Abstract: Systems and methods of non-line-of-sight passive detection and integrated early warning of an unmanned aerial system by a plurality of acoustic sensors are described. In some embodiments, the plurality of acoustic sensors is positioned within an intra-netted array in depth according to at least one of a terrain, terrain features, or man-made objects or structures. The acoustic sensors are capable of detecting and tracking unmanned aerial systems in non-line-of-sight environments. In some embodiments, the acoustic sensors may be in communication with internal electro-optical components or other external sensors, with orthogonal signal data then transmitted to remote observation stations for correlation, threat determination and if required, mitigation. The unmanned aerial systems may be classified by type and a threat level associated with the unmanned aerial system may be determined.

Abstract: A target vehicle recognition apparatus for recognizing a target vehicle as a target to be avoided by steering control of a host vehicle detects a stopped vehicle located in front of the host vehicle, determines whether the stopped vehicle is in a forward-facing state to the host vehicle or a rearward-facing state to the host vehicle, determines whether the stopped vehicle is in a right boundary line deviation state crossing a right boundary line of a travel lane of the host vehicle, a left boundary line deviation state crossing a left boundary line of the travel lane, and recognizes the target vehicle for steering control based on a captured image captured by a front camera of the host vehicle and each of the determination results.

Abstract: A method includes causing an aerial vehicle to deploy a tethered component to a particular distance beneath the aerial vehicle by releasing a tether connecting the tethered component to the aerial vehicle. The method also includes obtaining, from a camera connected to the aerial vehicle, image data that represents the tethered component while the tethered component is deployed to the particular distance beneath the aerial vehicle. The method additionally includes determining, based on the image data, a position of the tethered component within the image data. The method further includes determining, based on the position of the tethered component within the image data, a wind vector that represents a wind condition present in an environment of the aerial vehicle. The method yet further includes causing the aerial vehicle to perform an operation based on the wind vector.

Abstract: Aspects of the disclosure provide for automatically generating labels for sensor data. For instance first sensor data for a first vehicle is identified. The first sensor data is defined in both a global coordinate system and a local coordinate system for the first vehicle. A second vehicle is identified based on a second location of the second vehicle within a threshold distance of the first vehicle within the first timeframe. The second vehicle is associated with second sensor data that is further associated with a label identifying a location of an object, and the location of the object is defined in a local coordinate system of the second vehicle. A conversion from the local coordinate system of the second vehicle to the local coordinate system of the first vehicle may be determined and used to transfer the label from the second sensor data to the first sensor data.

Abstract: A target vehicle recognition apparatus detects a stopped vehicle ahead of the host vehicle, detects a reference boundary line position where at least one of two boundary lines forming a travel lane of the host vehicle intersects a reference axis extending from a lower end of the stopped vehicle in an image horizontal direction on a captured image, recognizes the stopped vehicle as a target vehicle of steering control when the reference boundary line position between a vehicle left end position of the stopped vehicle and a vehicle right end position of the stopped vehicle is present, and does not recognize the stopped vehicle as a target vehicle of steering control when the reference boundary line position between the vehicle left end position of the stopped vehicle and the vehicle right end position of the stopped vehicle is not present.

Abstract: Disclosed is a navigation system configured to track an object. The navigation system comprises a tracker configured to couple to the object and a localization device configured to track the tracker. The tracker and the localization device are configured to wirelessly communicate using a first communication method operable on a first spectrum and to wirelessly communicate using a second communication method operable on a second spectrum different from the first spectrum. The localization device utilizes the first communication method to track the tracker and utilizes the first communication method to manage an operating parameter of the tracker with respect to the second communication method.

Abstract: A medical device of an embodiment includes at least one movably mounted and motor-adjustable component; at least one drive unit for adjusting the at least one component; at least one motor control unit associated with the drive unit; and at least one sensing unit for sensing a position parameter dependent on the position of the at least one component. According to an embodiment of the invention, a safety function is integrated in the motor control unit. The safety function limits at least one operating parameter associated with the motion of the at least one component to be performed. An apparatus control unit controls the drive unit in dependence on the position parameter in accordance with the safety function. At least one embodiment of the invention further relates to a method for operating a medical device.

Abstract: An occurrence of one or more “care events” is detected by an electronic device monitoring environmental data and/or user data from one or more sensors. The electronic device transmits one or more alerts regarding the detected occurrence to at least one other electronic device. In some cases, the electronic device may cooperate with at least one other electronic device in monitoring, detecting, and/or transmitting. For example, the electronic device may detect the occurrence based on sensor data received from a cooperative electronic device or such data in combination with the electronic device's sensor data. By way of another example, the electronic device may detect the occurrence and signal a cooperative electronic device to transmit one or more alerts.

