Abstract: A method for determining misalignment of a vehicular camera and calibrating the misaligned camera includes providing a plurality of cameras at a vehicle and providing a control having an electronic control unit that includes a processor for processing image data captured by the plurality of cameras. Frames of image data captured by the plurality of cameras are processed to determine objects present in the field of view of at least one of the cameras. Responsive to processing vehicle data during driving of the vehicle, a vehicle motion vector is determined. Movement of an object relative to the vehicle is determined via processing of at least two frames of captured image data during driving of the vehicle. Responsive to determination of a difference between the relative movement of the object and the vehicle motion vector, misalignment of a misaligned camera is determined, and calibration of the misaligned camera is adjusted.

Abstract: Autonomous driving systems and methods include a controller of a first vehicle configured to detect an operating state of a second vehicle proximate the first vehicle, and to predict, based on the operating state of the second vehicle, a potential behavior for the second vehicle that optimizes a cost function from the perspective of the second vehicle. The controller then controls the first vehicle to avoid a collision with the second vehicle assuming the second vehicle operates according to the potential behavior.

Abstract: The disclosure relates to tracking the location of a target object. In one example, a computer vision system detects a configuration of environment objects. A location model that has been trained for the environment configuration is selected. A signal associated with the target object is received and interpreted using the selected location model to determine the location of the target object.

Abstract: A computer in a vehicle includes a processor programmed to apply, on the vehicle, upon detecting an occupant alertness level below a first threshold, a first periodic component to a first torque applied to one or more first-end wheels and a second periodic component to a second torque applied to one or more second-end wheels.

Abstract: Disclosed embodiments relate to adjusting vehicle Electronic Control Unit (ECU) software versions. Operations may include receiving a prompt to adjust an ECU of a vehicle from executing a first version of ECU software to a second version of ECU software; configuring, in response to the prompt and based on a delta file corresponding to the second version of ECU software, the second version of ECU software on the ECU in the vehicle for execution; and configuring, in response to the prompt, the first version of ECU software on the ECU in the vehicle to become non-executable.

Abstract: A device for a vehicle for providing information about an expected driving intention, a device for a vehicle for determining a driving recommendation, a method for a vehicle for providing information about an expected driving intention, a method for a vehicle for determining a driving recommendation, and a computer program. The device includes a driving analysis module to determine information about an expected trajectory of the vehicle, a control module to determine information about an expected driving intention of the vehicle based on the information about the expected trajectory of the vehicle, and an interface to make available the information about the expected driving intention for one or more vehicle-external entities.

Abstract: A method efficiently determines whether a trajectory of an obstacle to an autonomous driving vehicle (ADV) will require navigation adjustment for the ADV. The trajectory of the obstacle is represented by an ordered plurality of points, {P0 . . . PM}, and a reference line of the ADV is represented by an ordered plurality of points, {R0 . . . RN}, N>M. If the obstacle and ADV are heading in the same direction, then, for a first point P0 on the obstacle trajectory, the ADV finds a point S0 in {R0 . . . RN} that is the least distance from P0 to the reference line. For each of the remaining obstacle points, Pi, the search for a least distance point, Si, is limited to the portion of the reference line Si?1 to RN. If the obstacle and ADV are heading in opposing directions, the search process can be performed from PM, toward P0, in a similar fashion.

Abstract: A method for determining the position of a mobile node applied to a roadside unit (RSU) is provided. The RSU and a plurality of mobile nodes form a communication network of a road. The method includes the steps of: obtaining, by, via at least one sensor, first road information, wherein the first road information provides absolute position distribution information associated with the mobile nodes; receiving, by a communication device, second road information from a first mobile node of the mobile nodes, wherein the second road information provides relative position distribution information associated with the first mobile node and second mobile nodes adjacent to the first mobile node; and determining, by a comparison device, the position of the first mobile node on the road according to the first road information and the second road information.

Abstract: A device receives historical map data, and receives, during a time period, location data associated with a location of a vehicle. The device processes the location data, with a fitted history model, to generate a vehicle path, and processes a portion of the location data, with the fitted history model, to generate a fitted history path, based on the historical map data. The device compares the vehicle path and the fitted history path, and determines whether the vehicle path and the fitted history path match based on comparing the vehicle path and the fitted history path. The device provides the portion of the location data when the vehicle path and the fitted history path match, or adds location data to the portion of the location data and provides the portion of the location data and the added location data, when the vehicle path and the fitted history path do not match.

