Abstract: Systems and methods are provided for suggesting a charging station for an electric vehicle. A partial range of the electric vehicle corresponding to a predetermined percentage of the current state of charge of a battery of the electric vehicle is determined. A location corresponding to the partial range, along a route to a destination, is determined and used to select a suggested charging station based on the location corresponding to the partial range. The suggested charging station is generated for presentation at a display.

Abstract: A behavior prediction method includes: determining a position of a host vehicle; determining a position of another vehicle in a second travel lane, the second travel lane being an opposite lane to a first travel lane in which the host vehicle travels; detecting an intersecting passage intersecting the second travel lane at a position ahead of the host vehicle; and determining whether or not the another vehicle is located within a predetermined range from an intersection position of the intersecting passage and the second travel lane to a point away from the intersection position by a predetermined distance in an opposite direction to a traveling direction of a vehicle in the second travel lane and the another vehicle is in either state of a stopped state and a decelerated state to predict that there is a probability that a mobile unit enters the first travel lane from the intersecting passage.

Abstract: Disclosed here are methods and systems for automatically operating automated vehicles moving through vegetation obstacles with minimal damage, comprising receiving image(s) depicting vegetation obstacle(s) blocking at least partially a path of an automated vehicle executing a mission, analyzing the image(s) to extract one or more obstacle attributes of the vegetation obstacle(s), computing a plurality of movement patterns for operating the automated to cross the vegetation obstacle(s) based on one or more vehicle attributes of the automated vehicle with respect to one or more of the obstacle attributes where each movement pattern defines one or more movement parameters of the automated vehicle, selecting one of the movement patterns estimated to reduce a cost of damage to the automated vehicle and/or to the one or more vegetation obstacles, and outputting instructions for operating the automated vehicle to move through the vegetation obstacle(s) according to the selected movement pattern.

Abstract: An autonomous landing system for vertical landing aircraft includes a vertical landing aircraft including a powertrain and an onboard camera, a motion-stabilized visual cue including a visual indicator, wherein the visual cue is configured to maintain a fixed orientation of the visual indicator with respect to a horizon, and an autonomous control system configured to control a position of the aircraft with respect to the visual indicator of the visual cue based on image data captured by the onboard camera.

Abstract: Described is a method for aligning a vehicle service system (1) relative to a vehicle (2) positioned in a service area (8), where the vehicle service system (1) comprises: a calibration structure (3) for calibrating an ADAS sensor of an advanced driver assistance system of the vehicle (2); an apparatus (4) for measuring the alignment of the vehicle (2) and on which an apparatus camera (41) is mounted; wherein the method comprises the following steps: applying a front wheel target (51) and a rear wheel target (52) on a front wheel and on a rear wheel of the vehicle (2); capturing an image through the apparatus camera (41), wherein the image represents the front wheel target (51) and the rear wheel target (52); processing the image to derive information useful for positioning the calibration structure (3) relative to the vehicle (2); placing a positioning device (7) at an operating position, spaced from the calibration structure (3), in front of the apparatus (4) and alongside the first side of the vehicle (2).

Abstract: A 3D map comprising sensor data items depicting the environment is updated, each sensor data item having one or more associated variables such as a pose of a capture device or a position of a landmark. A graph is calculated from sensor data items. The graph comprises nodes and edges, a node representing at least one variable in the received sensor data items and an edge representing relationships between variables. The graph is partitioned into a plurality of subgraphs so as to reduce a number of variables that are shared between subgraphs. Each of the plurality of subgraphs is allocated to a respective worker node. At each worker node, updated values of the variables are computed. The process updates values of variables which are shared between subgraphs to a common value using a consensus process. The 3D map of the environment is updated according to the updated values of the variables.