Abstract: An apparatus for warning the collision of a vehicle includes an information acquirer configured to acquire information on a surrounding object and information on a vehicle, and a controller configured to generate collision predicting information for the surrounding object, based on the information on the surrounding object and the information on the vehicle, and generate control information to control braking of the vehicle and to provide, based on the collision predicting information, a buffer element to an outside of the vehicle while controlling the braking of the vehicle.

Abstract: Provided is a vehicle including an autonomous driver assistance system. The vehicle is capable of: acquiring a road image while driving; recognizing other vehicles and lanes from the acquired road image; recognizing the recognized driving pattern of the other vehicle based on the recognized location information of the other vehicle and the recognized location information of the lane, determining whether the other vehicle is a vehicle that fails to comply with a safety driving obligation based on the recognized driving pattern, outputting warning information when it is determined that the other vehicle is not complying with the safety driving obligation; determining whether a lane change is necessary based on the recognized location information of the lane of the other vehicle and the driving pattern of the other vehicle; guiding the lane change when it is determined that it is necessary to change the lane.

Abstract: Provided is an apparatus for assisting driving of a host vehicle, the apparatus comprising: a camera mounted to the host vehicle and having a field of view in front of the host vehicle, the camera configured to acquire image data; and a controller including a processor configured to process the image data. The controller may identify at least one object obstructing driving of the host vehicle based on the image data, and control a steering controller of a steering device to apply a periodically varying dithering torque to the steering device of the host vehicle in response to a collision with the at least one object being expected. The apparatus for assisting driving of a host vehicle may shorten the response time for emergency steering.

Abstract: A vehicle reducing unease of a driver during driver assistance, provided with a display device configured to display a surrounding vehicle together with a host vehicle at a relative position calculated by an object recognition device, display a mark showing that a lane change is planned to be performed at a predetermined space for performing a lane change in a destination driving lane which is a destination for a lane change when an automatic lane change is planned to be performed, and make a position of the mark change in accordance with the relative position of the surrounding vehicle when there is a surrounding vehicle present having an effect on a lane change in the destination driving lane.

Abstract: A three-dimensional point cloud label learning and estimation device includes: a clustering unit that clusters a three-dimensional point cloud into clusters; a learning unit that makes a neural network learn to estimate a label corresponding to an object to which points contained in each of the clusters belong; and an estimation unit that estimates a label for the cluster using the neural network learned at the learning unit. In the three-dimensional point cloud label learning and estimation device, the neural network uses a total sum of sigmoid function values (sum of sigmoid) when performing feature extraction on the cluster.

Abstract: The apparatus for controlling group driving according to as aspect may include an inter-vehicle communication unit for communicating with a leader vehicle to receive the driving state and traveling track of the leader vehicle, a leader vehicle learning unit for learning a driving pattern of the leader vehicle based on the driving state of the leader vehicle received through the inter-vehicle communication unit, an autonomous drive unit for autonomously driving the follower vehicle in accordance with the traveling track of the leader vehicle, and a follow-up control unit for receiving the driving state of the leader vehicle to learn the driving pattern of the leader vehicle, controlling the autonomous drive unit to follow the traveling track of the leader vehicle, and performing the autonomous driving by applying the driving pattern of the leader vehicle.

Abstract: A turning work vehicle includes a lower travel body, an upper turning body, a work device, a rotation body, and a support column. The lower travel body is provided with a blade. The upper turning body is supported by the lower travel body so as to be able to turn. The work device is supported by the upper turning body so as to be able to rotate. The rotation body is provided to the blade. The support column projects from the rotation body. A target prism, which is the measurement object of a total station, can be secured to the support column. The rotation body rotates in relation to the blade, whereby the posture of the support column is configured so as to be able to switch between an upright posture and a fallen posture.

Abstract: A map in a cloud service stores physical objects previously detected by other vehicles that have previously traveled over the same road that a current vehicle is presently traveling on. New data received by the cloud service from the current vehicle regarding new objects that are being encountered by the current vehicle can be compared to the previous object data stored in the map. Based on this comparison, an operating status of the current vehicle is determined. In response to determining the status, an action such as terminating an autonomous navigation mode of the current vehicle is performed.

