Abstract: A link combination extraction unit (24) acquires all the combination of link candidates from among link candidates having an angle with respect to a movement direction of a pedestrian equal to or smaller than a threshold value among link candidates for n walking route networks. The link combination extraction unit (24) acquires all the combinations of link candidates that do not intersect with each other among the acquired combinations of link candidates. The link combination extraction unit (24) acquires all the combinations of link candidates that do not connect to each other among the acquired combinations of link candidates. The link combination extraction unit (24) acquires all the combinations of link candidates that are not on the same straight line among the acquired combinations of link candidates. A candidate determination unit (26) acquires a combination of link candidates closest to position information of a pedestrian when there are a plurality of acquired link candidates.

Abstract: Systems and methods for providing real-time feedback to a driver of a vehicle based on real-time datasets is disclosed. The systems and methods include obtaining one or more sets of real-time data associated with a vehicle. Performing one or more operations on the set of real-time data, wherein the one or more operations are based on the set of real-time data. Generating, a feedback alert based on results of the one or more operations and one or more detected real-time behaviors of the vehicle. Providing the feedback alert for presentation at a user interface on-board the vehicle. The real-time data may include contextual data, environmental data, operating data, data for a plurality of drivers, or combinations thereof.

Abstract: Systems and methods for trajectory planning for an autonomous vehicle, may include: computing features for each of the plurality of candidate trajectories; computing scores for the features of the candidate trajectories, wherein the scores are based on parameter values associated with their corresponding final trajectories; determining, based on the computed scores, a trajectory of the candidate trajectories to be used as a warm-start trajectory for trajectory optimization and applying the warm-start trajectory to develop a final trajectory for the vehicle; and autonomously operating the autonomous vehicle in accordance with the final trajectory.

Abstract: Methods and systems are provided for assisting operation of a vehicle using speech recognition and transcription to provide a conversation log graphical user interface (GUI) display that consolidates communications with respect to the vehicle. One method involves receiving a data message from a system onboard the vehicle and generating a graphical representation of the data message within the conversation log GUI display, wherein the graphical representation of the data message includes a selectable element and is displayed on the conversation log GUI display concurrently with a graphical representation of a transcription of an audio communication with respect to the vehicle. The depicted data message and transcription are chronologically positioned with respect to one another in accordance with a timestamp associated with the data message. The conversation log GUI display dynamically updates in response to selection of the selectable element.

Abstract: Methods, systems, and media for generating and evaluating street grids comprising: receiving street grid information corresponding to a plurality of locations, wherein the street grid information corresponding to a location is associated with vehicular traffic information; training a pedestrian comfort model using the street grid information and the vehicular traffic information, wherein an output of the pedestrian comfort model is a predicted pedestrian comfort score that is based on traffic congestion from the vehicular traffic information; receiving a plurality of potential street grids; evaluating each potential street grid in the plurality of potential street grids using the trained pedestrian comfort model, wherein the trained pedestrian comfort model generates predicted pedestrian comfort scores for portions of each potential street grid; and generating an augmented map of each potential street grid that presents the predicted pedestrian comfort scores for each portion of each potential street grid.

Abstract: An autonomous vehicle configured to autonomously pass a cyclist includes an imaging device and processing circuitry configured to receive information from the imaging device. Additionally, the processing circuitry of the autonomous vehicle is configured to identify a cyclist passing situation based on the information received from the imaging device, and plan a path of an autonomous vehicle based on the cyclist passing situation. The autonomous vehicle also includes a positioning system and the processing circuitry is further configured to receive information from the positioning system, determine if the cyclist passing situation is sufficiently identified, and identify the cyclist passing situation based on the information from the imaging device and the positioning system when the cyclist passing situation is not sufficiently identified based on the information received from the imaging device.

Abstract: An environmental safety system may comprise a plurality of first sensors each located at a predetermined physical location of a traffic intersection and with a predetermined orientation. The system may have a memory storing executable instructions. The system may have one or more processors in communication with the plurality of first sensors and the memory. The one or more processors may be programmed by the executable instructions. The system may receive first sensor data captured at a time point and by the plurality of first sensors. The system may determine values of one or more parameters of an object of interest within a threshold distance of the traffic intersection using the first sensor data. The system may generate an information object comprising the values of the one or more parameters of the object of interest, the time point, and a signature of the information object. The system may transmit, via a communication network, the information object.

Abstract: Aspects of the disclosure provide for controlling an autonomous vehicle. For instance, a first probability distribution may be generated for the vehicle at a first future point in time using a generative model for predicting expected behaviors of objects and a set of characteristics for the vehicle at an initial time expected to be perceived by an observer. Planning system software of the vehicle may be used to generate a trajectory for the vehicle to follow. A second probability distribution may be generated for a second future point in time using the generative model based on the trajectory and a set of characteristics for the vehicle at the first future point expected to be perceived by the observer. A surprise assessment may be generated by comparing the first probability distribution to the second probability distribution. The vehicle may be controlled based on the surprise assessment.

Abstract: A plant tracking apparatus, system, and method for tracking planting locations of a plurality of plants configured to be planted in a ground surface using a planting utensil having a handle, a blade, and a shaft defined between the handle and the blade is disclosed herein. The plant tracking apparatus includes a housing configured to be coupled to the planting utensil. The plant track apparatus further includes a Global Navigation Satellite System (GNSS) sensor, a planting sensor, and a controller positioned within or coupled to the housing. The controller is configured to record location data from the GNSS sensor in response to a planting signal from the planting sensor. In certain embodiments, the controller may determine the planting signal by comparing data from the planting sensor to a predetermined motion profile.