Abstract: A computer is provided for a system for detecting, characterizing, and mitigating road network congestion. The system includes a plurality of motor vehicles. Each motor vehicle includes a telematics control unit (TCU) for generating one or more location signals for a location of the associated motor vehicle and one or more event signals for an event related to the associated motor vehicle. The computer includes one or more processors for receiving the location signal and/or the event signal from the TCU of the associated motor vehicles. The computer further includes a non-transitory computer readable storage medium (CRM) including instructions, such that the processor is programmed to identify a location of the road network congestion at a current time step. The processor is further programmed to track the road network congestion and predict the road network congestion at a next time step.

Abstract: An autonomous vehicle operates in a Follow Mode, wherein an apparatus for controlling movement of a vehicle includes an exterior monitoring system comprising at least one sensor to monitor an exterior region and to detect a location of a target user. A controller is configured to A) interactively map an activity zone having a selected expanse in the exterior region relative to the vehicle, B) compare a monitored location of the target user to the activity zone, C) detect a relocation event when the comparison of the monitored location of the target user to the activity zone exceeds a predetermined deviation, and D) send a navigation command in response to detecting the relocation event in order to autonomously reposition the vehicle so that a relative location of the target user is restored to the activity zone.

Abstract: Providing explanations in route planning includes determining a route based on at least two objectives received from a user, where a second objective of the at least two objectives is constrained to within a slack value of a first objective of the at least two objectives; receiving, from the user, a request for an explanation as to an action along the route; and providing the explanation to the user. The explanation describes an extent of violating the slack value.

Abstract: A navigation and positioning system for an underwater glider includes a micro-electro-mechanical system inertial measurement unit, a global positioning system receiving module, a triaxial magnetometer, a Doppler velocimeter, and an integrated navigation hardware processing system. If a navigation and positioning error is too large, the underwater glider stops working in real time and switches from the underwater working state to the up floating error correction state; and when velocity and location errors of a GPS/INS integrated navigation system are smaller than specified thresholds, the underwater glider switches from the up floating error correction state to the underwater working state and continues to work. An H? Kalman filter algorithm based on an adaptive multiple fading factor is established to ensure robustness and adaptability of navigation and positioning of a glider.

Abstract: Techniques for analyzing driving scenarios are discussed herein. For example, techniques may include determining a level of exposure associated with scenarios, searching for similar scenarios, and generating new additional scenarios. A driving scenario may be represented as top-down multi-channel data. The top-down multi-channel data may be provided as input to a neural network trained to output a prediction of future events. A multi-dimensional vector representing the scenario can be received as an intermediate output from the neural network and may be stored to represent the scenario. Multi-dimensional vectors representing different scenarios may be stored in a multi-dimensional space, and similar scenarios may be identified by proximity searching of the multi-dimensional space.

Abstract: System for navigating to a trajectory starting point by autonomous robot includes a GNSS navigation receiver including antenna, analog front end, plurality of channels, and a processor, generating navigation and orientation data for the robot; based on the navigation and the orientation data, the system calculating a position and a direction of movement for the robot towards the starting point of the trajectory, given known physical constraints for movement of the robot; the system calculating spatial and orientation coordinates z1, z2 of the robot, which relate to the position and the direction of movement, where z1 represents lateral deviation, and z2 represents angular deviation; the system continuing with a programmed path for the robot for any spatial and orientation coordinates z1, z2 within an attraction domain; and for any spatial and orientation coordinates of the robot outside the attraction domain, the system continues maneuvering until the robot is inside the attraction domain.

Abstract: A vehicle computing system may implement techniques to determine an action for a vehicle to perform based on a cost associated therewith. The cost may be based on a detected object (e.g., another vehicle, bicyclist, pedestrian, etc.) operating in the environment and/or a possible object associated with an occluded region (e.g., a blocked area in which an object may be located). The vehicle computing system may determine two or more actions the vehicle could take with respect to the detected object and/or the occluded region and may generate a simulation associated with each action. The vehicle computing system may run the simulation associated with each action to determine a safety cost, a progress cost, a comfort cost, an operational rules cost, and/or an occlusion cost associated with each action. The vehicle computing system may select the action for the vehicle to perform based on an optimal cost being associated therewith.