Abstract: In the method, a predetermined first number of sensed positions (Pi) of the object (20) are provided, the positions being provided with respect to a vehicle coordinate system (K) of the vehicle (10). Depending on a predetermined second number of the provided positions, a second coordinate system (K?) is determined. The provided positions are transformed into the second coordinate system (K?) and a function is determined which approximates a course of the provided positions in the second coordinate system (K?). For a predetermined third number of sampling points of the function, at least one analytical property of the function is determined at the respective sampling point. The coordinates and the at least one analytical property of the respective sampling point are transformed into the vehicle coordinate system (K).

Abstract: Techniques for aggregating costs associated with one or more heat maps to control a vehicle in an environment are discussed herein. A vehicle computing device can implement a model to determine heat maps and respective cost information for different features of the environment based on sensor data. The vehicle computing device can output a planned trajectory for the vehicle based on combining the heat maps. The techniques can also include determining a rationalization or root cause detailing reasons why the planned trajectory was determined.

Abstract: An approach is provided for determining travel direction and/or location data based on sequential semantic events. The approach, for example, involves processing sensor data collected from at least one sensor of a mobile device to determine a set of observed time-sequenced semantic events. The semantic events are associated with traveling within a transportation system, and at least one semantic event of the set of observed time-sequenced semantic events is based on a turn angle value determined from the sensor data. The approach also involves initiating a comparison of the set of observed time-sequenced semantic events against a set of known time-sequenced semantic events and/or a known piece of information associated with the transportation system. The approach further involves determining a direction of travel and/or a location of the mobile device within the transportation system based on the comparison. The approach further involves providing the direction of travel and/or the location as an output.

Abstract: A computer-implemented method, a computer system, and a computer program product for trajectory similarity search is provided. The present invention may include, in response to receiving, by one or more processors, a search request for at least one trajectory similar to a query trajectory, determining, by one or more processors, a respective similarity between a query trajectory and a plurality of trajectories by calculating, in a synchronized way, a spatial distance measure and a time difference measure between the query trajectory and the plurality of trajectories. The present invention may further include, identifying, by one or more processors, the at least one trajectory from the plurality of trajectories based on the respective similarity between the query trajectory and the plurality of trajectories.

Abstract: Systems and methods are provided for navigating an autonomous vehicle. In one implementation, a navigational system for a host vehicle may include at least one processor programmed to: receive a stream of images captured by a camera onboard the host vehicle, wherein the captured images are representative of an environment surrounding the host vehicle; and receive an output of a LIDAR onboard the host vehicle, wherein the output of the LIDAR is representative of a plurality of laser reflections from at least a portion of the environment surrounding the host vehicle.

Abstract: A server jointly tracks states of multiple vehicles using measurements of satellite signals received at each vehicle and parameters of the probabilistic distribution of the state of each vehicle. The server fuse states and measurements into an augmented state of the multiple vehicles and an augmented measurement of the augmented state subject to augmented measurement noise defined by a non-diagonal covariance matrix with non-zero off-diagonal elements, each non-zero off-diagonal elements relating errors in the measurements of a pair of corresponding vehicles. The server executes a probabilistic filter updating the augmented state and fuses the state of at least some of the multiple vehicles with a corresponding portion of the updated augmented state.

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: A map information correction apparatus includes a feature point priority determination unit that determines a priority for a feature point of own mobile object surrounding information. A feature pair priority determination unit gives, when there is one or more feature pairs, a priority to the feature pair, based on an own mobile object surrounding information priority of the feature pair and a map information priority of the feature pair. The feature pair is a pair of an own mobile object surrounding information feature point and a received map information feature point that correspond to each other. An error calculation unit calculates an error in the map information, based on a high-priority own mobile object surrounding information feature point and a high-priority map information feature point. A correction unit corrects the map information using the error.

Abstract: A tracking system for tracking an expanded state of an object is provided. The tracking system comprises at least one processor and a memory having instructions stored thereon that, when executed by the at least one processor, cause the tracking system to execute a probabilistic filter that iteratively tracks a belief on the expanded state of the object, wherein the belief is predicted using a motion model of the object and is further updated using a compound measurement model of the object. The compound measurement model includes multiple probabilistic distributions constrained to lie on a contour of the object with a predetermined relative geometrical mapping to the center of the object. Further, the tracking system tracks the expanded state of the object based on the updated belief on the expanded state.