Abstract: A system may include a follower aircraft including a processor configured to: determine a follower aircraft location at a time t0; receive a real-time kinematics (RTK) update from a lead aircraft, the RTK update including information associated with: a lead aircraft location at the time t0, the lead aircraft location at a time t1 relative to the lead aircraft location at the time t0, and an object location at the time t1 relative to the lead aircraft location at the time t1; perform RTK processing to determine the follower aircraft location at the time t0 relative to the lead aircraft location at a time t0; determine the follower aircraft location at a time t2 relative to the follower aircraft location at the time t0 by utilizing time relative navigation (TRN); and determine the object location at time t2 relative to the follower aircraft location at the time t2.

Abstract: A computer system can estimate preparation times associated with items offered by a plurality of entities to manage a service over a given geographic region. The computer system can receive, from a user device of a user, a request that includes a selection of one or more items offered by one or more entities near the service location. The network system can determine an optimal route of navigation for a service provider to navigate in fulfilling the request. The route of navigation can be determined based at least in part on timing information associated with the one or more items selected by the user. The timing information can be determined based on historical data and/or real-time data.

Abstract: A method for controlling the light distribution of a headlamp arrangement of a vehicle. Oncoming traffic is detected by an oncoming traffic detector, and an additional light field is subsequently dynamically superimposed by the control unit with the aid of effector in an area of the travel direction lane, in particular in the area of a right lane marking.

Abstract: This automatic driving assistance device automatically performs least a part of vehicle control including steering, braking, and acceleration and deceleration within a predetermined travel section. The automatic driving assistance device includes: a switching section determination unit that determines, in the travel section, a section in which a first load that is based on a road shape or a road structure becomes equal to or less than a predetermined threshold as a switching section in which the at least a part of the vehicle control is switched from automatic driving to manual driving; a driving action planning unit that, when the vehicle enters the determined switching section, generates an automatic driving action plan so that a second load that is based on a travel situation of nearby vehicles around the vehicle is reduced; and a driving switching unit that ends automatic driving that is based on the automatic driving action plan and switches the automatic driving to the manual driving.

Abstract: A display system includes a projector that projects a virtual image onto a target space to allow a target person to visibly recognize the virtual image and a controller that controls display of the virtual image. When the projector projects a virtual image corresponding to a caution object, the controller selects at least one reference point from one or more candidate points existing around the caution object and associates the virtual image with the at least one reference point.

Abstract: In a travel control method for a vehicle in which a certain target inter-vehicle distance is set from among a plurality of settable target inter-vehicle distances and a subject vehicle is controlled to follow, in an automated or autonomous manner, a traveling trajectory of a preceding vehicle traveling ahead of the subject vehicle, when a trajectory-following travel mode for following the traveling trajectory of the preceding vehicle in the automated or autonomous manner transitions from an OFF state to an ON state, the target inter-vehicle distance between the subject vehicle and the preceding vehicle is set to a relatively small value from among the settable values.

Abstract: A vehicle control apparatus is provided which includes position detecting means for detecting a position of a detected target using reflection information derived from a radar device 21, first determining means for determining whether the detected target is expected to be an obstacle not based on an intensity of a received reflected wave contained in the reflection information, and second determining means for determining whether an obstacle exists at the position, as detected by the position detecting means, or not using the image information. When the second determining means determines that the obstacle exists, and when a distance between an own vehicle and the detected target is smaller than a given threshold value, the detected target is determined as a target with which collision should be avoided regardless of a result of determination made by the first determining means.

Abstract: A method for locating a vehicle, including the following steps: sensorial detection of first surroundings objects by the vehicle; locating the vehicle by reconciling data of the sensorially detected first surroundings objects with map data of a first digital map, in the case in which reconciliation of the data of the first surroundings objects with the map data of the first digital map to a defined extent is not possible, a second digital map for a local surroundings of the vehicle being created and location of the vehicle being carried out using the second digital map, data from second surroundings objects of an ascertaining device, which are conveyed from the ascertaining device to the vehicle, being used for creation of the second digital map.

