Abstract: A vehicle data collection system includes a vehicle-mounted sensor; a non-transitory computer readable medium configured to store instructions; and a processor connected to the non-transitory computer readable medium. The processor is configured to execute the instructions for generating an invariant feature map, using a first neural network; and comparing the invariant feature map to template data to determine a similarity between the invariant feature map and the template data, wherein the template data is received from a server. The processor is further configured to execute the instructions for determining whether the determined similarity is exceeds a predetermined threshold; and instructing a transmitter to send the sensor data to the server in response to a determination that the determined similarity exceeds the predetermined threshold.

Abstract: Embodiments of the present disclosure are directed towards a system and method for performing an inspection of an underwater environment. Embodiments may include providing an autonomous underwater vehicle (“AUV”) and performing an inspection of an underwater environment using the AUV. Embodiments may further include acquiring real-time sensor data during the inspection of the underwater environment and applying an active simultaneous localization and mapping (“SLAM”) algorithm during the inspection, wherein applying includes estimating one or more virtual landmarks based upon, at least in part, at least one past measurement and a current estimate of AUV activity.

Abstract: A method for determining information on an expected trajectory of an object comprises: determining input data being related to the expected trajectory of the object; determining first intermediate data based on the input data using a machine-learning method; determining second intermediate data based on the input data using a model-based method; and determining the information on the expected trajectory of the object based on the first intermediate data and based on the second intermediate data.

Abstract: Systems and methods for coordinating point of interest pickups in a transportation service are provided. In example embodiments, the system detects a location of a device of a user. Responsive to detecting the location of the device of the user, the system automatically determines one or more potential pickup points based on the detected location. A pickup point user interface (UI) that displays one or more potential pickup points based on the detected location is presented on the device of the user without displaying a map. The system receives confirmation of a pickup point from the one or more potential pickup points and receives an indication of a destination. The system then establishes the transportation service based on the confirmed pickup point and the destination. The system can provide user interfaces that display progress of a driver to the pickup point and progress to the destination without displaying a map.

Abstract: An operation management apparatus includes a plan generator configured to generate a travel plan for each of a plurality of vehicles that form a line of vehicles and that travel autonomously along a predetermined travel route; a communication device configured to transmit the travel plans to the respective vehicles and receive, from the vehicles, travel information that indicates travel status of the vehicles; and an operation monitor configured to detect, based on the travel information, whether or not overtaking and passing of the vehicles have occurred. In response to the overtaking and passing, the plan generator modifies the travel plans so as to keep the order as switched upon the overtaking and passing.