Abstract: Systems and methods are provided for vehicle navigation. In one implementation, a processing device may be configured to obtain a planned driving action for accomplishing a navigational goal of a host vehicle; receive sensor data from an environment surrounding the host vehicle; identify a target vehicle moving in the environment and a velocity of the target vehicle; calculate a stopping distance and a predicted trajectory for the target vehicle; calculate a planned trajectory for the host vehicle corresponding to the planned driving action; identify an intersection of the planned trajectory for the host vehicle with the predicted trajectory for the target vehicle; determine a braking action of the host vehicle to comply with a safety requirement; and cause the braking action to be applied to decelerate the host vehicle to change the planned trajectory, until the changed trajectory does not intersect the predicted trajectory of the target vehicle.

Abstract: An autonomous driving assistance device includes a manual driving control section, an autonomous driving control section, and a travelling condition determining section. If it is detected that there is a malfunction in a first sensor during control of the autonomous driving of the vehicle, the autonomous driving control section executes emergency autonomous driving until a predetermined condition is satisfied while changing, based on the determined travelling condition, a driving manner of an emergency autonomous driving as compared with a driving manner of the autonomous driving executed before no malfunctions are detected in the first sensor; and after the emergency autonomous driving is terminated, the autonomous driving assistance device being configured to selectively execute one of: causing the autonomous driving control section to stop the vehicle; and causing the manual driving control section to control the manual driving.

Abstract: A vehicle control apparatus includes: a clutch controller configured to switch an operation state of a clutch mechanism from a release state to an engagement state upon switching of a traveling mode from a motor traveling mode to an engine traveling mode; and a motor controller configured to control a traveling motor to suppress variation in torque upon starting of the engine. The clutch controller is configured to control the clutch mechanism to be brought into the engagement state at a first engaging speed when the engine is started on a condition that a revolution speed of the motor driving system is higher than a revolution threshold, and to control the clutch mechanism to be brought into the engagement state at a second engaging speed lower than the first engaging speed when the engine is started on a condition that the revolution speed is lower than the revolution threshold.

Abstract: A vehicle control system includes a direction detector configured to detect a direction of a face or line of sight of an occupant of a host vehicle; an automated driving controller configured to execute automated driving; and a switching controller configured to switch an automated driving mode executed by the automated driving controller to any one of a plurality of automated driving modes including a first automated driving mode in which a predetermined task is required of the occupant or a predetermined automation rate is set and a second automated driving mode in which a level of the task required of the occupant is lower than in the first automated driving mode or an automation rate is lower than in the first automated driving mode, wherein the switching controller includes the direction detected by the direction detector being a predetermined direction in switching conditions for switching from the second automated driving mode to the first automated driving mode.

Abstract: A computer includes a processor and a memory storing instructions executable by the processor. The instructions include to rank a list of minimal risk maneuvers for a vehicle by expected risk score; for each minimal risk maneuver, update a distance from a present location of the vehicle to a respective end location, wherein each end location satisfies a minimal risk condition corresponding to the respective minimal risk maneuver; in response to a first anomalous condition selected from a set of anomalous conditions, determine a distance limit based on the first anomalous condition; then select the minimal risk maneuver ranked best for the expected risk score from the minimal risk maneuvers for which the respective distances are below the distance limit; and then instruct the vehicle to perform the selected minimal risk maneuver.

Abstract: A computer-implemented method for validating the existence of roadwork is provided. The method comprises, for example, retrieving information for at least one segment of a road captured by a plurality of vehicles. The information comprises at least two of lane marking data, speed funnel presence data, and traffic behavior change data. The method also comprises generating a confidence score based on analysis of the retrieved information. The method further comprises validating the existence of the roadwork on the at least one segment of the road based on the generated confidence score.

Abstract: Location of an autonomous driving vehicle (ADV) is determined with respect to a high definition map. On-boards sensors of the ADV obtain a 3D point cloud of objects surrounding the ADV. The 3D point cloud is organized into an ADV feature space of cells. Each cell has a median intensity value and a variance in elevation. To determine the ADV location, a coarse search of a subset of cells in the ADV feature space performed with respect to the high definition map, using a similarity metric that is based on the median intensity and variance in elevation of the candidate cell. When similarity of the first candidate cell is determined, a lookup table of similarity scores is generated and used for determining the similarity score for subsequent candidate cells. Then a fine search is performed on a small subset of candidate cells surrounding the highest similarity score cell.

Abstract: Provided are a speed planning method and apparatus for self-driving, a device and a medium, relating to artificial intelligence technologies such as self-driving and deep learning. The solution includes acquiring the current state of a vehicle and interpolating actions based on the current state and a predetermined state table to obtain the target action of the current state. The current state includes at least the remaining running distance and the current speed. The state table is determined based on a reinforcement learning method and includes multiple states and an action performed in each state. The action performed in each state includes at least acceleration.

