Abstract: A drive for a machine includes a computer configured to control a first electric motor for driving vehicle wheels and a second electric motor for driving a work attachment. The second electric motor is configured to drive at least one hydraulic pump with an adjustable stroke volume. A sensor is configured to detect the stroke volume of the pump. The computer processes the stroke volume to control the second electric motor.

Abstract: A method and system of determining whether a stationary vehicle is a blocking vehicle to improve control of an autonomous vehicle. A perception engine may detect a stationary vehicle in an environment of the autonomous vehicle from sensor data received by the autonomous vehicle. Responsive to this detection, the perception engine may determine feature values of the environment of the vehicle from sensor data (e.g., features of the stationary vehicle, other object(s), the environment itself). The autonomous vehicle may input these feature values into a machine-learning model to determine a probability that the stationary vehicle is a blocking vehicle and use the probability to generate a trajectory to control motion of the autonomous vehicle.

Abstract: A multi-stop route selection system may include a telematics device associated with a vehicle having one or more sensors arranged therein, a mobile device, and a server computer. The server computer may receive driving data of a driver of the vehicle and a vehicle location from the telematics device, determine one or more driving behaviors of the driver based on the driving data, receive data regarding a calendar of the driver from the mobile device, identify a plurality of appointments in the calendar, determine a route comprising multiple destinations for the driver based on the vehicle location, the one or more driving behaviors, and the plurality of appointments, transmit the route to the mobile device, receive a request to add a new destination to the route from the mobile device, generate a modified route comprising the new destination, and transmit the modified route for the driver to the mobile device.

Abstract: Embodiments of the present invention provide systems and methods for combining sensor data to measure vehicle movement. Embodiments may collect vehicle and driving data using sensors of a mobile device of a user, such as a location determination sensor and a movement determination sensor. In some embodiments, the data from the sensors may be combined to more accurately estimate vehicle movement, such as vehicle acceleration.

Abstract: This document describes methods and systems for enabling an autonomous vehicle (AV) to determine a path to a stopping location. The AV will determine a desired stop location (DSL) that is associated with a service request. The AV's motion control system will move the AV along a path to the DSL. While moving along the path, the AV's perception system will detect ambient conditions near the DSL. The ambient conditions will be parameters associated with a stopping rule. The AV will apply the stopping rule to the ambient conditions to determine whether the stopping rule permits the AV to stop at the DSL. If the stopping rule permits the AV to stop at the DSL, the motion control system will move the AV to, and stop at, the DSL. Otherwise, the motion control system will not stop the AV at the DSL.

Abstract: Methods and systems are provided for integratedly managing a vehicle operation state. A vehicle integration management method performed by a server implemented by using a computer may include receiving vehicle operation data related to an operation state of the vehicle from a vehicle terminal mounted or embedded in the vehicle; and providing a service related to the vehicle operation data through a dedicated application on a user terminal used by a user of the vehicle. The providing may provide at least one of an operation report, a parking impact notification, and an accident situation notification based on the vehicle operation data in association with the application.

Abstract: Methods and systems are disclosed for correlating synthetic LiDAR data to a real-world domain for use in training an model for use by autonomous vehicle when operating in an environment. To do this, the system will obtain a data set of synthetic LiDAR data, along with images of a real-world environment. The system will transfer the synthetic LiDAR data to a two-dimensional representation, use the two-dimensional representation and the images to train a model that a vehicle can use to operate in a real-world environment.

Abstract: Methods and systems are provided for integratedly managing a vehicle operation state. A vehicle integration management method performed by a server implemented by using a computer may include receiving vehicle operation data related to an operation state of the vehicle from a vehicle terminal mounted or embedded in the vehicle; and providing a service related to the vehicle operation data through a dedicated application on a user terminal used by a user of the vehicle. The providing may provide at least one of an operation report, a parking impact notification, and an accident situation notification based on the vehicle operation data in association with the application.

Abstract: An apparatus, a system and a method indirectly detect the operational state of a machine among a plurality of operational states and track the movement of a material through a plurality of machines.

Abstract: A system includes a processor configured to receive a user profile responsive to an efficiency determination request for a vehicle model. The processor is also configured to obtain efficiency-affecting data from the user profile. The processor is further configured to compare the efficiency-affecting data to data gathered from drivers of the vehicle model, to determine a correlation between the user profile and similar drivers of the vehicle model. Also, the processor is configured to predict fuel efficiency for the new vehicle model based on efficiency achieved by the similar drivers.

Abstract: An example trailer monitoring system includes a trailer monitoring unit (TMU) that has an image capture arrangement disposed within the TMU, the image capture arrangement to capture first image data, and an accelerometer carried by the TMU, the accelerometer to generate acceleration data of the TMU. The system also has one or more processors configured to access the acceleration data and configured to compare the acceleration data to a reference acceleration data range to determine if the acceleration data is within the reference acceleration range, in response to the acceleration data being outside the reference acceleration data range, the one or more processors are to record an impact event associated with the TMU being impacted, and in response to the acceleration data being outside the reference acceleration data range, the one or more processors are to generate a message associated with the impact event.