Abstract: A system and method for monitoring pedestrians based upon information is collected by a wide array of sensors already included in modern motor vehicles. Also included, is a system of monitoring pedestrians by aggregating data collected by an array of vehicles.

Abstract: Various implementations described herein generate training instances that each include corresponding training instance input that is based on corresponding sensor data of a corresponding autonomous vehicle, and that include corresponding training instance output that is based on corresponding sensor data of a corresponding additional vehicle, where the corresponding additional vehicle is captured at least in part by the corresponding sensor data of the corresponding autonomous vehicle. Various implementations train a machine learning model based on such training instances. Once trained, the machine learning model can enable processing, using the machine learning model, of sensor data from a given autonomous vehicle to predict one or more properties of a given additional vehicle that is captured at least in part by the sensor data.

Abstract: A method for operating a sensor device for detecting an object, having a first surroundings sensor and a second surroundings sensor for detecting a surroundings of the sensor device, including detecting a surroundings of the sensor device using the first surroundings sensor to ascertain first surroundings data, the second surroundings sensor being deactivated; ascertaining whether the first surroundings data are sufficient to be able to conclude with a predetermined probability whether an object is located in the surroundings; if the first surroundings data are sufficient, ascertaining whether an object is located in the surroundings, based on the first surroundings data; if the first surroundings data are not sufficient, activating the deactivated second surroundings sensor; detecting the surroundings of the sensor device using the second surroundings sensor to ascertain second surroundings data; ascertaining whether an object is located in the surroundings, based on the second surroundings data.

Abstract: A vehicle control device including: a recognizer (13) that recognizes a surrounding situation of a subject vehicle; a driving controller (140 or 160) that executes driving control of controlling one or both of steering and acceleration/deceleration of the subject vehicle on the basis of the surrounding situation recognized by the recognizer; and a notifier (30 or 180) that notifies a vehicle occupant of the subject vehicle of predetermined information, wherein the driving controller sets a degree of margin for a surrounding environment set in the driving control after start of the notification of the predetermined information using the notifier to be higher than that before start of the notification of the predetermined information.

Abstract: Disclosed are ultrasound devices and methods for use in guiding a subdermal probe during a medical procedure. A device can be utilized to guide a probe through the probe guide to a subdermal site. In addition, a device can include a detector in communication with a processor. The detector can recognize the location of a target associated with the probe. The processor can utilize the data from the detector and create an image of a virtual probe that can accurately portray the location of the actual probe on a sonogram of a subdermal area. In addition, disclosed systems can include a set of correlation factors in the processor instructions. As such, the virtual probe image can be correlated with the location of the actual probe.

Abstract: A vehicular communication control device includes: a short range communication processor executing a direct vehicle-to-vehicle communication; a wide area communication processor executing an indirect vehicle-to-vehicle communication; a vehicle data generator; and a communication quality determination unit determining a communication quality of the direct vehicle-to-vehicle communication. The short range communication processor wirelessly transmits a communication packet including vehicle data in a predetermined short range transmission cycle.

Abstract: A system is disclosed for providing a platform for creating, browsing and searching a journal of a user's activities.

Abstract: Aspects of the present disclosure involve systems, methods, and devices for determining reflectance properties of objects based on Lidar intensity values, A system includes one or more processors of a machine and a machine-storage medium storing instructions that, when executed by the one or more processors, cause the machine to perform operations comprising accessing an incoming data point output by a Lidar unit during operation of a vehicle. The operations may further include inferring, using a reflectance inference model, a reflectance value of an object based on the incoming data point. The reflectance inference model comprises a mapping of previously collected data points to a coordinate system using associated range values and raw intensity values. The operations may further include determining one or more characteristics of the object based on the inferred reflectance value.

Abstract: An uttered speech of a user is acquired and recognized, and the recognition result is output. Evaluation information is generated from the recognition result. The position where the evaluation information is generated is detected. A reliability determining unit determines reliability of the evaluation information using post information posted on the Internet within a predetermined distance range based on the position where the evaluation information is generated within a predetermined period based on current date and time and determines whether the evaluation information is to be transmitted. A communication unit performs transmission, to the travel assistance server, of the evaluation information determined to be transmitted by the reliability determining unit, reception of the evaluation information stored in the travel assistance server, and reception of the post information posted on the Internet.

