Abstract: A system for analyzing wireless telematics data to determine that a vehicle is engaged in an extended period of travel and prompt additional devices within the vehicle regarding the extended period of travel. The system may comprise a telematics server and a plurality of mobile applications to be implemented on a plurality of telematics devices belonging to a plurality of users. The plurality of telematics devices transmit telematics data to the telematics server. The data is analyzed and the telematics server transmits an indication to the telematics devices, causing the mobile applications to execute in a driver application mode or passenger application mode. Messages containing notifications to change drivers or pull over are sent to the telematics devices.

Abstract: The present embodiments relate to a method in a system, a method in a network device, and a network device. The method includes: acquiring, from an entity, a notification of the occurrence of an accident of a vehicle in an area; requesting a RAN node and a CN node of the mobile operator to provide information regarding the vehicle; receiving from the CN node a combined information including information regarding communication with the vehicle and/or information of interest in said area provided to the core network node from vehicles and/or users, and/or devices present in said area where the accident occurred, and available information regarding the vehicle; and analyzing the received combined information.

Abstract: An example operation includes one or more of determining one or more objects in a transport that may become airborne and altering a portion of the transport to minimize the one or more objects from becoming airborne during a collision.

Abstract: Methods and systems are provided for monitoring a health of a vehicle component. In one embodiment, a method is provided, comprising dividing a population of vehicles of a connected vehicle population into a plurality of vehicle classes; for each vehicle class of the plurality of vehicle classes, training a class-specific model of the vehicle class to predict a health status variable of a vehicle component included in the vehicle class based on labelled data from historic databases and calibration data; and for each vehicle class of the plurality of vehicle classes, using a first Federated Learning strategy to request local model data from each vehicle of a plurality of vehicles of the vehicle class; receive the local model data from the plurality of vehicles; update the class-specific model based on the received local model data; and send updated parameters of the class-specific model to vehicles included in the vehicle class.

Abstract: The present disclosure relates to systems and methods for analyzing health of vehicle batteries and vehicle electrical systems. Vehicle batteries, as well as other components of a vehicle electrical system, tend to degrade over time, and eventually fail. The described systems and methods generate an electrical system metric based on electrical data from a plurality of vehicles. Electrical system performance of individual vehicles is compared to the generated electrical system metric, to determine electrical system performance of vehicles relative to other similar vehicles.

Abstract: A vehicle inspection method in a production line of a vehicle includes: performing a part inspection in steps of manufacturing parts of the vehicle, the part inspection in which each of the parts after being manufactured is inspected with an inspection device and which includes one or more inspection items; storing a result of the part inspection in a storage device such that the result is associated with the part; and displaying the result of the part inspection, on a display device used in a completed vehicle inspection for inspecting a completed vehicle serving as the vehicle that is completed, information indicating at least the part of the parts corresponding to a failed item serving as the inspection item which is determined not to be passed in the result of the part inspection stored in the storage device and information indicating the failed item.

Abstract: Various embodiments provide prognostic vehicle diagnosis methodologies for monitoring the relative health of various vehicle components over time, to enable replacement of those vehicle components prior to component failure. Sensors monitoring those vehicle components transmit generated telematics data to a computing entity configured to generate a telematics data signature based on the sensor-generated data, and to compare the telematics data signature against a reference data signature to ascertain the relative health of the vehicle component. If the telematics data signature satisfies a failure threshold identified within the reference signature, the computing entity initiates a replacement process at least in part by generating an alert for a maintenance personnel.

Abstract: An information collection system corrects vehicle state information of each of a plurality of vehicles. Identification information and the vehicle state information is transmitted by a first transmitter, the identification information being information based on which a target vehicle is specified from among the vehicles. Disclosure position information and the identification information are transmitted by a second transmitter, the disclosure position information being set as position information on the target vehicle based on (i) alternative position information indicating a position of the target vehicle in an alternative manner and (ii) disclosure information indicating a disclosure range to disclose the alternative position information.

Abstract: Systems and methods for determining a reparability of a vehicle are provided. In some embodiments, vehicle data is obtained, and a list of variables is generated from the obtained data. A machine learning algorithm may then be trained to generate a reparability metric by: (i) generating correlation metrics between the variables and costs to repair the vehicle, (ii) removing variables with correlation metrics below a threshold, and (iii) training the machine learning algorithm based upon unremoved variables.