Abstract: Techniques and systems are disclosed for using swept volume profile data cached in association with a PRM to improve various aspects of motion planning for a robot. In some implementations, a first probabilistic road map representing possible paths to be travelled by a robot within a physical area is generated. An initial path for the robot within the first probabilistic road map is determined. Data indicating a second probabilistic road map representing a path to be travelled by a movable object within the physical area is obtained. A potential obstruction associated with one or more edges included in the subset of edges is detected. An adjusted path for the robot within the first probabilistic road map is then determined based on the potential obstruction.

Abstract: The present disclosure is directed to systems and methods avoiding collisions by monitoring the presence and alertness of a person in a vehicle. The alertness of that person may be monitored by identifying actions performed by that person when an automated driving assistant is used in a vehicle. Systems and method consistent with the present disclosure may monitor the alertness of a person that is located in a driving position of a vehicle according to criteria associated with particular individuals or with criteria associated with specific protocols. When a system or method consistent with the present disclosure identifies that a person is not alert, a corrective action may be initiated that reduces likelihood of a collision.

Abstract: A method for calculating a time to contact of an autonomous vehicle, the method comprising: obtaining a plurality of event data an image, wherein the event data is associated with a pixel associated with a change in light intensity; determining a reference signal frequency associated with a transmitted light; identifying a select event data from the plurality of event data, wherein the light frequency associated with the select event data is substantially the same as the reference signal frequency; determining an object based on the select event data, wherein the object is fully enclosed by a bounding box comprising coordinates of a rectangular border; calculating a distance between a set of coordinates of the bounding box closest to the autonomous vehicle and the autonomous vehicle; and calculating the time to contact between the set of coordinates of the bounding box and the autonomous vehicle.

Abstract: The present disclosure relates to the field of swarm intelligence and provides a multi-intelligent-agent cooperated transportation method and system as well as a computer readable storage medium.

Abstract: A system and a method for tracking an expanded state of an object including a kinematic state indicative of a position of the object and an extended state indicative of one or combination of a dimension and an orientation of the object is provided herein. The system comprises at least one sensor configured to probe a scene including a moving object with one or multiple signal transmissions to produce one or multiple measurements of the object per the transmission, and a processor configured to execute a probabilistic filter tracking a joint probability of the expanded state of the object estimated by a motion model of the object and a measurement model of the object, wherein the measurement model includes a center-truncated distribution having predetermined truncation intervals. The system further comprises an output interface configured to output the expanded state of the object.

Abstract: Techniques disclosed provide for enhanced V2X communications by defining information Elements (IE) for V2X messaging between V2X entities. For a transmitting vehicle that sends a V2X message to a receiving vehicle, these IEs are indicative of a detected vehicle model type detected by the transmitting vehicle of a detected vehicle; a pitch rate of the transmitting vehicle, a detected vehicle, or a detected object; a roll rate of the transmitting vehicle, a detected vehicle, or a detected object; a yaw rate of a detected vehicle, or a detected object; a pitch rate confidence; a roll rate confidence; an indication of whether a rear brake light of a detected vehicle is on; or an indication of whether a turning signal of a detected vehicle is on; or any combination thereof. With this information, the receiving vehicle is able to make more intelligent maneuvers than otherwise available through traditional V2X messaging.

Abstract: The present disclosure relates to a method for generating a panoramic surround view image of a vehicle, comprising: acquiring actual original images of external environment of a first part and a second part of the vehicle hinged to each other; processing the actual original images to obtain respective actual independent surround view images of the first part and the second part; obtaining coordinates of respective hinge points of the first part and the second part; determining matched feature point pairs in the actual independent surround view images of the first part and the second pan; calculating a distance between two points in each matched feature point pair accordingly, and taking matched feature point pairs with the distance less than a preset first threshold as a successfully matched feature point pairs; and taking a rotation angle corresponding to the maximum number of the successfully matched feature point pairs as a candidate rotation angle of the first part relative to the second part.

Abstract: A driving assistance apparatus in a vehicle, the driving assistance apparatus comprising an acquisition unit configured to acquire a location coordinate of a self-vehicle at a predetermined period of time, a specification unit configured, based on a plurality of the location coordinates acquired continuously by the acquisition unit, to specify a curved region of a road, and a registration unit configured to register the curved region specified by the specification unit in a database predetermined.

