Abstract: A system for context-aware decision making of an autonomous agent includes a computing system having a context selector and a map. A method for context-aware decision making of an autonomous agent includes receiving a set of inputs, determining a context associated with an autonomous agent based on the set of inputs, and optionally any or all of: labeling a map; selecting a learning module (context-specific learning module) based on the context; defining an action space based on the learning module; selecting an action from the action space; planning a trajectory based on the action S260; and/or any other suitable processes.

Abstract: A network system can receive, from a user device of a requesting user, a query related to a first service. If the network system determines that a first service provider is in progress of providing a second service for the requesting user, the network system can identify, based on a service location of the second service, a plurality of entities that provide items available for selection in association with the first service. The network system can further determine whether to select the first service provider to fulfill the request for the first service based on an estimated first service duration associated with the first service and an estimated duration remaining for the second service. The first service duration can be estimated based on respective timing information associated one or more items selected by the requesting user. The network system can update a route for the first service provider.

Abstract: Aspects and implementations of the present disclosure address shortcomings of the existing technology by enabling lidar-assisted segmentation and identification of particulate matter in autonomous vehicle (AV) applications, by: obtaining, by a sensing system of the AV, a plurality of return points, each return point having one or more velocity values and one or more coordinates of a reflecting region that reflects a signal emitted by the sensing system, identifying, in view of the one or more velocity values of each of a first set of the return points of the plurality of return points, that the first set of the return points is associated with a particulate matter in an environment of the AV, and causing a driving path of the AV to be determined in view of the particulate matter.

Abstract: Example embodiments relate to identification of proxy calibration targets for a fleet of sensors. An example method includes collecting, using a sensor coupled to a vehicle, data about one or more objects within an environment of the vehicle. The sensor has been calibrated using a ground-truth calibration target. The method also includes identifying, based on the collected data, at least one candidate object, from among the one or more objects, to be used as a proxy calibration target for other sensors coupled to vehicles within a fleet of vehicles. Further, the method includes providing, by the vehicle, data about the candidate object for use by one or more vehicles within the fleet of vehicles.

Abstract: Some embodiments provide a mapping application that displays a transit map including a group of transit lines. The mapping application receives a request to display a transit route in the transit map. The mapping application also, in response to the received request, displays the transit route by modifying portions of transit lines along the route to emphasize the portions of the transit lines while modifying other transit lines not along the route to de-emphasize the transit lines not along the route.

Abstract: A vehicle-to-infrastructure cooperation information processing method, apparatus, device and an autonomous vehicle are provided. The method includes: acquiring first on-board perception data of a target vehicle, the first on-board perception data including data of an obstacle around the target vehicle sensed by the target vehicle; generating virtual obstacle data for representing the target vehicle according to positioning data of the target vehicle; generating second on-board perception data based on the virtual obstacle data and the first on-board perception data; and fusing the second on-board perception data with roadside perception data to obtain fusion data, the fusion data including all obstacle data in both the second on-board perception data and the roadside perception data, and the obstacle data in the roadside perception data including obstacle data for representing the target vehicle.

Abstract: A vehicle control system includes a controller that detects a communication loss between a first vehicle and a second vehicle and/or a monitoring device in a vehicle system. The controller operationally restricts movement of the vehicle system based on the communication loss. The controller obtains or generates a transitional plan that designates operational settings for the first vehicle and/or the second vehicle based at least in part on a location of the first vehicle and/or the second vehicle. The controller selectively changes movement of the first vehicle and/or the second vehicle via the transitional plan to reduce a speed of the first vehicle and/or the second vehicle responsive to the communication loss being detected.

Abstract: An occupancy grid manager having a non-uniform occupancy which includes a plurality of cells, configurable in a plurality of cell sizes, each cell representing a region of an environment of a vehicle; and one or more processors, configured to determine one or more context factors; select a cell size for a cell of the plurality of cells based on the one or more context factors; process sensor data provided by one or more sensors; and determine a probability that the cell of the plurality of cells is occupied based on the sensor data.

Abstract: Disclosed are a control method of a mobile robot, a mobile robot, and a storage medium. The method includes: when distance information obtained by a laser radar has an effective distance change, predicting an inclination angle of a forward road section relative to a current road surface where the mobile robot is currently located; determining a slope of the forward road section based on the inclination angle and a pitch angle; controlling movement of the mobile robot based on the slope and a result of comparison between the slope and a slope threshold preset by the mobile robot; and marking the forward road section as a slope area on a slope map, where the slope map is used to control, based on the slope area when the mobile robot passes by the slope area, the mobile robot to send climbing warning information.

Abstract: A vehicle collision determination system includes an acceleration sensor fixedly positioned to a front end of the vehicle and configured to measure acceleration at a fixed position, a detector configured to detect whether the vehicle collides using the acceleration measured by the acceleration sensor, a metrics setting unit configured to set at least one metric using the acceleration measured by the acceleration sensor when the detector detects collision of the vehicle, and a determiner configured to determine whether an object that has collided with the vehicle is a pedestrian using the at least one metric set by the metrics setting unit.

