Abstract: To provide a vehicle position processing apparatus, a vehicle control apparatus, a vehicle position processing method, and a vehicle control method capable of increasing the number of the position information of front object used for generation of the trajectory and improving the generation accuracy of the trajectory. A vehicle position processing apparatus, a vehicle control apparatus, a vehicle position processing method, and a vehicle control method that obtains positions of a target object, sets a trajectory generation range which is a continuous range including a position of the target object close to a position of the present own vehicle, selects positions of the target object included in the trajectory generation range among the plural positions of the target object, as target object positions for trajectory generation, and generates a trajectory of the target object based on the target object positions for trajectory generation.

Abstract: Aspects of the disclosure relate to determining a next vehicle task for a vehicle of a fleet. Vehicle data from the vehicle, charger data about at least one charger, and demand data may be received and used to determine the next vehicle task. The vehicle may be directed to the next vehicle task. Determining a next vehicle task may further be based on predictions made using the vehicle data, the charger data, and the demand data. Heuristics may also be used in determining a next vehicle task.

Abstract: Methods, computer-readable storage media including computer instructions, and systems for reducing power consumption or greenhouse gas emissions. In some examples, a method includes determining a context of a vehicle, selecting a particular smart mode from among multiple smart modes that are associated with the vehicle, the particular smart mode being associated with deactivation or moderation of one or more vehicle components that draw battery power or that contribute to greenhouse gas emissions, and transmitting a message to deactivate or moderate the one or more vehicle components of the vehicle according to the selected, particular smart mode.

Abstract: A vehicle control apparatus performs a following travel mode in which an own vehicle travels while following a followed vehicle ahead of the own vehicle. The apparatus includes a surrounding object detection section that acquires detection information regarding a surrounding object, a space determination section that uses the detection information to determine presence/absence of a free space located laterally to an own lane, a setting condition determination section that determines whether a first other vehicle having entered the own lane from the free space or a second other vehicle traveling ahead of a preceding vehicle having entered the free space from the own lane meets a setting condition for setting the first or second other vehicle as the followed vehicle, and an automated driving control section that sets the first or second other vehicle as the followed vehicle to perform the following travel mode if the setting condition is met.

Abstract: A method and a system for constructing a driving coordinate system for use in the field of smart transport. The method for constructing a driving coordinate system comprises: determining the road boundary line on one side of the road on which a current vehicle is situated as a reference line for constructing a driving coordinate system; in a vehicle coordinate system, determining the reference line point having the smallest distance between the reference line and the current vehicle position as an origin point OF of the driving coordinate system; on the basis of the origin point OF, determining the road guiding line direction as the XF axis of the driving coordinate system and determining the direction relative to the road guiding line direction according to the left-hand rule as the YF axis of the driving coordinate system; and, on the basis of the origin point OF, the XF axis, and the YF axis, forming a corresponding driving coordinate system.

Abstract: A method for determining a driving maneuver of a vehicle with a control unit includes receiving a measurement data relating to a traffic situation from a sensor, determining a current detection area of the sensor by evaluating the measurement data, and creating a sensor model based on the measurement data. An estimated detection area of the sensor from the measurement data is modelled through forward simulation based on a vehicle position of the vehicle. A change in the estimated detection area of the sensor due to a driving maneuver is determined along with the driving maneuver that causes an increase in the estimated detection area due to the sensor model.

Abstract: Provided are autonomous vehicles (AV), computer program products, and methods for maneuvering an AV in a roadway, including receiving forecast information associated with predicted trajectories of one or more actors in a roadway, determining a relevant trajectory of an actor based on correlating a forecast for predicted trajectories of the actor with the trajectory of the AV, regenerate a distance table for the relevant trajectory previously generated for processing constraints, generate a plurality of margins for the AV to evaluate, the margins based on a plurality of margin types for providing information about risks and effects on passenger comfort associated with a future proximity of the AV to the actor, classifying an interaction between the AV and the actor based on a plurality of margins, and generating continuous scores for each candidate trajectory that is also within the margin of the actor generated for the relevant trajectory.

Abstract: Apparatus, device, methods and system relating to a vehicular telemetry environment for identifying in real time unpredictable network communication faults in network zones based upon pre-processed raw telematics big data logs that may include gps data and an indication of vehicle status data, and supplemental data that may further include location data and network data.

Abstract: Drone-based systems and methods are described for providing an airborne relocatable communication hub within a delivery vehicle for broadcast-enabled devices maintained within the delivery vehicle. Such a method has an aerial communication drone paired with the delivery vehicle transitioning to an active power state, uncoupling from a secured position on an internal docking station fixed within the delivery vehicle and then moving to a first deployed airborne position within the delivery vehicle. At a first position, the method has the aerial communication drone establishing a first wireless data communication path to a first broadcast-enabled device within the delivery vehicle, then establishing a second wireless data communication path to a second broadcast-enabled device within the delivery vehicle. The drone then couples the first and second wireless data communication paths it established operating as the airborne relocatable communication hub for the devices.

Abstract: Example aspects of the present disclosure describe determining, using a machine-learned model framework, a motion trajectory for an autonomous platform. The motion trajectory can be determined based at least in part on a plurality of costs based at least in part on a distribution of probabilities determined conditioned on the motion trajectory.