Abstract: A driver assistance system includes an image sensor and a radar mounted to a vehicle and each having a sensing field oriented toward the outside of the vehicle. A controller processes the image data acquired by the camera and the radar data acquired by the radar, detects a stationary obstacle ahead of the vehicle on the basis of the image data or radar data, determines a monitoring range around a location of the stationary obstacle on the basis of the radar data, identifies an object present within the monitoring range on the basis of the radar data, and determines the object as a pedestrian on the basis of a speed of the object toward a road along which the vehicle travels.

Abstract: Methods, systems and computer readable media for dynamic displays are described. The dynamic displays can include functions to detect when a user with a device approaches, and request information about the user from the user device. The dynamic display system can then use the information about the user to retrieve other associated information (e.g., a course schedule, calendar, or appointment list) and provide the user with directions to a destination via one or more dynamic displays and/or through navigation instructions sent to the user's device.

Abstract: Driver assistance system and method of assisting a driver when operating a vehicle in a transportation route network. The system includes a first interface to provide navigation data relating to the network, a position detection unit to provide a position of the vehicle, a second interface to provide first data relating to first objects, arranged along transportation routes of the network, a sensor system to sense current surroundings of the vehicle at the position in order to generate surroundings data, a first evaluation unit to determine second data relating to second objects based on the surroundings data, a fusion unit to match and fuse the first data and the second data to form third data, and a control unit to execute at least one assistance function in order to assist operation of the vehicle, wherein the assistance function is executed depending on the third data and the navigation data.

Abstract: A non-transitory computer-readable recording medium stores a program that causes a computer to execute a process. The process includes extracting a sailing log of a ship in a sea area with a sailing route existing therein, the sea area being such that a distance between two ships of the ship and another ship is less than a predetermined value and at least one of the two ships has a ship track deviating from the sailing route; and evaluating risks at a plurality of points that are included in the sea area, based on the extracted sailing log.

Abstract: A video analytics algorithm, system, and method for use in real time allowing accurate, reliable, and timely warnings that facilitate traffic safety and efficiency. The system and method are readily implemented with minimal computational resources, providing broad applicability. In an embodiment, a video analytics method may include (a) obtaining a sequence of real-time images as input from a traffic monitoring system; (b) identifying a plurality of vehicles within a pre-defined region of interest; (c) tracking vehicles within the predefined region of interest; and (d) detecting a conflict event when the vehicles are located within a pre-determined maximum separation threshold based on each vehicles coordinates in a spatial-temporal domain.

Abstract: A trolling device for a boat includes a trolling motor and a control mechanism. The control mechanism controls at least one of the speed and the direction of the trolling motor. The control mechanism is configured to receive control instructions from an electronic GPS mapping computer to cause the trolling motor to maintain a controlled drift of the fishing boat with respect to an anchor point, water current rate, water current direction, wind, and/or wave action.

Abstract: This disclosure relates generally to autonomous vehicle, and more particularly to method and system for determining a drivable navigation path for an autonomous vehicle. In one embodiment, a method may be provided for determining a drivable navigation path for the autonomous vehicle. The method may include receiving a base navigation path on a navigation map, a position and an orientation of the autonomous vehicle with respect to the base navigation path, and an environmental field of view (FOV). The method may further include deriving a navigational FOV based on the environmental FOV, the base navigation path, and the orientation of the vehicle. The method may further include determining a set of navigational data points from the navigational FOV, and generating at least a portion of the drivable navigation path for the autonomous vehicle based on the set of navigational data points.

Abstract: An electronic apparatus and a method of controlling a group action, the method being performed by the electronic apparatus are provided. An electronic apparatus and a method of controlling a group action, the method being performed by the electronic apparatus that is capable of creating the group action corresponding to a status change of an external apparatus and is also capable of controlling the external apparatus are provided. Some embodiments provide an electronic apparatus and a method of controlling a group action, the method being performed by the electronic apparatus that is capable of creating the group action corresponding to status information of an external apparatus, which is received from a server, and is also capable of changing a status of the external apparatus via the created group action.

