Abstract: A driving analysis server may be configured to receive vehicle operation data from vehicle sensors, and may use the data to identify a potentially high-risk or unsafe driving event by the vehicle. The driving analysis server also may receive corresponding image data, video, or object proximity data from the vehicle or one or more other data sources, and may use the image, video, or proximity data to analyze the potentially high-risk or unsafe driving event. A driver score for the vehicle or driver may be calculated or adjusted based on the analysis of the data and the determination of one or more causes of the driving event.

Abstract: Method for controlling a hydraulic system for a working machine, the system including a first electric machine connected to a first hydraulic machine the first hydraulic machine including an input side and an output side a second electric machine connected to a second hydraulic machine the second hydraulic machine including a high-pressure side and a low-pressure side the high-pressure side connected to the input side; a hydraulic consumer coupled to the output side via a supply line and configured to be powered by the first hydraulic machine; a first return line hydraulically coupling the hydraulic consumer to the input side and to the high-pressure side; wherein the method includes detecting a return flow from the hydraulic consumer through the first return line; and controlling the second hydraulic machine to maintain a pressure in the first return line at a pressure level higher than a predetermined minimum pressure level.

Abstract: The present disclosure relates to a method of selecting an accident image by using speed profile analysis, which can sufficiently secure an available capacity of a storage medium, can reduce the amount of transmission data and a fee therefor, and can prevent a loss of unnecessary management expenses, by selecting an actual accident image by using speed profile analysis before and after the occurrence of an impact event and deleting, from the storage medium, an image having a grade determined to have a low accident possibility or changing a state of the image into an overwritable state or taking measures for preventing the transmission of the image to a cloud server.

Abstract: A tire noise testing method, a vehicle and a control device that are efficient in an actual vehicle noise test. The method of the invention is conducted while a vehicle is driven automatically. The method includes a step of operating a control unit when the vehicle reaches a predetermined position or reaches a predetermined speed, for putting the vehicle into coast-traveling with a prime mover of the vehicle in a non-driving state. The method further includes a step of operating a measuring unit for measuring the tire noise of the vehicle during the coast-traveling of the vehicle.

Abstract: Provided is a process that includes: obtaining, using one or more surface tension sensors, one or more surface tension measurements of a surface, determining a reaction force for an aircraft using the one or more surface tension measurements and a weight of the aircraft. The process includes causing one or more engines included in the aircraft to generate thrust based on the reaction force.

Abstract: A drive recorder to be mounted on a vehicle includes an acquisition unit, a recording unit, a communication unit, and a control unit. The acquisition unit acquires data representing driving condition. The recording unit records the acquired data. The communication unit transmits the acquired data to the outside. The control unit controls the quality of the data to be transmitted based on the information received from the outside.

Abstract: Disclosed are methods and systems for predicting time varying loudness in a geographic region. Training data, including noise information, weather information, and traffic information is collected from a plurality of sensors located in a plurality of geographic regions. The information is collected during multiple time periods. The noise information includes time varying loudness. Static features of the geographic regions are also defined and included in the training data. The static and time varying dynamic features train a model. The model is used predict time varying loudness within a different region and at a time later than times the training data is collected. The predicted loudness levels are utilized, in some aspects, to determine a route for an aircraft.

Abstract: A method for controlling a vehicle includes identifying a user identity associated with a user riding in the vehicle, determining a destination associated with the user identity, creating a detection zone proximate to the vehicle when the vehicle is localized in a first drop-off location associated with the destination, causing a sensory system to identify a hazard within the detection zone and generate a localization of the hazard, determining that a first probability of realizing a risk associated with the hazard is less than a first probability threshold, and generating a vehicle door actuation that permits the user to exit the vehicle based on the first probability of realizing the risk.

Abstract: A vehicle state monitoring device includes a storage device configured to store information relating to a vehicle traveling under power from an engine; a determining device configured to determine a state of the vehicle using the information stored in the storage device; and a storage control device. The storage control device is configured to, each time the vehicle travels a predetermined distance, store a frequency relation as the information in the storage device. The frequency relation is a relation between revolutions of the engine, a fuel-related parameter that is a load factor or a fuel injection rate of the engine, and a running frequency of the engine at the revolutions and the fuel-related parameter while the vehicle travels the predetermined distance.

Abstract: A vehicle includes a traction battery and a cell monitor associated with battery cell strings each having associated connected battery cells. Each monitor is configured to generate a compressed encoded representation of the traction battery cell voltage measurements using artificial intelligence, such as a neural network. A battery controller in communication with each cell monitor receives the compressed encoded representation and generates reconstructed battery cell voltage measurements and controls the traction battery in response to the reconstructed traction battery cell voltage measurements. An unencoded battery cell voltage measurement may be communicated with the compressed encoded representation of the battery cell voltage measurements and used to validate the reconstructed measurements.

