Abstract: Systems, methods, and devices for determining a location of a vehicle or other device are disclosed. A method includes receiving sensor data from a sensor and determining a prior map comprising LIDAR intensity values. The method includes extracting a sub-region of the prior map around a hypothesis position of the sensor. The method includes extracting a Gaussian Mixture Model (GMM) distribution of intensity values for a region of the sensor data by expectation-maximization and calculating a log-likelihood for the sub-region of the prior map based on the GMM distribution of intensity values for the sensor data.

Abstract: A method and system of detecting when a navigable element previously determined to be closed is in an open state is disclosed, the navigable element forming part of a network of navigable elements within a geographic area, the navigable elements being represented by segments of an electronic map. Positional data relating to the movement of a plurality of devices along the navigable elements of the navigable network with respect to time is obtained, and a navigable element is identified as being in a closed state based at least on the positional data and a first visit interval associated with the segment representing the navigable element. The positional data is then used to determine a second visit interval for the segment representing the navigable element, and the navigable element is changed to be in an open state when a parameter based on the determined second visit interval for the segment representing the navigable element passes a predetermined threshold value.

Abstract: A method for determining the position of a vehicle, including sensing of multiple objects in a surround field of the vehicle, detecting a sequence of the multiple sensed objects in a digital map and determining a position of the vehicle in the digital map based on a position of the detected sequence in the digital map. An apparatus for determining the position of a vehicle, as well as to a computer program are also described.

Abstract: Systems and methods for detection and interdiction of drone vehicles with respect to controlled-environment facilities may monitor electromagnetic signals originating within or transiting operational boundaries associated with a controlled-environment facility, receive the electromagnetic signals originating within or transiting the operational boundaries associated with the controlled-environment facility, and analyze the received electromagnetic signals to determine if the received electromagnetic signals are controlling or associated with a drone. This monitoring may be carried-out by a software-defined radio associated with a central access point of a wireless communications managed access system of the controlled-environment facility and the electromagnetic signals may be received by the software-defined radio of the managed access system (central access point).

Abstract: The present disclosure provides an inter-vehicle communication system configured to detect a vehicle as a communication target of DSRC to properly establish an automatic driving system. In the inter-vehicle communication system configured to perform communication between a plurality of vehicles using DSRC, each of vehicles includes an identification code (ID) of the vehicle in information to be transmitted by a DSRC unit. Each vehicle includes: an individual communication unit (optical communication unit) for optical communication, which is configured to transmit/receive IDs of vehicles through communication between individual vehicles; and a unit configured to detect information having a corresponding ID by collating the ID received by the individual communication unit with the ID included in the information received by the DSRC unit. Through ID collation, a communication counterpart vehicle of DSRC is detected.