Abstract: A method and system are provided for adapting a vehicle control strategy of an on-road vehicle following a reoccurring fixed route to a predetermined destination, which fixed route extends through at least one geographical zone associated with at least one environmental restriction. When it is determined that the vehicle is approaching the geographical zone, historical data collected from previous passages of one or several vehicles through the zone is accessed, and the vehicle control strategy inside the geographical zone is adapted based on the historical data and the environmental restriction.

Abstract: A social networking system recommends objects, such as pages, of the social networking system to users of the social networking system based on the location of the user. The social networking system obtains location information identifying the location of the user. Based on the location of the user, the social networking system identifies levels of geographical partitions encompassing the location of the user. For each level of geographical partitions, the social networking system accesses relevant objects of the social networking system with connections to users located within the level of geographical partitions. The social networking system may have determined a term frequency-inverse document frequency (tf-idf) value for each relevant object. Based on the number of connections and the tf-idf value associated with each relevant object, the social networking system merges the relevant objects accessed at each level into a set of relevant objects to recommend to the user.

Abstract: A method of disambiguating a location of a mobile station within a structure includes: obtaining, at the mobile station, regional pressure indications and corresponding region indications indicating regions within a structure that are vertically displaced with respect to each other, each of the regional pressure indications indicating atmospheric pressure information associated with the corresponding region; determining mobile station pressure information associated with a present location of the mobile station; comparing the mobile station pressure information with the regional pressure indications; and based on the comparing, determining in which of the regions the mobile station presently resides.

Abstract: Systems, methods, and non-transitory computer-readable media can determine a road segment. A set of features associated with the road segment can be determined based at least in part on data captured by one or more sensors of a vehicle. A level of similarity between the road segment and each of a set of road segment types can be determined by comparing the set of features to features associated with each of the set of road segment types. The road segment can be classified as a road segment type based on the level of similarity. Scenario information associated with the road segment can be determined based on the classified road segment type.

Abstract: A guidance system, for use on an automated vehicle includes a camera, a vehicle-to-vehicle transceiver, and a controller. The camera detects a lane-marking on a roadway and detects a lead-vehicle traveling ahead of a host-vehicle. The vehicle-to-vehicle transceiver receives a future-waypoint from the lead-vehicle, wherein the future-waypoint defines a future-route of the lead-vehicle along the roadway. The controller is in communication with the camera and the vehicle-to-vehicle transceiver. The controller determines a projected-path for the host-vehicle based on the lane-marking. The controller also determines a lead-path of the lead-vehicle based on the camera. The controller steers the host-vehicle according to the lead-path when the lane-marking is not detected and the lead-path corresponds to the projected-path. The controller steers the host-vehicle according to the projected-path while the lane-marking is not detected and the future-waypoint does not correspond to the projected-path.

Abstract: A system for proximity-based analysis of multiple entities includes a first communication device associated with a first entity and an additional communication device associated with an additional entity, wherein the first communication device and the additional communication device are communicatively couplable. The system includes one or more processors communicatively coupled to at least one of the first communication device or the at least an additional communication device. The one or more processors are configured to: identify a spatial relationship between the first entity and the additional entity based on one or more signals from the first communication device or the additional communication device, identify an operation unit defined by an association between the first entity and the additional entity based on the spatial relationship between the first entity and the at least the additional entity, and report one or more characteristics of the operation unit.

Abstract: Some embodiments provide an autonomous navigation system which enables autonomous navigation of a vehicle along one or more portions of a driving route based on monitoring, at the vehicle, various features of the route as the vehicle is manually navigated along the route to develop a characterization of the route. The characterization is progressively updated with repeated manual navigations along the route, and autonomous navigation of the route is enabled when a confidence indicator of the characterization meets a threshold indication. Characterizations can be updated in response to the vehicle encountering changes in the route and can include a set of driving rules associated with the route, where the driving rules are developed based on monitoring the navigation of one or more vehicles of the route. Characterizations can be uploaded to a remote system which processes data to develop and refine route characterizations and provide characterizations to one or more vehicles.

Abstract: Aspects of the present disclosure involve systems, methods, and devices for determining reflectance properties of objects based on Lidar intensity values, A system includes one or more processors of a machine and a machine-storage medium storing instructions that, when executed by the one or more processors, cause the machine to perform operations comprising accessing an incoming data point output by a Lidar unit during operation of a vehicle. The operations may further include inferring, using a reflectance inference model, a reflectance value of an object based on the incoming data point. The reflectance inference model comprises a mapping of previously collected data points to a coordinate system using associated range values and raw intensity values. The operations may further include determining one or more characteristics of the object based on the inferred reflectance value.