Abstract: In order to obtain competitive pricing for vehicle servicing, a pricing service provider is used to obtain pricing data from a plurality of service vendors. In at least some embodiments, one or more of the following types of additional information for each vendor will be provided along with the pricing data, to enable the consumer (the owner or operator of the vehicle) to make an informed selection: a rating of the vendor, a relative distance between the consumer (or known vehicle location) and the vendor, and a time period defining when the vendor will be able to accommodate the service. In at least some embodiments, a pricing service provider hosts a reverse auction for the benefit of the consumer. In at least some embodiment, the pricing service provider hosts a webpage upon which results of the service requests from the plurality of vendors are displayed.

Abstract: A vehicle inspection method in a production line of a vehicle includes: performing a part inspection in steps of manufacturing parts of the vehicle, the part inspection in which each of the parts after being manufactured is inspected with an inspection device and which includes one or more inspection items; storing a result of the part inspection in a storage device such that the result is associated with the part; and displaying the result of the part inspection, on a display device used in a completed vehicle inspection for inspecting a completed vehicle serving as the vehicle that is completed, information indicating at least the part of the parts corresponding to a failed item serving as the inspection item which is determined not to be passed in the result of the part inspection stored in the storage device and information indicating the failed item.

Abstract: A system for a distributed in-vehicle real-time sensor data processing can be adapted to receive a request for sensor data from vehicles. The system may be further adapted to generate an application for collection of the sensor data. The application may have sensor requirements for performing the collection of sensor data. The system may be further adapted to identify a set of vehicles for distribution of the application based on available sensors in each vehicle corresponding to the sensor requirements. The system may be further adapted to transmit the application to the set of vehicles and receive sensor data results from respective instances of the application executing on the set of vehicles. The system may be further adapted to transmit a command to remove the respective instances of the application from the set of vehicles.

Abstract: An analytics reporting system to perform operations that include: aggregating sensor data collected from a plurality of sensor devices within a database, the sensor data comprising a set of values that correspond with a metric; generating a threshold value based on the set of values that correspond with the metric; accessing a portion of the sensor data based on an identifier associated with the portion of the sensor data; determining the portion of the sensor data transgresses the threshold value; and generating a report that comprises a display of the portion of the sensor data based on the determining that the portion of the sensor data transgresses the threshold value.

Abstract: A method of visualizing output data of a traffic planning method for controlling a plurality of vehicles (v1, v2, . . . ), wherein each vehicle occupies one node in a shared set of planning nodes (wp1, wp2, . . . ) and is movable to other nodes along predefined edges between pairs of the nodes, wherein the output data indicates respective planned node occupancies of the vehicles for a sequence of time steps, the method comprising: obtaining a graphical representation of the planning nodes; and in the graphical representation, indicating each vehicle's planned movements between the nodes by linear graphical elements, wherein an appearance parameter of the linear graphical elements has a time variation with respect to the time step, which time variation is common to all vehicles. The appearance parameter may be a line width, line style, color or texture.

Abstract: A battery monitoring network is provided that includes a battery. The battery monitoring network also includes a battery monitoring system integrated within the battery. The battery monitoring system includes a diagnostic system configured to monitor or to store one or more battery parameters of the battery. Additionally, the battery monitoring system includes a transmitter configured to transmit data indicative of the one or more battery parameters of the battery. Furthermore, battery monitoring network includes a cloud-based computing network having a remote server configured to receive the data indicative of the one or more battery parameters of the battery. Moreover, the cloud-based computing network is configured to interface with a plurality of battery monitoring systems, and includes an internet connection.

Abstract: Systems and methods for determining the effectiveness of vehicle safety features are provided. Vehicle build information (VBI) for vehicles manufactured by a plurality of OEMs may be obtained. The VBI may contain OEM-specific terminology for smart safety features associated with each vehicle. The obtained VBI may be analyzed to generate an ontology model mapping each feature to any OEM-specific terminology associated with the feature. The ontology model may be applied to the VBI to generate translated VBI for each vehicle, such that the OEM-specific terminology associated with each feature is replaced with OEM-agnostic terminology for the feature. Vehicle accident record information may be obtained for each vehicle, including, e.g., the number, frequency, severity, etc. of accidents associated with each vehicle.

