The present invention provides a robust and effective solution to an entity or an organization by allowing to visualize the flow of automotive data signals from a source system to a sink system with different metric signals at each step and creating a mechanism for creating automotive signal quality marker (ASQM) for high quality automotive data signals by determining high value data parameters, inter-parameter correlation, data quality variation with trip duration, and frequency of data collection/distribution across datasets. The quality criterion thus developed is applied to data generated from a plurality of data sources. The ASQM may be calculated by converting the developed automotive data signals quality criterion into a numeric value on a specified scale. It can be used by all stakeholders in the value chain for consistent measurement of automotive data signals quality.

A system and a method for diagnosing a problem with a motor vehicle using sound. Ambient noise information for the motor vehicle is determined. Current sound information is received, and whether there is a variation in sound between the current sound information and the ambient noise information is determined. The ambient noise information is subtracted from the current sound information if the variation has been identified, to identify a sound anomaly. A sound anomaly signal is extracted and compared with predetermined anomaly signal information stored in a database. The predetermined anomaly signal information is associated with diagnostic information.

A technique is described herein for automatically logging journeys taken by a user, and then automatically classifying the purposes of the journeys. In one implementation, the technique obtains journey data from one or more movement-sensing devices as a user travels from a starting location to an ending location in a vehicle. The technique generates a set of features based on the journey data, and then uses a machine-trainable model (such as a neural network) to make its classification based on the features. The machine-trainable model accepts at least one feature that is based on statistical information regarding at least one aspect of prior journeys that the user has taken. Overall, the technique provides a resource-efficient solution that rapidly provides personalized results to individual respective users. In some implementations, the technique performs its personalization without sharing journey data with a remote server.

A one-touch control system for operating the controls of a towed vehicle using a towing vehicle. The system includes an electronic control unit integrated into the towed vehicle and configured to receive a selection signal from the towing vehicle and simultaneously control a number of different components based on the selection signal. The components including a switch configured to turn on and off the towed vehicle, a sensor configured to detect whether a passenger is present in the towed vehicle, and an odometer configured to be deactivated when the switch indicates that the towed vehicle is off and the sensor indicates that there are no passengers in the towed vehicle.

Systems and methods for providing continuous safe-driver training safely are provided. A safe-driving challenge may be presented to an operator of a vehicle. Data captured by sensors associated with the vehicle may be analyzed to determine whether the operator of the vehicle has completed the safe-driving challenge. Based on a determination that the operator of the vehicle has completed the safe-driving challenge, a notification may be provided to the operator (e.g., indicating to the operator that he or she has successfully completed the challenge). A processor may randomly select whether a reward is to be provided to the operator of the vehicle based on the determination that the operator of the vehicle has completed the safe-driving challenge. Moreover, if a reward is to be provided to the operator of the vehicle, a processor may randomly select a type of reward to be provided to the operator of the vehicle.

A recording apparatus includes: a captured data acquisition unit configured to acquire captured data captured by a camera that captures an image of an outside of a vehicle; an event detection unit configured to detect an event with respect to the vehicle; an attachment/detachment detection unit configured to detect an attachment/detachment state of the recording apparatus with respect to the vehicle; and a recording controller configured to store, when the event detection unit has detected the event, captured data for a predetermined period of time due to the detected event as first event recording data, invalidate, when it is detected by the attachment/detachment detection unit that the recording apparatus has been detached from the vehicle, the detection of the event by the event detection unit after the detection of the detachment, and store captured data after the detection of the detachment as second event recording data.

According to one embodiment, a method of generating warning messages based on system load of an autonomous driving vehicle can relieve a safety operator of the burden of constantly monitoring the vehicle and outside driving environments. The method uses a threshold for each of a number of system load parameters to determine whether the vehicle has a heavy system load that needs the attention of the safety operator. In one example, the vehicle can use a CPU usage threshold and an end-to-end latency threshold to determine whether the vehicle has a heavy system load while travelling on a road segment. If any of the thresholds is exceeded, the vehicle can send a warning message to the safety driver. The system load thresholds may be determined from data collected from the autonomous driving vehicle when it previously travelled on the road segment.

This disclosure relates to a method for situation-dependent storage of data of a system, in which data of the system is detected, is amalgamated in at least one data block and is stored in a volatile memory, and in which, in response to the occurrence of at least one predefined trigger event in the at least one data block, amalgamated data are transferred from the volatile memory into a read-only memory, and in which a time window, in which the data for the at least one data block is captured, is selected automatically and dynamically according to the at least one trigger event.

A vehicle system may include a memory of a vehicle configured to maintain at least one smart contract between a manufacturer of the vehicle and a supplier of components to the manufacturer, and a processor of the vehicle configured to receive at least one diagnostic code from the vehicle, the diagnostic code being associated with at least one vehicle component, in response to the code being identified by the processor as being associated with the at least one smart contract, update the at least one smart contract within the memory with the code, and transmit the smart contract, as updated, to a third party associated with the vehicle component.

Provided are a server for maintenance, a remote monitoring system, and a remote monitoring method. The server is connected, via a network, to a plurality of working machines each including a working machine display device that displays machine state information and a working machine operating device to be used for predetermined operation, and to a monitoring terminal that includes a display part and remotely monitors information on the working machines. Communication between each of the plurality of working machines and the server is one-way communication from the working machines to the server. The server includes a first storage part, a second storage part, and a display processing part. The display processing part generates a display part simulated image, and causes the display part of the monitoring terminal to display a maintenance screen including the display part simulated image.