Abstract: The present application discloses a method, device and system for automatic oiling of a long-distance transport vehicle. The method provided by the present application includes: obtaining, by a transport planning system at a network side, vehicle status information, transport mission information and highway port information of the vehicle before the long-distance transport vehicle starts from a highway port of departure; generating a transport plan according to the vehicle status information, the transport mission information and the highway port information, wherein the transport plan comprises at least one highway port to be stopped at, cargo quantity to be loaded at each highway port to be stopped at and oil mass to be filled at each highway port to be stopped at; and sending the transport plan to the vehicle.

Abstract: An automated method of controlling a speed of a vehicle includes identifying parameters of a driving instance of the vehicle; identifying a predetermined profile that is applicable to the driving instance based on the identified parameters; identifying a predetermined speed policy applicable to the driving instance based on the identified profile; and implementing the identified speed policy during the driving instance. The method may be repeated during the driving instance, whereby the speed policy that is implemented is automatically updated when one or more changes in the identified parameters cause a different predetermined speed policy to be identified. Parameter may include driver parameters (e.g., driver age and driver experience); vehicle parameters (e.g., vehicle age, mileage, and tire wear) tire maintenance information); behavior parameters (e.g., speed, acceleration, hard braking of the vehicle, following distance, swerving, and cornering); and circumstance parameters (e.g.

Abstract: Systems and methods for controlling an autonomous vehicle are provided. In one example embodiment, a computer-implemented method includes receiving data indicative of an operating mode of the vehicle, wherein the vehicle is configured to operate in a plurality of operating modes. The method includes determining one or more response characteristics of the vehicle based at least in part on the operating mode of the vehicle, each response characteristic indicating how the vehicle responds to a potential collision. The method includes controlling the vehicle based at least in part on the one or more response characteristics.

Abstract: A system for regulating the speed of a vehicle includes defining a first border for a first geographic region. The border has a first speed within the border and a second speed outside of the border. The system includes determining a first velocity of the vehicle including a vehicle speed and direction of the vehicle approaching the border. The difference between the vehicle speed and the second speed is the calculated, as is a distance between the vehicle and the border. If the difference between the vehicle speed and the second speed divided by the distance is greater than a predetermined value, the vehicle is decelerated at a rate so that the vehicle will have a second speed when the vehicle reaches the border.

Abstract: A driving support ECU initializes a target trajectory calculation parameter at a start of LCA; calculates, based on the target trajectory calculation parameter, a target trajectory function representing a target lateral position which is a target position of an own vehicle in a lane width direction in accordance with an elapsed time from the start of LCA; calculates a target control amount based on the target trajectory function; when a steering operation by a driver has been detected, again initializes the target trajectory calculation parameter; and recalculates the target trajectory function based on the target trajectory calculation parameter.

Abstract: An in-vehicle sensing module for monitoring a vehicle is disclosed, which is advantageous for use in the context of a shared vehicle service, such as a car rental service, an autonomous taxi service, or a ride sharing service. The in-vehicle sensing module at least includes a controller, a cellular transceiver, and one or more integrated sensors configured to monitor a status of the vehicle. The in-vehicle sensing module utilizes appropriate algorithms, models, or thresholds to interpret sensor data and enrich the data with metadata and event detection. The in-vehicle sensing module uploads relevant sensor data, event data, or other metadata to a cloud storage backend, which is made accessible by authorized third-parties.

Abstract: The disclosure is directed to, among other things, distributed ledger systems for modular vehicles. The disclosure may involve receiving, at a first ledger associated with a first node, information regarding an interaction between the first node and a second node. The same transaction information may also be received at a second ledger associated with the second node, as well as ledgers associated with any other number of nodes. The first node, second node, and any other number of nodes may be modular vehicle components. Additionally, the first ledger, second ledger, and any other number of ledgers include a set of the same information. The first node, second node, and third node may be nodes on a distributed ledger network.

Abstract: A communication adapter of a gas turbine engine of an aircraft includes a communication interface configured to wirelessly communicate with an offboard system and to communicate with an engine control of the gas turbine engine, a memory system, and processing circuitry. The processing circuitry is configured to receive an engine control dynamic data recording request from the offboard system, confirm an authentication between the communication adapter and the engine control, transfer the engine control dynamic data recording request received at the communication adapter from the offboard system to the engine control based on the authentication, and transmit an update completion confirmation of the engine control from the communication adapter to the offboard system based on a confirmation message from the engine control.

Abstract: Systems and methods are provided for managing air traffic and tolling for a plurality of unmanned aircraft system. Various embodiments include terrestrial and unmanned aircraft system based tracking modules for tracking a plurality of unmanned aircraft systems and reporting flight data to a tolling entity for collection from operators.