Abstract: Methods, computing systems, and technology for machine-learned vehicle component health monitoring are presented. An example method may include obtaining operating data describing one or more operational characteristics of a component of a subsystem onboard a vehicle. The example method may include generating, using a component longevity model and based on the operating data, a component longevity value for the component. The example method may include generating, using a vehicle usage model and based on the component longevity value, a prognosis for the component. In the example method, the vehicle usage model may be configured to evaluate the component longevity value based on a usage pattern associated with the vehicle. The example method may include initiating, based on the prognosis, a corrective action to mitigate degradation of the component.

Abstract: A control system is programmed for monitoring the health and charge of batteries used to power a battery electric machine (BEM) or other heavy equipment and determining when maintenance, service, or replacement should be performed for the batteries as a function of data related to travel route segments over which the BEM or other heavy equipment is operated. The control system is programmed to receive historical information mapping the performance and energy consumption of a BEM or other heavy equipment, such as battery state-of-charge, power usage, battery state-of-health, and number of charge cycles for a battery supplying power to the BEM or other heavy equipment operating over a travel route segment, and instruct an operator to replace or perform maintenance on the batteries if the difference between present and historical performance exceeds a threshold level.

Abstract: A trainable transceiver comprises a transceiver circuit, a user interface, and a control circuit in selective communication with the transceiver circuit. The control circuit is further in communication with and configured to process inputs received at the user interface. The transceiver circuit is configured to, in response to a particular input received at the user interface, transmit an activation signal to a vehicle charging station.

Abstract: Provided are methods, systems, devices, apparatuses, and tangible non-transitory computer readable media for navigation and geocoding. The disclosed technology can perform operations including accessing location data and semantic tags. The location data can include information associated with locations including the location of a carrier and the location of a passenger. The semantic tags can include information associated with features of the locations. The location data and the semantic tags that satisfy meeting criteria can be identified. The meeting criteria can be associated with a suitability of a location for the carrier and the passenger. A meeting location for the carrier and the passenger can be determined based on the location data and the semantic tags that satisfy the meeting criteria. Furthermore, indications associated with the meeting location can be generated based on the features of the meeting location.

Abstract: A battery management system in a vehicle includes: monitoring devices arranged in a housing accommodating battery; and a control device arranged in the housing, acquiring battery information from the monitoring devices, and performing a predetermined process. The control device stores, in advance as learning data, data that correlates with an electric field intensity in the housing for frequency channels that are usable to transmit and receive data to and from each of the monitoring devices performing wireless communication. The control device determines a target frequency channel of the frequency channel hopping based on the learning data.

Abstract: A system includes a processor configured to wirelessly receive vehicle usage data. The processor is also configured to aggregate received data over time. The processor is further configured to classify vehicle usage into a predetermined category based on the aggregated received data. Also, the processor is configured to access a set of maintenance recommendations associated with the predetermined category and send a maintenance recommendation based on a correspondence between the aggregated data and a value associated with one of the maintenance recommendations.

Abstract: The invention relates to a method of acquiring information of an accessory connected to a vehicle. The method comprises, in a control unit of the vehicle, acquiring an accessory identifier from the accessory. The method further comprises transmitting the accessory identifier to a remote server comprising accessory information, matching, in the server, the accessory identifier with corresponding accessory information, transmitting the accessory information to the vehicle and receiving the accessory information in the control unit.

Abstract: A supervisory control system is disclosed that provides an operator situational awareness interface use with monitoring a plurality of automated vehicles (AVs). The system is configured to: generate a map of a geographical area of interest; obtain location data and perceived risk data for a plurality of AVs in the geographical area; generate a vehicle icon corresponding to each AV; position the vehicle icon for each AV on the map based on the location data for a corresponding AV; apply a color coding to each vehicle icon based on a perceived risk level for a corresponding AV; and signal a display device to display an AV fleet map graphic that includes the color coded vehicle icons positioned on the map. The controller may be further configured to: generate an AV servicing queue graphic that displays vehicle icons in an order based on a determined servicing priority.

