Abstract: A smart communications hub can enable management of driverless and/or autonomous vehicles. Separating current wireless data from driverless vehicle sensor data can allow for quicker resolutions involving driverless vehicles. The smart communications hub can communicate to other groups such as driverless vehicle providers, service providers, vehicle management, law enforcement, etc. The smart communications hub can also process request from both mobile applications and micro-service applications.

Abstract: A data collecting system including a component assembled in an electric vehicle, a data collector connected to the component through a bus of the electric vehicle, and a debug server connected to the data collector is disclosed. The component collects different data from the electric vehicle and performs different sending procedures respectively under different situations including: a regular sending-procedure sends regular data to the bus based on a regular frequency; a high-speed sending-procedure starts collecting high-speed data and sending the same to the bus based on a high-speed frequency after a condition is satisfied; and a high-resolution sending-procedure sends high-resolution data to the bus after an error occurs, wherein the high-resolution data is collected within a period of time before and after the error occurs. The data collector collects these data from the bus. The debug server analyzes the data collected by the data collector.

Abstract: The present invention provides specific systems, methods and algorithms based on artificial intelligence expert system technology for determination of preferred routes of travel for electric vehicles (EVs). The systems, methods and algorithms provide such route guidance for battery-operated EVs in-route to a desired destination, but lacking sufficient battery energy to reach the destination from the current location of the EV. The systems and methods of the present invention disclose use of one or more specifically programmed computer machines with artificial intelligence expert system battery energy management and navigation route control. Such specifically programmed computer machines may be located in the EV and/or cloud-based or remote computer/data processing systems for the determination of preferred routes of travel, including intermediate stops at designated battery charging or replenishing stations.

Abstract: A method for providing driving assistance by detecting and warning against areas on one or other side of the road which are obscured by vehicles in other lanes is based on a HD map and includes acquiring location and driving speed of a vehicle which is carrying an apparatus applying the method. The system of the method includes at least one sensor, and environmental information as to surroundings is acquired with location. The speeds of other vehicles relative to the driving speed of the vehicle are calculated, and an instruction to the driver is generated the speed of the vehicle is less than a first predefined value but the speed of the vehicle relative to the driving speeds of the other vehicles is larger than a second predefined value. The apparatus applying the method is also disclosed.

Abstract: Estimating electrical parameters of a track circuit including a transmitter, a receiver, and a track section between the transmitter and receiver. The transmitter outputs, over the track section towards the receiver, a signal including a data packet part, and the signal received by the receiver is decoded to determine the data packet received. Simulated signals are generated, via a predetermined software model including parameters of the track circuit, by varying an actual value input for the model parameters, each signal generated corresponding to actual values input for the parameters. Each simulated signal is compared with the signal received at a receiver until finding a part of a simulated signal that matches a corresponding part of the signal received at a receiver. The actual parameter values corresponding to the simulated signal that match the signal received at the receiver are estimated as the actual parameters of the track circuit.

Abstract: Methods and systems for controlling navigation of a vehicle are disclosed. The system will first detect a URU within a threshold distance of a drivable area that a vehicle is traversing or will traverse. The system will then receive perception information relating to the URU, and use a plurality of features associated with each of a plurality of entry points on a drivable area boundary that the URU can use to enter the drivable area to determine a likelihood that the URU will enter the drivable area from that entry point. The system will then generate a trajectory of the URU using the plurality of entry points and the corresponding likelihoods, and control navigation of the vehicle while traversing the drivable area to avoid collision with the URU.

Abstract: A method for generating at least one school zone indicator, the method may include receiving by a vehicle computerized system, school zone indicators, wherein the school zone indicators are indicative of school zone elements; obtaining sensed information regarding an environment of the vehicle; processing the sensed information, wherein the processing comprises searching for one or more school zone indicators of the school zone indicators; wherein the school zone element is selected out of (i) a school zone object and (ii) a school zone situation; autonomously determining, when finding at least one of the one or more school zone identifiers, that the vehicle is driving towards a school zone or is within the school zone; and generating an alert when determining that the vehicle is driving towards the school zone or is within the school zone.

Abstract: A system includes an array of photodiode sensors positioned on an autonomous vehicle. Each photodiode sensor in the array of photodiode sensors is oriented in a different direction and configured to generate electrical current signals in response to detecting a flashing light in a surrounding environment of the autonomous vehicle. The system also includes a processor coupled to the array of photodiode sensors. The processor is configured to determine a location of a source of the flashing light relative to the autonomous vehicle based on electrical current signals from at least one photodiode sensor in the array of photodiode sensors. The processor is also configured to generate a command to maneuver the autonomous vehicle based on the location of the source relative to the autonomous vehicle.

Abstract: Recovery of a flying vehicle that has fallen to the ground is facilitated. A positioning unit measures a position of the flying vehicle during flight. A specification unit specifies a feature of a region on the ground corresponding to the measured position. A determination unit determines a sending interval of position information indicating the position of the flying vehicle, according to the specified feature. A sending unit sends the position information at the determined sending interval.

Abstract: Example systems and methods are disclosed for determining vehicle pose data for an autonomous vehicle. The vehicle computer system may receive pose data from multiple pose measurement systems of the autonomous vehicle. Each pose measurement system may include one or more corresponding sensors of the autonomous vehicle. The vehicle computer system may determine a pose data quality for the received pose data for each pose measurement system. The vehicle computer system may set the vehicle pose data to the pose data of the pose measurement system with the highest pose data quality. The vehicle computer system may control the autonomous vehicle based on the vehicle pose data.