Abstract: Disclosed is a lane information generating method that can generate lane information of an increasing or decreasing lane which increases or decreases from a traveling lane with high accuracy is provided. By determining characteristic points based not only on traveling trajectory information of a vehicle but also on the shape of the increasing line of the increasing lane increasing from two traveling lanes, a control unit can complementarily using information of a shape of the increasing line at a position at which variation is easily generated in the traveling trajectory, and thus generate the characteristic points as the lane information of an increasing line with high accuracy.

Abstract: The technology relates to controlling a vehicle in an autonomous driving mode in accordance with behavior predictions for other road users in the vehicle's vicinity. In particular, the vehicle's onboard computing system may predict whether another road user will perform a “continuing” lane driving operation, such as going straight in a turn-only lane. Sensor data from detected/observed objects in the vehicle's nearby environment may be evaluated in view of one or more possible behaviors for different types of objects. In addition, roadway features, in particular whether lane segments are connected in a roadgraph, are also evaluated to determine probabilities of whether other road users may make an improper continuing lane driving operation. This is used to generate more accurate behavior predictions, which the vehicle can use to take alternative (e.g., corrective) driving actions.

Abstract: Embodiments for operational envelope detection (OED) with situational assessment are disclosed. In some embodiments, a method comprises: determining at least one current or future constraint for a trajectory of a vehicle in an environment that is associated with the vehicle becoming immobile for an extended period of time; determining a stopping-reason for immobility of the vehicle based on determining the at least one current or future constraint for the trajectory of the vehicle in the environment; identifying a timeout threshold based on the stopping-reason, wherein the timeout threshold is an amount of time a planning system of the vehicle will wait before initiating at least one remedial action to address the immobility; identifying that the timeout threshold is satisfied; and initiating the at least one remedial action for the vehicle based on the identifying that the timeout threshold is satisfied.

Abstract: A method for detecting small obstacles includes: acquiring a first 3D point cloud corresponding to image data acquired by a cleaning robot; extracting, from the first 3D point cloud, a second 3D point cloud of a ground region; extracting, from the second 3D point cloud, a third 3D point cloud having a height value in a set height range; calculating a ground projection point cloud of the third 3D point cloud; and, determining morphologically-connected regions in the ground projection point cloud, and using a morphologically-connected region having an area less than a preset value as a region where a small obstacle is located. By effectively recognizing the ground, acquiring the ground projection point cloud and processing the point cloud by image processing, accuracy and timeliness of the algorithm can be improved compared with directly processing discrete 3D point clouds.

Abstract: Example aspects of the present disclosure relate to an example computer-implemented method for predicting the intent of actors within an environment. The example method includes obtaining state data associated with a plurality of actors within the environment and map data indicating a plurality of lanes of the environment. The method include determining a plurality of potential goals each actor based on the state data and the map data. The method includes processing the state data, the map data, and the plurality of potential goals with a machine-learned forecasting model to determine (i) a forecasted goal for a respective actor of the plurality of actors, (ii) a forecasted interaction between the respective actor and a different actor of the plurality of actors based on the forecasted goal, and (iii) a continuous trajectory for the respective actor based on the forecasted goal.

Abstract: Apparatus, device, methods and system relating to a vehicular telemetry environment for identifying in real time unpredictable network communication faults in network zones based upon pre-processed raw telematics big data logs that may include GPS data and an indication of vehicle status data, and supplemental data that may further include location data and network data.

Abstract: Apparatus, device, methods and system relating to a vehicular telemetry environment for the real time generation and transformation of raw telematics big data into analytical telematics big data that includes raw telematics big data and supplemental data.

Abstract: Example methods for multistage autonomous vehicle motion planning include obtaining sensor data descriptive of an environment of the autonomous vehicle; identifying one or more objects in the environment based on the sensor data; generating a plurality of candidate strategies, wherein each candidate strategy of the plurality of candidate strategies comprises a set of discrete decisions respecting the one or more objects, wherein generating the plurality of candidate strategies includes: determining that at least two strategies satisfy an equivalence criterion, such that the plurality of candidate strategies include at least one candidate strategy corresponding to an equivalence class representative of a plurality of different strategies that are based on different discrete decisions; determining candidate trajectories respectively for the plurality of candidate strategies; and initiating control of the autonomous vehicle based on a selected candidate trajectory.

Abstract: Apparatus, device, methods and system relating to a vehicular telemetry environment for identifying in real time unpredictable network communication faults in network zones based upon pre-processed raw telematics big data logs that may include GPS data and an indication of vehicle status data, and supplemental data that may further include location data and network data.

Abstract: Drone-based systems and methods are described for providing an airborne relocatable communication hub within a delivery vehicle for broadcast-enabled devices maintained within the delivery vehicle. Such a method has an aerial communication drone paired with the delivery vehicle transitioning to an active power state, uncoupling from a secured position on an internal docking station fixed within the delivery vehicle and then moving to a first deployed airborne position within the delivery vehicle. At a first position, the method has the aerial communication drone establishing a first wireless data communication path to a first broadcast-enabled device within the delivery vehicle, then establishing a second wireless data communication path to a second broadcast-enabled device within the delivery vehicle. The drone then couples the first and second wireless data communication paths it established operating as the airborne relocatable communication hub for the devices.