Abstract: A computing system, including a processor configured to, at development time, receive a machine learning model topology including a plurality of layers. The processor may be further configured to generate an internal representation graph of the machine learning model topology. The internal representation graph may include a plurality of internal representation layers. By performing one or more modifications to the internal representation graph, the processor may be further configured to generate an inferencer graph including a plurality of inferencer layer blocks. Each inferencer layer block may indicate an input buffer size, a logic function, and an output buffer size. At deployment time, the processor may be further configured to transmit, to a plurality of processing devices, instructions to implement the machine learning model topology with the respective input buffer sizes, logic functions, and output buffer sizes selected for the plurality of inferencer layer blocks of the inferencer graph.

Abstract: A worksite management system may include a worksite controller including one or more worksite controller processors configured to receive a signal indicative of a task to be performed by a machine at a worksite, identify a machine for performing the task, and generate a signal indicative of the machine. The worksite management system may also include a mobile device including one or more mobile device processors configured to receive the signal indicative of the machine, display an image representative of the machine, and display a prompt for a person at the worksite to validate availability of the machine to perform the task.

Abstract: In a control device for a vehicle, the vehicle is configured to charge an electric power storage device with an electric power supplied from a charger. The control device includes an input and output circuit and a control circuit. The input and output circuit is configured to input predetermined signal and output the predetermined signal. The control circuit is configured to prepare for charging of the electric power storage device by controlling transmission and reception of signals through the input and output circuit according to a predefined communication sequence. The control circuit is configured to proceed with the predefined communication sequence by transmitting the second signal to the charger even when the vehicle does not receive the first signal at the predetermined timing.

Abstract: Methods and systems are provided for increasing an accuracy of anomaly detection in assets such as vehicle components. In one example, a method provides for continuous health monitoring of connected physical assets, comprising adapting thresholds for anomaly detection and root cause analysis algorithms for the connected assets based on an aggregation of new connected data using machine learning; updating and ranking advanced statistical and machine learning models based on their performance using connected data until confirming a best performing model; and deploying the best performing model to monitor the connected physical assets.

Abstract: A device and a method for planning of maintenance work on a machine. Based on sensor data S, input data E are generated. The input data E are compared with model sensor data of different model data pattern and are checked regarding conformity. Each model data pattern is assigned a maintenance model in the model database. If a conformity of input data E with model sensor data M of a model data pattern has been determined, the assigned maintenance model can be selected for a maintenance of the machine. The maintenance model comprises at least one maintenance step and the resource required for it to be carried out. Subsequently, the availability of the required resource is checked and the resource is requested, if available. By such a device or method, a predicted maintenance can be performed based on empirical knowledge contained in the maintenance models of model database.

Abstract: A vehicle monitoring apparatus includes: a first communicator that receives specifying information for specifying a target vehicle from a server; and an acquirer that acquires driving information from the target vehicle, the driving information being information regarding driving of the target vehicle specified by the specifying information received by the first communicator. The first communicator transmits the driving information acquired by the acquirer to the server. For example, the acquirer may acquire the driving information obtained from the target vehicle through communication.

Abstract: A method for instructing users of car-sharing services to operate a shared vehicle includes identifying a user of a selected vehicle, determining a customary vehicle of the user based on the identification, determining differences between the selected vehicle and the customary vehicle, and informing the user of the determined differences.

Abstract: An information collection system corrects vehicle state information of each of a plurality of vehicles. Identification information and the vehicle state information is transmitted by a first transmitter, the identification information being information based on which a target vehicle is specified from among the vehicles. Disclosure position information and the identification information are transmitted by a second transmitter, the disclosure position information being set as position information on the target vehicle based on (i) alternative position information indicating a position of the target vehicle in an alternative manner and (ii) disclosure information indicating a disclosure range to disclose the alternative position information.

Abstract: Apparatus, device, methods and system relating to a vehicular telemetry environment for the real time generation and transformation of raw telematics big data into analytical telematics big data that includes raw telematics big data and supplemental data.

Abstract: This on-vehicle data management device includes: a data collection section configured to collect data that is obtained by a first apparatus of a vehicle and that is recorded in a record region provided in the first apparatus; an information obtaining section configured to obtain information related to travel of the vehicle from a second apparatus of the vehicle, the second apparatus being different from the first apparatus; and a storage processing section configured to store target data collected by the data collection section in association with the information related to travel of the vehicle obtained by the information obtaining section.