Abstract: A method and system of deploying, creating and certifying the “virtual presence” of a user at a location other than the actual location of the user that verifiably associates a power of attorney or agency contract and a “representing entity” to (1) establish the authority of a “representing entity” to act as if the user were physically present at the remote location, and (2) submit the “representing entity” to the jurisdiction of the remote location, even though the user is at a different location and only virtually “present” at the remote location. The representing entity could be an animate object or device located at the remote location, such as a robot, drone, or vehicle, or a “presence” that only exists electronically, commonly referred to as an “avatar.

Abstract: Provided imaging control apparatus effectively avoid image capturing competition in a scene in which a large number of infrared cameras capture images. The imaging control apparatus includes an image acquisition unit that acquires an infrared image generated by an infrared camera imaging reflected light of emitted infrared rays; and a control unit that controls a setting for the generation of the infrared image on the basis of a control parameter transmitted to another apparatus or received from another apparatus via a communication interface.

Abstract: A control device for a loading machine includes a measurement data acquisition unit that acquires measurement data of a measurement device mounted on the loading machine that includes working equipment, a target calculation unit that extracts, from the measurement data, loading target data being measurement data on a loading target on which excavated material excavated by the working equipment is loaded and calculates, based on the loading target data, height data indicating a height of an upper end portion of the loading target and distance data indicating a distance from the loading machine to the loading target, and a working equipment control unit that controls the working equipment based on the height data and the distance data.

Abstract: Described herein are systems, methods, and non-transitory computer readable media for constructing and utilizing vehicle field-of-view (FOV) information. The FOV information can be utilized in connection with vehicle localization such as localization of an autonomous vehicle (AV), sensor data fusion, or the like. A customized computing machine can be provided that is configured to construct and utilize the FOV information. The customized computing machine can utilize the FOV information, and more specifically, FOV semantics data included therein to manage various data and execution patterns relating to processing performed in connection with operation of an AV such as, for example, data prefetch operations, reordering of sensor data input streams, and allocation of data processing among multiple processing cores.

Abstract: A self-position estimation device equipped to a vehicle: captures an image of a periphery of the vehicle; detects a state quantity of the vehicle; acquires position information indicating a position of the vehicle from a satellite system; stores map data that defines a map in which a road is expressed by a link and a node; estimate a self-position of the vehicle on the map, as an estimation position, based on the captured image, the state quantity, the position information, and the map data, respectively; recognizes a road section in which a lane quantity increases or decreases based on the captured image; and sets a weighting of the estimation position of the vehicle estimated based on the map data relatively smaller in response to a recognition of the road section in which the lane quantity increases or decreases.

Abstract: Systems and methods for controlling an autonomous vehicle are described. A trajectory planner module provides a first trajectory to a trajectory control module. The trajectory control module determines parameters of the first trajectory. The trajectory control module compares the parameters to a respective threshold value. The trajectory control module obtains one or more alternative trajectories, determines parameters of each alternative trajectory, and compares the parameters of the alternative trajectory to a respective threshold value. The trajectory control module selects a trajectory for controlling the autonomous vehicle that has parameters which are within a range defined by the threshold values and controls the autonomous vehicle based on the selected trajectory. Thus, before handing back control to a driver, the trajectory control module selects from alternate trajectories for controlling the autonomous vehicle.

Abstract: A driving support system executes a risk avoidance control for reducing a risk of collision with an object in front of a vehicle. A risk potential field represents a risk value as a function of position. An obstacle potential field is a risk potential field in which the risk value is maximum at a position of the object and decreases as a distance from the object increases. A vehicle center potential field is the risk potential field in which a valley of the risk value extends in a lane longitudinal direction from a position of the vehicle. A first risk potential field is the sum of the vehicle center potential field and the obstacle potential field. The driving support system executes a steering control such that the vehicle follows the first valley of the risk value represented by the first risk potential field.

Abstract: An aviation radio frequency database and radio frequency control system to automate the retrieval of radio frequencies and tuning of an aircraft radio includes a portable electronic device intended to relieve pilots of retrieving radio frequencies manually from maps, notes and directories eliminates the manual switching of frequencies on radios and other electronic devices replacing these procedures with a direct wireless link from a controlling device to the radio or other electronic device. The application of the invention is not limited to aviation but can be utilized in any utility scenario where operation calls for parameter changes, the object is conserving time and human effort, and raising standards of accuracy and system integrity. Remote control of onboard radio and other controllable electronics is achieved both by delivery of control codes and by use of a voice-to-text application.