Abstract: Systems and methods are provided for controlling an autonomous vehicle. In one embodiment, a method includes: receiving image data from a camera device coupled to the autonomous vehicle; computing, by a processor, a value based on the image data; determining, by a processor, an existence of an emergency vehicle based on the computed value; selecting, by a processor, a first control strategy based on the determined existence of an emergency vehicle; and generating, by a processor, at least one signal to autonomously control the autonomous vehicle based on the control strategy.

Abstract: An apparatus for assisting driving of a host vehicle provides stable control of the host vehicle by using road conditions including intersections, crosswalks and the like, forward lane markings, and a preceding vehicle. The apparatus includes an image sensor to capture images of an area in front of the host vehicle, and a controller configured to recognize a road section having no lane markings on a drive path, or recognize forward lane markings. The controller performs lateral control of the host vehicle selectively based on the forward lane markings and the recognized preceding vehicle according to whether the road section having no lane markings is recognized.

Abstract: The purpose of the present invention is to obtain assistance for traveling in an appropriate position, through steering assistance control, when a driver intends to travel in a position offset either to the left or to the right from the center of a traffic lane. Provided is a vehicular steering assistance control device for controlling a host vehicle so that the vehicle travels in a predetermined position of a traffic lane, wherein the amount of steering control is adjusted according to the driver's intentions.

Abstract: A system and method for autonomous vehicle routing using annotated maps. For at least some path segments within a geographic region in which the vehicle is operating, values are determined for the path segments based at least on risk factors associated with autonomous operation of the vehicle along each path segment. Path segments are combined to generate a travel route, from a first location to a second location, based on the determined values, and the vehicle is controlled to navigate along the travel route.

Abstract: A vehicle control apparatus mounted to an own vehicle to control the own vehicle according to a position of other vehicle ahead of the own vehicle is provided. The device includes a setting means setting a parameter indicating a position of the other vehicle relative to the own vehicle in a lateral direction perpendicular to the path of the own vehicle, a determination means determining whether the other vehicle is in the path of the own vehicle based on the parameter, a detection means detecting whether a relative movement has been made in the lateral direction by at least one of the own vehicle and the other vehicle, and a correction means correcting the parameter when a relative movement has been made in the lateral direction.

Abstract: Innovations in the area of controlling behavior of computer-controlled entities such as cars in a computer-represented environment are presented herein. In various examples described herein, the behavior of computer-controlled cars is controlled by an artificial intelligence (“AI”) behavior engine. The AI behavior engine performs operations to determine if the behavior (driving pattern, etc.) of a computer-controlled car should change for a funnel section. If so, the AI behavior engine switches the computer-controlled car to a trailing mode configuration and selects a candidate car to follow in the funnel section based on various criteria. The AI behavior engine also determines how to follow the candidate car by selecting a racing path and setting rules to determine the speed to use for following the candidate car. Control values are then set. The described innovations also generally apply to other racing scenarios, self-driving/autonomous cars, and other applications with robotic equipment and devices.

Abstract: Method and apparatus are disclosed for systems and method to detect blocked vehicles. An example vehicle includes range detection sensors and a body control module. When the vehicle is parked, the body control module (a) scans, with the range detection sensors, the area around the vehicle to detect objects, (b) based on positions of the objects, determines whether the vehicle is able to maneuver out of its current parking spot, and (c) when the vehicle is not able to maneuver, sends an alert to a mobile device of a driver of the vehicle.

Abstract: A driving assistance apparatus includes a plurality of sensor devices mounted in a host vehicle, an attention calling device configured to call attention of a driver of the host vehicle, and at least one electronic control unit. The at least one electronic control unit acquires host vehicle information, acquires object information, estimates an expected path through which the host vehicle passes, determines whether or not a target object is present, determines whether or not there is a front space in front of the host vehicle based on the object information, generates a request signal so as to call attention of the driver of the host vehicle, forbids generation of the request signal when the electronic control unit determines that the target object is present, and that there is no front space, and controls the attention calling device to call attention of the driver.