Abstract: Techniques for monitoring and predicting vehicle health are disclosed. In some examples, sensor data (e.g., audio data) may be used to create a sensor signature associated with a vehicle component. The sensor signature may be compared with one or more second sensor signatures associated with the vehicle component over the life of the vehicle component to determine changes in an operating status associated with the vehicle component. In some examples, a machine learned model may be trained to identify a vehicle component and/or and operating status of a vehicle component based on sensor data that is inputted into the machine learned model. In this way, sensor data may be input into the machine learned model and the machine learned model may output a corresponding vehicle component and/or operating status associated with the component.

Abstract: A driving assist apparatus executes an autonomous braking control when a predetermined autonomous stop condition becomes satisfied, executes a stopped state keeping control to keep the own vehicle stopped after stopping the own vehicle by the autonomous braking control, and terminates executing the stopped state keeping control when a predetermined stopped state keeping termination condition becomes satisfied while executing the stopped state keeping control. The driving assist apparatus executes a driving force limitation control to limit a driving force generated to move the own vehicle to a value smaller than the driving force which depends on an amount of operating the acceleration pedal when determining that the predetermined stopped state keeping termination condition is satisfied, and a mistaken pressing operation occurs. The mistaken pressing operation is an operation performed by a driver to mistakenly press an acceleration pedal with an intention to press a brake pedal.

Abstract: A control system is provided that may include a controller for a vehicle system. The controller may include one or more processors configured to obtain at least one first operating parameter related to an operating system of the vehicle system, and determine an operating condition of the operating system based at least in part on the first operating parameter. The one or more processors may also be configured to communicate with an off-board sensor to obtain at least one auxiliary operating parameter related to the operating condition, and verify the operating condition based at least in part on the auxiliary operating parameter.

Abstract: A vehicle includes a battery pack including a secondary battery, a battery sensor that detects a state of the secondary battery, and a first control device, a second control device provided separately from the battery pack, and a converter. The first control device is configured to use a detection value of the battery sensor to obtain a current upper limit value indicating an upper limit value of an input current of the secondary battery. The second control device is configured to use a power upper limit value indicating an upper limit value of an input power of the secondary battery to control the input power of the secondary battery.

Abstract: In an automated vehicle (AV) system, interdependencies between components of the AV are determined, an operational domain state of one or more of the components can be determined based on the determined interdependencies, and an output signal representing the operational domain state of the one or more components can be generated. A user interface can present a notification based on the output signal to notify the driver and/or other occupants of the AV of the operational domain state of one or more of the components.

Abstract: This disclosure relates to improved techniques for personalizing vehicle routes and operator sessions using pre-trained machine learning language models. In certain embodiments, a language model is trained on operator interaction data to learn operator route preferences for vehicle operators. These learned operator route preferences can be leveraged to optimize and personalize vehicle routes and operator sessions in various ways. Other embodiments are disclosed herein as well.

Abstract: A deterioration evaluation apparatus for a secondary battery, which evaluates a degree of deterioration of the secondary battery of a hybrid vehicle including an engine that outputs a driving power, a motor that outputs a driving power, and the secondary battery configured to exchange an electric power with the motor, includes one or more processors configured to evaluate the degree of deterioration of the secondary battery based on a first relationship. The first relationship is set by using an accelerator operation amount and an operation point. The operation point includes a rotation speed of the engine and a load factor of the engine. The first relationship is a relationship between the operation point and a load on the secondary battery when the engine is operated at the operation point.

Abstract: A system and method are disclosed for monitoring rides in a vehicle in which a driver of the vehicle picks up a rider at a pickup location and drives the rider to a drop-off destination. The system includes at least one sensor arranged in the vehicle and configured to capture sensor data during the rides, a transceiver configured to communicate with a personal electronic device of a driver of the vehicle, a non-volatile memory configured to store data; and a processor. The system captures sensor data during a ride, determines an activity index indicating an activity level within the vehicle during the ride, and stores the sensor data captured during the ride with the activity index as metadata. In response to an upload request, the system uploads sensor data depending on the activity level.

Abstract: The present disclosure relates generally to aggregation of data associated with events related to automotive vehicles. Automotive vehicles may include a variety of sensing devices used in local sensing operations. However, these sensing devices may not be leveraged beyond the local sensing operations. When automotive vehicles are operated, sometimes events occur. As discussed herein, an event-based data aggregation service may aggregate sensing data from one or more sensing devices, such as sensing devices of the automotive vehicles, in response to receiving an event notification associated with one or more of the events and may use the sensing data when responding to the event notification.

Abstract: A system and method for providing charging options based on electric vehicle operator daily activities that include analyzing data associated with daily activities of an operator of an electric vehicle and determining at least one travel routine and at least one prospective travel plan that is completed by the operator of the electric vehicle based on the daily activities. The system and method also include determining a current geo-location of the electric vehicle. The system and method further include presenting an electric vehicle charging planner user interface that presents at least one prospective travel path to the at least one predicted point of interest.