Abstract: A vehicle control apparatus is provided. The vehicle control apparatus can obtain periphery information of a vehicle and perform following control including steering and acceleration/deceleration of the vehicle. In a case in which a front vehicle which is to be a following target does not satisfy a specific condition not including a speed condition, the vehicle control apparatus performs at least one of: lowering an automation level; and requesting a driver of the vehicle to perform a predetermined task which is not requested to the driver in a case in which the front vehicle satisfies the specific condition.

Abstract: The present invention relates to an early warning reentry system comprising a high efficiency module for determining spacecraft reentry time and a highly efficient method for determining spacecraft reentry time. The method permits more accurate, earlier spacecraft reentry time determinations using publicly available trajectory information without the need for accounting for the actual design configuration of the spacecraft in question. Thus, a module for making such determinations can easily and inexpensively be added to an early warning reentry system.

Abstract: A vehicle includes: a capturer to capture a driver of the vehicle driving in an autonomous driving mode to obtain driver position information; a driver state detector to detect a state of the driver; and a controller to determine a time required to change from the autonomous driving mode to a manual operation mode based on the obtained driver position information and the detected driver state. In particular, the controller controls the change to driving mode of the vehicle based on the determined time to change from the autonomous driving mode to the manual operation mode.

Abstract: The present invention relates to a method and system for accurately predicting future trajectories of observed objects in dense and ever-changing city environments. More particularly, the present invention relates to substantially continuously tracking and estimating the future movements of an observed object. As an example, an observed object may be a moving vehicle, for example along a path or road. Aspects and/or embodiments seek to provide an end to end method and system for substantially continuously tracking and predicting future movements of a newly observed object, such as a vehicle, using motion prior data extracted from map data.

Abstract: A vehicular driving assistance system includes an exterior viewing camera disposed at a vehicle and an ECU disposed at the vehicle for processing captured image data to detect an object exterior of the vehicle. The ECU performs processing tasks for multiple vehicle systems, including at least (i) a headlamp control system, (ii) a collision avoidance system and (iii) a lane departure warning system. Responsive to determination at the ECU that one of the multiple vehicle systems requires safety critical processing, (i) processing for that vehicle system is determined at the ECU to be a higher priority task, (ii) the ECU performs safety critical processing for that higher priority task and (iii) lower priority processing tasks are shifted from the ECU to other processors within the vehicle so that the ECU maximizes safety critical processing for that higher priority task.

Abstract: Methods, computer readable media, and systems for systems and methods for multi-agent system control using consensus and saturation constraints are described.

Abstract: A device is provided for controlling longitudinal guidance of a vehicle designed to be driven in an at least partly automated manner. The vehicle includes an actuation element for having a driver control longitudinal guidance, the actuation element being blockable within predefined limit positions in accordance with a variable representing the degree of automation of the vehicle and a first condition. The actuation element can be unblocked in accordance with the variable representing the degree of automation of the traveling vehicle and at least one second condition.

Abstract: A control device for a vehicle that has a footrest that is located in front of and below a driver's seat is provided. The device includes a travel control unit configured to automatically perform travel control that includes at least one of: acceleration/deceleration; and steering, of the vehicle, and a footrest sensor configured to detect that the footrest is pressed. Conditions for the travel control unit to perform the travel control include a condition that the footrest is pressed.

Abstract: A method for controlling an ego vehicle during a collision of the vehicle with another vehicle includes an ascertainment of a driving direction of the other vehicle, a determination of a steering signal for aligning a driving direction of the ego vehicle with the driving direction of the other vehicle and a provision of the steering signal to an interface of a steering unit for steering the ego vehicle.

Abstract: Control is performed so as to detect a brain wave or a heartbeat of a driver of a vehicle during automatic driving of the vehicle, and use a plurality of indexes further correlated with sleepiness of the driver among indexes related to the brain wave or the heartbeat of the driver to calculate a concentration index CI, which is an index indicating driving concentration of the driver, at each preset control interval.

Abstract: Embodiments are directed to a user interface for superimposingly displaying, on a map, a plurality of travel route patterns reflecting tendencies of movements of a moving object and a new travel route predicted using the plurality of travel route patterns. The plurality of travel route patterns being extracted in advance by analyzing traveling history data of the moving object and being displayed in different manners, according to a prediction probability between each of the plurality of travel route patterns and the new travel route.

Abstract: Methods, apparatus, systems and articles of manufacture to implement computer aided dispatch of drones are disclosed. Example drone dispatching methods include transmitting a flight plan for a drone to a flight control platform associated with first operator for piloting the drone. The flight plan is based on a first location associated with a service request. In response to receiving a message from the flight control platform, a first communication session between the flight control platform and a flight control unit of the drone is initiated to permit remote piloting of the drone. A drone observation platform associated with a second operator is selected based on a subject matter qualification associated with the second operator and descriptive information included in the service request. A second communication session between the flight control platform and the drone observation platform is initiated for remote piloting of the drone.