Abstract: A navigation system includes an IMU, a navigation estimator configured to estimate a current navigation solution based on (i) a previous navigation solution, and (ii) a specific force vector and an angular rate vector measured by the IMU, an RI sensor, an RI data preprocessor configured to perform an a priori transformation of RI data acquired by the RI sensor using the current navigation solution to obtain transformed RI data, an RI map database configured to retrieve a valid keyframe map based on the transformed RI data, and an RI filter manager (RFM) configured to construct a map registration cost gradient (MRCG) measurement based on (i) the transformed RI data, and (ii) the known position and the known orientation of the valid keyframe map. The navigation estimator is further configured to determine an absolute navigation solution based on at least (i) the current navigation solution, and (ii) the MRCG measurement.

Abstract: A system provides feedback to a user to guide the user to point a part of the body at a target of interest. An angle sensor senses the angle in which the part of the user's body is pointing, such as the head or the hand. The system computes the angle to a target and compares to the angle in which the part of the user's body is pointing and the feedback indicates to the user how to point more closely to the direction of the target. Additional sensors allow the system to update the angle to the target as the position of the user changes. A walking sensor is disclosed to accurately measure the position of the user.

Abstract: Based on a set of planned control parameters defining a planned path for a vehicle, a set of reference control parameters corresponding to the set of planned path control parameters are identified. Optimized controller inputs associated with the identified set of reference control parameters, the set of planned control parameters, and operation noise data are input to a vehicle dynamics model that outputs a vehicle state model. Based on the vehicle state model, an actual path for the vehicle and an operating range for the actual path are determined. The planned path is determined to be one of verified or unverified based on the operating range.

Abstract: An example operation includes one or more of detecting, by a server, a target transport operating in an unsafe manner, locating, the by the server, at least one autonomous transport in front of the target transport, and maneuvering the at least one autonomous transport to affect the target transport.

Abstract: Systems and methods that facilitate identifying and controlling the systems and subsystems in a vehicle to enable autonomous operation of the vehicle are disclosed. An autonomous vehicle interface (AVI) (the “AVI control system”) can interface with and control the system of the vehicle, thereby enabling control of the vehicle as a whole. Electronic control units may be associated with each of the systems and subsystems in the vehicle, and the AVI may interface with and control these electronic control units over a shared data bus. In order to control particular electronic control units, the systems and methods provide for sampling data packets transmitted by the electronic control units on the shared data bus, measuring the impedance of the shared data bus when data packets are being transmitted, and identifying particular electronic control units based on the measured impedance.

Abstract: Systems and methods for determining whether a vehicle is driving in an unsafe or unsatisfactory manner are disclosed. In some implementations, a system may determine one or more driving scores for a vehicle based on observations of a driving behavior of the vehicle during a time period. The system may generate an indication of unsatisfactory driving based on at least one of the one or more driving scores exceeding a threshold value. The system may provide the indication of unsatisfactory driving to one or more entities. In some aspects, the system may identify one or more dangerous driving attributes exhibited by the vehicle during the time period based on the observations received from the one or more devices. The system may also generate the indication of unsatisfactory driving based at least in part on the identified dangerous driving attributes.

Abstract: Detection of a launch event of an autonomous vehicle may consider input from a variety of sensors, including acceleration sensors and touch sensors In some aspects, a method includes receiving a first input from a touch sensor, receiving a second input from an accelerometer, determining whether a launch of the autonomous vehicle is detected based on the first input and the second input, and controlling the autonomous vehicle in response to the determining. In some aspects, when a launch is detected, a motor of the autonomous vehicle may be energized. By detecting a launch event in this manner, improved safety and reliability may be realized. A reduced occurrence of false positive launch events may reduce a risk that the motor of the autonomous vehicle is energized when the vehicle has not actually been launched.

Abstract: A communication system that determines a context and an intent of a specific remote vehicle located in a surrounding environment of a host vehicle includes one or more controllers for receiving sensed perception data including sensed perception data. The one or more controllers execute instructions to determine a plurality of vehicle parameters related to the specific remote vehicle. The the one or more controllers execute instructions to associate the specific remote vehicle with a specific lane of travel of a roadway based on map data. The one or more controllers determines possible maneuvers, possible egress lanes, and a speed limit for the specific remote vehicle for the specific lane of travel based on the map data, and determines the context and the intent of the specific remote vehicle based on the plurality of vehicle parameters, the possible maneuvers, the possible egress lanes for the specific remote vehicle, and the speed limit related to the specific remote vehicle.

Abstract: Systems and methods for navigating an aerial vehicle are provided. One example aspect of the present disclosure is directed to a method for navigating an aircraft. The method includes receiving, by one or more processors, one or more first geographic coordinates via an interface configured to receive geographic coordinates from a satellite transmission. The method includes receiving, by the one or more processors, one or more second geographic coordinates via an interface configured to receive geographic coordinates from a ground transmission. The method includes determining, by the one or more processors, that the one or more first geographic coordinates and the one or more second geographic coordinates are inconsistent. The method includes updating, by the one or more processors, a flight plan using the one or more second geographic coordinates when the one or more first geographic coordinates are inconsistent with the one or more second geographic coordinates.

Abstract: A vehicle system includes an electronic control unit. The electronic control unit is configured to execute a first program, a second program, and a third program. The first program is configured to recognize an object present around a vehicle, the second program is configured to store information related to the recognized object as time-series map data, and the third program is configured to predict a future position of the object based on the stored time-series map data. The first program and the third program are configured to be (i) first, individually optimized based on first training data corresponding to output of the first program and second training data corresponding to output of the third program, and (ii) then, collectively optimized based on the second training data corresponding to the output of the third program.