Abstract: In an abnormal noise evaluation system, running noise of a vehicle is acquired, and the running noise is analyzed to generate analysis data. A rotational order component of the running noise of the vehicle is then extracted from the analysis data, and features for each rotational order of the running noise of the vehicle is generated based on the extracted rotational order component. Subsequently, a learning model is generated using as training data a combination of the features for each rotational order generated for a learning object that is of the same type as an object to be evaluated and an evaluation result given in advance to the learning object. Whether there is abnormal noise from the object to be evaluated is evaluated by applying the features for each rotational order generated for the object to be evaluated to the learning model, and an evaluation result is output.

Abstract: Method and system for determining a status of a mobile device of a user are disclosed. For example, the method includes receiving first sensor data at a first time from an application installed on a mobile device of a user, determining a first location of the mobile device, immediately subsequent to receiving the first sensor data at the first time, receiving second sensor data at a second time from the application, the second time following the first time by a time interval, determining a second location of the mobile device, determining a distance between the first location and the second location, determining whether the distance corresponding to the time interval exceeds a predetermined threshold, and determining whether a trip log indicative of at least one trip during the time interval is received from the application.

Abstract: A system and method for contextually monitoring vehicle states. The method includes enriching a plurality of messages based on at least one missing property value and a plurality of predictive properties in the plurality of messages, wherein at least one message of the plurality of messages is generated by a vehicle monitoring system, wherein each message of the plurality of messages is ingested at a vehicle state monitor, wherein each of the predictive properties is a property indicated in one of the plurality of messages of a predetermined type of property; and generating a contextual vehicle state for a vehicle based on the enriched plurality of messages, wherein the contextual vehicle state is a snapshot of a plurality of vehicle state properties at a given time.

Abstract: Techniques for providing a user interface for remote vehicle monitoring and/or control include presenting a digital representation of an environment and a vehicle as it traverses the environment on a first portion of a display and presenting on a second portion of the display a communication interface that is configured to provide communication with multiple people. The communication interface may enable communications between a remote operator and any number of occupants of the vehicle, other operators (e.g., other remote operators or in-vehicle operators), and/or people in an environment around the vehicle. The user interface may additionally include controls to adjust components of the vehicle, and the controls may be presented on a third portion of the display. Furthermore, the user interface may include a vehicle status interface that provides information associated with a current state of the vehicle.

Abstract: Systems and methods for determining the effectiveness of vehicle safety features are provided. Vehicle build information (VBI) for vehicles manufactured by a plurality of OEMs may be obtained. The VBI may contain OEM-specific terminology for smart safety features associated with each vehicle. The obtained VBI may be analyzed to generate an ontology model mapping each feature to any OEM-specific terminology associated with the feature. The ontology model may be applied to the VBI to generate translated VBI for each vehicle, such that the OEM-specific terminology associated with each feature is replaced with OEM-agnostic terminology for the feature. Vehicle accident record information may be obtained for each vehicle, including, e.g., the number, frequency, severity, etc. of accidents associated with each vehicle.

Abstract: An example operation includes one or more of determining an issue related to a stationary transport, determining a cause of the issue, determining moving transports that do not have the issue, but exhibit characteristics similar to the cause, and based on the characteristics, notifying the moving transports of a potential of the issue.

Abstract: A train control method is provided for a vehicle on-board controller (VOBC) configured on one end of a train. The method includes: performing a train awakening process; acquiring a running plan sent by an automatic train supervision (ATS) system after the train is successfully awakened; setting, according to a direction indicated by the running plan, a running direction of the train to be downward or upward; when the running direction is set to downward, using, as a head for train positioning, one end of the train not configured with the VOBC, to acquire positioning information of the train; when the running direction is set to upward, using, as the head for train positioning, one end of the train configured with the VOBC, to acquire the positioning information of the train; and controlling, according to the positioning information of the train, the train to pull out of a parking garage.

Abstract: An object of the present invention is to reduce an error between an actual machine and a simulation by removing the influence of overlearning of an adjustment by a mathematically-described function, and to optimize automatic operation control of the machine. An automatic operation control system for controlling an automatic operation of a machine sets a first model showing a relation between a control signal string input to the machine on the basis of a mathematically-described function and data output from the machine controlled in accordance with the control signal string. In a learning process including learning the automatic operation control of the machine, the system executes learning using the first model until a first condition is satisfied.