Abstract: Techniques and systems are disclosed for using swept volume profile data cached in association with a PRM to improve various aspects of motion planning for a robot. In some implementations, a first probabilistic road map representing possible paths to be travelled by a robot within a physical area is generated. An initial path for the robot within the first probabilistic road map is determined. Data indicating a second probabilistic road map representing a path to be travelled by a movable object within the physical area is obtained. A potential obstruction associated with one or more edges included in the subset of edges is detected. An adjusted path for the robot within the first probabilistic road map is then determined based on the potential obstruction.

Abstract: An online concierge system receives an order from a customer. The online concierge system transmits a notification to the customer's client device indicating that the order is ready for pick up and receives location data from the customer's client device as the customer travels to a pickup location. In response to the online concierge system receiving a first indication that the customer has entered an outer geofence, the online concierge system transmits a second notification to a runner's client device that the customer is in transit. In response to the online concierge system receiving a second indication that the customer has entered an inner geofence, the online concierge system starts a timer. When the online system receives a confirmation that the order has been picked up by the customer, it stops the timer and computes a wait time for pick up of the order.

Abstract: Systems, computer program products, and methods are described herein for centralized resource transformation engine within a technical environment.

Abstract: Described are a mechanical scanning unit (32) of an optical transmission and receiving device of an optical detection apparatus of a vehicle, an optical transmission and receiving device, an optical detection apparatus, a driver assistance device and a vehicle. The scanning unit (32) comprises at least one first beam influencing device (42) for deflecting at least one light beam (38), which has been radiated into the scanning unit (32), in a first direction (y) and at least one second beam influencing device (44) for changing a beam propagation of the at least one light beam (38) in a second direction (z). The at least one second beam influencing device (44) is arranged in the beam path of the at least one light beam (38) downstream of the at least one first beam influencing device (42). The first direction (y) and the second direction (z) extend perpendicularly or at an angle with respect to one another.

Abstract: The present disclosure discloses a method for monitoring driving behavior risk degree, including: acquiring first vehicle size information of a first vehicle, second vehicle size information of a second vehicle, vehicle driving information and vehicle driving environment information; determining the number of overlapping regions of the first vehicle and the second vehicle based on the first vehicle size information, the second vehicle size information and the vehicle driving information; and determining risk degree information of driving behavior based on the number of overlapping regions, the vehicle driving information and the vehicle driving environment information. This method may be applied in multiple scenarios, and facilitates drivers or passengers in avoiding them from traffic collision incidents, so that the safeties of the drivers and the passengers is greatly improved.

Abstract: A data collector collects device data obtained from a device that is placed, for example, at a home, a workplace or the like. A distribution data generator adds ancillary information (for example, a time, a unit, precision, a resolution, a content of processing, a manufacturer, a model number or the like) to the device data collected by the data collector, thereby generating distribution data. A data provider provides, to an outside, (for example, to a data usage server), the distribution data generated by the distribution data generator.

Abstract: A method for risk based processing, the method may include detecting, based on first sensed information sensed at a first period, a suspected risk within an environment of a vehicle; selecting, from reference information, a situation related subset of the reference information, wherein the situation related subset of the reference information is related to the situation; selecting, from reference information, a suspected risk related subset reference information, wherein the potential risk related subset of the reference information is related to the potential risk; and determining whether the suspected risk is an actual risk, based at least on part on the suspected risk related subset reference information.

Abstract: Autonomous vehicle operation with explicit occlusion reasoning may include traversing, by a vehicle, a vehicle transporation network. Traversing the vehicle transportation network can include receiving, from a sensor of the vehicle, sensor data for a portion of a vehicle operational environment, determining, using the sensor data, a visibility grid comprising coordinates forming an unobserved region within a defined distance from the vehicle, computing a probability of a presence of an external object within the unobserved region by comparing the visibility grid to a map (e.g., a high-definition map), and traversing a portion of the vehicle transportation network using the probability. An apparatus and a vehicle are also described.

Abstract: A control device detects a first vehicle traveling in front of an own vehicle using a front looking radar device, and detects a second vehicle which is predicted to cut in between the own vehicle and the first vehicle using the front looking radar device and/or front-side looking radar devices. The control device calculates a first target acceleration required for the own vehicle to maintain an inter-vehicle distance between the own vehicle and the first vehicle at a first set inter-vehicle distance; and calculates a second target acceleration required for the own vehicle to maintain an inter-vehicle distance between the own vehicle and the second vehicle at a second set inter-vehicle distance. The control device selects either the first target acceleration or the second target acceleration and controls the own vehicle in such a manner that an actual acceleration of the own vehicle becomes closer to the mediated target acceleration.