Abstract: Systems and methods to fuse aviation-related data systems for comprehensive aircraft system health monitoring are provided. One example method includes obtaining, by one or more computing devices, fault data indicative of a plurality of fault indications provided by a first plurality of components of an aircraft. The method includes obtaining, by the one or more computing devices, condition indicators describing the respective operational conditions of a second plurality of components of the aircraft. The method includes fusing, by the one or more computing devices, the fault data with the condition indicators to form a comprehensive data set. The method includes identifying, by the one or more computing devices, one or more causes of the plurality of fault conditions based at least in part on the comprehensive data set. One example system includes a data fuser, a cause identifier, and an alert generator.

Abstract: A collision avoidance assist apparatus executes an emergency steering control including processes to determine a target steering torque used to change a steering angle to avoid a collision of a vehicle with an obstacle so as not to move the vehicle out of a moving lane when the vehicle has a high probability of colliding with the obstacle, and the moving lane is a straight lane, and applies a steering torque corresponding to the determined target steering torque to a steering mechanism. The collision avoidance assist apparatus stops executing the emergency steering control when determining that the moving lane is a curved lane, based on only one of left and right lane markings at an avoidance side of the obstacle which is the left or the right side of the obstacle which the vehicle passes over while executing the emergency steering control.

Abstract: A computer-implemented method is provided for creating a velocity grid using a simulated environment for use by an autonomous vehicle. The method may include simulating a road scenario with simulated objects. The method may also include recording image data collected from a camera sensor, the image data comprising a first 2D image frame comprising the simulated objects made up of a plurality of pixels. The method may also include identifying a first 3D point on the first simulated object in a 3D view of the simulated road scenario, wherein the first 3D point corresponds to the first pixel in the first 2D image frame. The method may also include generating a velocity of the first point based upon a velocity of the first simulated object, and projecting the velocity back into the first 2D image frame.

Abstract: A computer-implemented method is provided for training a machine-learning (ML) algorithm that contributes to piloting an autonomous vehicle using a velocity grid generated from a simulation. The method may include simulating a scene. The scene includes a simulated autonomous vehicle and at least one simulated object moving in the scene. The method may also include predicting a velocity of at least one point on the simulated object as it moves in the simulated scene using a ML algorithm. The method may also include comparing the predicted velocity of the at least one point on the simulated object with velocities in the velocity grid generated from a simulation. The method may further include adjusting the ML algorithm to more accurately predict velocity of at least one point on the simulated object as it moves in the scene based on a difference in the predicted velocity compared to the velocity grid, which yields a trained ML algorithm.

Abstract: A navigation system for generating turn segments includes a processor, a memory module communicatively coupled to the processor, a segment list stored in the memory module that includes a plurality of known segments, and machine readable instructions stored in the memory module. The machine readable instructions cause the navigation system to identify a current location of the navigation system, search the segment list for at least one known segment candidate that is within a threshold distance of the current location, determine whether at least one known segment candidate from the segment list includes the current location, track turn movements of the navigation system to form an unknown segment in response to determining at least one known segment candidate does not include the current location, and to link the unknown segment to the plurality of known segments from the segment list.

Abstract: A computed-implemented method is provided for creating a velocity grid using a simulated environment for use by an autonomous vehicle. The method may include simulating a road scenario with simulated objects, collecting first LiDAR data from simulated LiDAR sensors in the simulated road scenario, wherein the collected first LiDAR data comprises a first plurality of points that are representative of a first simulated object at a first 3D location and a first time. The method may also include transforming the first plurality of points from a simulated-scene frame-of-reference to a first simulated object frame-of-reference, and simulating the first simulated object to move from the first 3D location to a second 3D location within the simulated road scenario between the first time and a second time.

Abstract: A system and method for mapping a mobile device position on segments that lie between waypoints on a non-linear map by converting real world geographic coordinates of a mobile device to image X, Y coordinates using an image X, Y length or scale of a respective segment as a basis for the conversion. The mobile device position may be mapped in real time and presented to a user via a mobile device. The coordinate may be mapped in real-time to a specific X, Y location on the map and may be presented to a user on a screen, stored in a database, or used in any appropriate way.

Abstract: An approach is provided for resolving an inconsistency in road closure data stored in a mapping platform. The approach, for example, involves processing map data to generate a roadway graph representing a spatial relationship between a first road segment and a second road segment. The spatial relationship indicates that a first closure state of the first road segment cannot differ from a second closure state of the second road segment. The approach also involves determining that the inconsistency in the road closure data for the first road segment and the second road segment indicates that first closures state and the second closure state do not match. The approach further involves changing the road closure data stored in the mapping platform either to match the first road closure state with the second road closure state, or to match the second road closure state with the first road closure state in response to the inconsistency.

Abstract: A traffic analysis system analyzes location data from a plurality of vehicles to determine journeys made by the vehicles. Vehicles may make one or more rest stops during a journey. The traffic analysis system compares rest periods to journey criteria to determine whether a rest period delineates the end of a journey, or whether a rest period is still within the journey. In this way, a plurality of trips can be chained together into a journey to provide more accurate analysis of traffic patterns.

Abstract: A system, method and server for a controlling a relation between a vehicle and traffic flow over a road segment. The system includes a telemetric device of the vehicle and a processor of the server. The telemetric device obtains telemetric data related to the road segment being traversed by the vehicle. The processor determines a property of the road segment based on the telemetric data and a road profile for the road segment, determines a disruption score indicative of a level of disruption in the traffic flow for the road segment based on the property, and outputs a notification signal when the disruption score is above a selected disruption threshold. The notification signal is usable for controlling the relation between the vehicle and the traffic flow.

Abstract: The present invention provides a vehicle control apparatus, a vehicle control method, and a vehicle control system capable of improving reliability of road recognition.