Abstract: A method for asset maintenance includes determining a location of an asset, receiving meteorological data corresponding to the location, determining forecasted meteorological conditions for the asset from the meteorological data, determining a forecasted probability of degradation or failure of the asset based, at least in part, on the forecasted meteorological conditions, and dispatching asset maintenance services for the asset responsive to determining that the forecasted probability of degradation or failure of the asset is above a selected threshold. The method may also include collecting sensor data corresponding to the asset, and determining the forecasted probability of degradation or failure of the asset based, at least in part, on the forecasted meteorological conditions and the sensor data. A corresponding apparatus, computer program product, and computer system are also disclosed herein.

Abstract: Systems and methods are provided for automating the process of determining non-reusable parts associated with replacement or repair of a primary part of a vehicle involved in a collision event. The primary parts to be repaired may be indicated in repair estimate record. Notably, replacement of some primary parts may require replacement of certain non-reusable parts (NRPs) that were not damaged during the collision event and are not identified as such. The method determines which NRPs are required to be replaced when repairing the primary damaged part by using repair documents specifying repair instructions for repairing the primary part. Further, the repair estimate record is updated to include the information related to the primary pars and their associated NRPs.

Abstract: According to various embodiments, a fleet management system is provided for capturing, storing, and analyzing telematics data to improve fleet management operations. The fleet management system may be used, for example, by a shipping entity (e.g., a common carrier) to capture telematics data from a plurality of vehicle sensors located on various delivery vehicles and to analyze the captured telematics data. In particular, various embodiments of the fleet management system are configured to analyze engine idle data in relation to other telematics data in order to identify inefficiencies, safety hazards, and theft hazards in a driver's delivery process. The fleet management system may also be configured to assess various aspects of vehicle performance, such as vehicle travel delays and vehicle speeds.

Abstract: A method, comprising: receiving position data from a mobile device; incrementing a counter variable, said counter variable associated with a predefined geographic area that includes a position of the position data, and initializing a time variable, said time variable set to a predefined value and decremented continuously; and decrementing said counter variable in response to expiration of said time variable.

Abstract: A method and system for processing requests for vehicular data, including receiving a vehicle request for a vehicle parameter from a client system (e.g., third party application); verifying client access to the vehicle parameter; determining one or more parameter values for the requested vehicle parameter; and transmitting the one or more parameter values to the client system.

Abstract: A vehicle failure-factor specifying apparatus includes (a) a peculiarity-presence determining portion configured to determine, based on a pre-failure driving state in a stage prior to occurrence of a certain failure in a vehicle, whether a peculiarity was present or absent in the pre-failure driving state, and (b) a failure-causing-driving state specifying portion configured, when the peculiarity was present in the pre-failure driving state, to determine whether the peculiarity present in the pre-failure driving state of the vehicle is substantially identical with a peculiarity in the pre-failure driving state of other vehicles.

Abstract: A system for replacing an original hose assembly of a work machine with a replacement hose assembly includes at least a computing device, a database, and a server. The server is associated with the database and includes a processor configured via computer-executable instructions to perform a method of identifying the replacement hose assembly. The method includes prompting a user to select hose attributes associated with a hose of the original hose assembly. Based on the selected hose attributes, a replacement hose may be identified. The method further includes prompting the user to select coupling attributes associated with a coupling of the original hose assembly. Based on compatibility with the identified replacement hose and the selected coupling attributes, a replacement coupling may be identified. The method further includes generating a bill of materials for the replacement hose assembly and displaying the bill of materials.

Abstract: The vehicle electronic control apparatus includes two or more FPGAs that each receive information from the sensor, a nonvolatile memory that holds a bit stream for determining a configuration for the FPGA, an MCU that incorporates two or more nonvolatile memories, in each of which a program code for calculating the control command is installed, and an error control module that outputs an error signal to the outside at a time when an abnormality occurs in at least one of the FPGA and the nonvolatile memory incorporated in the MCU; the nonvolatile memory that holds the bit stream and the nonvolatile memory incorporated in the MCU can be accessed from the outside.