerator pedal position. Modifying the APO-to-torque conversion provides the driver of a vehicle the sensation that the vehicle is resisting approaching closer to a lead vehicle. The APO-to-torque conversion is modified based on a scene determination to classify vehicles as in-lane, neighbor-lane, or on-coming. Lane change assist methods and systems are used to modify the APO-to-torque conversion range based on a lead vehicle, a neighbor vehicle, or both.

Abstract: Provided are a control unit and a method in a control unit to automatically control a lane change assist function in a vehicle. Multiple conditions indicating that a lane change assist function are activated at a current position of the vehicle are evaluated in the control unit. The conditions are selected from sensor based conditions, historical based conditions, and map based conditions. Sensor based conditions are conditions based on sensor. Historical based conditions are conditions based on historical data received. Map based conditions are conditions based on digital map data. If conditions from at least two different groups of conditions are evaluated as met, a digital signal is provided in the control unit enabling activation of the lane change assist function in the vehicle.

Abstract: A method may include obtaining input information that describes a driving operation of a vehicle and obtaining a rule that indicates an approved driving operation of the vehicle. The method may include parsing the rule using a domain-specific language to generate rule conditions in which the domain-specific language is a programming language that is specifically designed for analyzing driving operations of vehicles. The method may include representing the input information as observations relating to the vehicle in which each of the observations is comparable to one or more of the rules. The method may include comparing the observations to one or more respective comparable rule conditions and generating a grading summary that evaluates how well the observations satisfy the respective comparable rule conditions based on the comparison. A future driving operation of the vehicle may be adjusted based on the grading summary.

Abstract: Aspects of the present disclosure relate to a vehicle for maneuvering an occupant of the vehicle to a destination autonomously as well as providing information about the vehicle and the vehicle's environment for display to the occupant.

Abstract: A speed control device sets a target speed of the own vehicle to a basic speed that is a set speed set in advance or sets the target speed of the own vehicle to a basic speed that is a speed equal to or less than the set speed in which a distance to a preceding vehicle is maintained at a predetermined distance or more when there is a preceding vehicle. The speed control device sets the target speed of the own vehicle to a correction speed instead of the basic speed when the speed control device determines that an adjacent lane is congested and a speed difference between the speed of the own vehicle and an average speed or a lowest speed of another vehicle in the adjacent lane is equal to or more than a first reference value.

Abstract: Provided is a steering assist apparatus configured to perform a steering assist control for changing a steering angle of a vehicle in such a manner that the vehicle moves along a target path; determine whether a newly-detected object is a stationary object or a moving object; cancel the steering assist control and inform a driver that the steering assist control is cancelled when the newly-detected object is the stationary object and a cancel condition is satisfied; pause the steering assist control and inform the driver that the steering assist control is paused when the newly-detected object is the moving object and a pause condition is satisfied; and resume the steering assist control when a resume condition is satisfied.

Abstract: A control method of automatic driving imported “Smart Gains” model can bypass the problem caused by high levels of complexity that currently trouble automatic driving control systems. The knowledge generated by a Gaussian process machine learning model with the maximum probability can carry out the closed-loop control of automatic driving with a given trajectory, can solve the nonlinear adjustment problem of the actuators of the automatic driving vehicle, as well as the optimization control problem of the randomness of the control object. This feature can also make the automatic driving vehicle run smoothly, save energy, be comfortable and fast, and achieve automatic driving above Level 4.

Abstract: A vehicle control device recognizes a second self-position, which is obtained by correcting a first self-position, and an orientation of a vehicle on a road, on which the vehicle is traveling, based on a situation around the vehicle, the first self-position, and map information, determines a steering control mode and a speed control mode of the vehicle based on the second self-position and the orientation of the vehicle, and performs automated driving by controlling the vehicle based on the determined control modes. When the vehicle is scheduled to advance from a first lane to a second lane and it is not possible to recognize a target associated with a road indicating an end point of a merging section, a determiner determines a steering angle control mode for searching for the target based on the second self-position and the orientation of the vehicle.