Abstract: A parking assist apparatus includes an ECU. The ECU displays a first left support image on a predetermined display area of a touch panel display section so that an entire area of a tentative target parking space is displayed within the predetermined display area, based on a relative position of the tentative target parking space with respect to a vehicle.

Abstract: A method includes receiving one or more search terms at a mobile computing device while the mobile computing device is located at a particular location. A search query that includes the one or more search terms and a location history of the mobile computing device is transmitted to a server. The method also includes receiving one or more search results in response to the search query, where the one or more search results include content identified based on a predicted destination of the mobile computing device. An interface identifying the one or more search results is displayed at the mobile computing device.

Abstract: Provided is an image processing method. The image processing method includes receiving images acquired from a plurality of vehicles positioned on a road; storing the received images according to acquisition information of the received images; determining a reference image and a target image based on images having the same acquisition information among the stored images; performing an image registration using a plurality of feature points extracted from each of the determined reference image and target image; performing a transparency process for each of the reference image and the target image which are image-registered; extracting static objects from the transparency-processed image; and comparing the extracted static objects with objects on map data which is previously stored and updating the map data when the objects on the map data which is previously stored and the extracted static objects are different from each other.

Abstract: A method, apparatus, and system for filtering obstacle candidates determined based on outputs of a LIDAR device in an autonomous vehicle is disclosed. A point cloud comprising a plurality of points is generated based on outputs of the LIDAR device. One or more obstacle candidates are determined based on the point cloud. The one or more obstacle candidates are filtered to remove a first set of obstacle candidates in the one or more obstacle candidates that correspond to noise based at least in part on characteristics associated with points that correspond to each of the one or more obstacle candidates. One or more recognized obstacles comprising the obstacle candidates that have not been removed are determined. Operations of an autonomous vehicle are controlled based on the recognized obstacles.

Abstract: A trailer flank object contact avoidance system for a vehicle towing a trailer includes a sensor system configured to detect objects in an operating environment of the vehicle and a controller. The controller processes information received from the sensor system to monitor a relative position of at least one object with respect to the vehicle during driving and determines an instantaneous path of the trailer based on a vehicle steering angle and whether the instantaneous path of the trailer would bring the trailer into contact with the at least one object. The controller issues a coaching notification to the driver that reverse driving is required to prevent contact between the trailer and the vehicle when a corrective steering angle cannot prevent contact of the trailer with the at least one object during forward driving.

Abstract: A vision-cued random-access LIDAR system and method which determines the location and/or navigation path of a moving platform. A vision system on a moving platform identifies a region of interest. The system classifies objects within the region of interest, and directs random-access LIDAR to ping one or more of the classified objects. The platform is located in three dimensions using data from the vision system and LIDAR. The steps of classifying, directing, and locating are preferably performed continuously while the platform is moving and/or the vision system's field-of-view (FOV) is changing. Objects are preferably classified using at least one smart-vision algorithm, such as a machine-learning algorithm.

Abstract: A method and device for a vehicle having wheels which are each assigned a sensor for generating wheel signals. The unit determines whether a wheel is affected by a failure of the corresponding wheel signal. The unit acquires wheel signals which are assigned to the wheels, and for a wheel affected by a wheel signal failure, the corresponding wheel signal is acquired in the form of a substitute signal. The unit calculates a target brake pressure for a wheel at which an increase in brake pressure is necessary. The increase in brake pressure takes place in accordance with the wheel signal which is obtained for the wheel and in accordance with the determination as to whether the wheel is affected by a wheel signal failure. The unit further determines a slip threshold for an anti-lock brake control operation applied to the wheel affected by the wheel signal failure.

Abstract: A terrestrial acoustic sensor array for detecting and preventing airspace collision with an unmanned aerial vehicle (UAV) includes a plurality of ground-based acoustic sensor installations, each of the acoustic sensor installations including a sub-array of microphones. The terrestrial acoustic sensor array may further include a processor for detecting an aircraft based on sensor data collected from the microphones of at least one of the plurality of acoustic sensor installations and a network link for transmitting a signal based on the detection of the aircraft to a control system of the UAV.

Abstract: An example system includes a sensor for obtaining information about an object in an environment and one or more processing devices configured to use the information in generating or updating a map of the environment. The map includes the object and boundaries or landmarks in the environment. The map includes a static score associated with the object. The static score represents a likelihood that the object will remain immobile within the environment. The likelihood may be between certain immobility and certain mobility.

Abstract: A method for logging and reporting driver activity and operation data of a vehicle. The method utilizes an onboard recorder operatively connected to a data bus of the vehicle and configured to continuously electronically monitor and obtain vehicle operation data including vehicle mileage data. Data processing software is operable for generating an hours of service log and a vehicle fuel tax log.