A computer-implemented method for generating ground truth data may include the following steps carried out by computer hardware components: for a plurality of points in time, acquiring sensor data for a respective point in time; and for at least a subset of the plurality of points in time, determining ground truth data of the respective point in time based on the sensor data of at least one present and/or past point of time and at least one future point of time.

A system for increasing the safety of voice conversations between drivers and remote parties is shown. The system includes an in-vehicle subsystem and a remote subsystem. The system includes a plurality of sensors which are configured to generate monitoring data. The system includes a computing device, which may be distributed between the subsystems and is configured to calculate a risk level as a function of the monitoring data. The computing device may engage an automatic safety response as a function of the risk level, that may include suspension or termination of on-going conversations among the parties, together with notification about the status of the communication channel. The safety response may be communicated to the driver by generating an alert. The in-vehicle and the remote subsystems communicate using a wireless connection and collaborate in engaging the automatic safety response and communicating any alerts to the driver and remote party using notifications.

A vehicle control apparatus includes an electric motor, an engine, and a control system. The control system executes a first speed mode or a second speed mode as a speed mode of the transmission on the basis of a driving operation performed by a driver, sets a speed ratio on a lower side in the second speed mode than in the first speed mode in a case where an accelerator operation performed by the driver is cancelled, executes a first assist mode or a second assist mode as an assist mode in which the electric motor is brought into a power-running state, and switches the assist mode to the second assist mode in a case where the amount of the accelerator operation is increased greater than a starting threshold while the second speed mode is being executed.

An information processing apparatus compares a sense of use of a first vehicle with a sense of use of a second vehicle based on first information about one or more automobile components used by a user in the first vehicle that the user has used in the past in the first vehicle and second information about one or more automobile components used by the user in the second vehicle that is a vehicle candidate lent to the user. Then, the information processing apparatus notifies the user of result information related to a result of the comparing the sense of use of the first vehicle with the sense of use of the second vehicle.

An information processing server includes a target vehicle data recognition unit configured to recognize target vehicle data including a traveling state of a target vehicle and position information of the target vehicle on a map, an unstable behavior position recognition unit configured to recognize an unstable behavior position which is a position on the map, at which at least one target vehicle has performed an unstable behavior, based on a plurality of pieces of the target vehicle data, a determination unit configured to determine whether the unstable behavior position is in a continuous occurrence situation or a discontinuous situation, based on whether or not a plurality of the target vehicles perform the unstable behavior at the unstable behavior position, and a storage processing unit configured to store a determination result by the determination unit, in a storage database in association with the unstable behavior position.

The disclosure provides a method and device for generating driving suggestion, and computer-readable storage medium. The method comprises: acquiring N driving records, wherein the N driving records are derived from at least two vehicles, each driving record comprises a mapping relationship between a driving period and an acceleration value, and the N is an integer greater than 1; determining a plurality of acceleration metric values based on the acceleration values in the N driving records, wherein each vehicle corresponds to at least one acceleration metric value, and the acceleration metric value is positively correlated with the acceleration value; determining a metric threshold according to the plurality of acceleration metric values; and generating a driving suggestion based on the metric threshold and the driving record corresponding to any one of the at least two vehicles.

An in-vehicle data collection and processing device receives real-time data from a plurality of sensors relating to at least one of a current vehicle condition and a current driver condition. The device then predicts, by processing at least a portion of the real-time data through a pre-trained pattern recognition algorithm, a likelihood of occurrence of at least one of a plurality of incidents involving the vehicle. In response, the device outputs one or more types of warnings and/or conducts a vehicle evasive maneuver if the likelihood is predicted to be above one or more thresholds.

A vehicle includes: a driver assistance system; an accelerator configured to perform acceleration of the vehicle; a braking device configured to perform deceleration of the vehicle; a velocity sensor configured to detect a current velocity of the vehicle; a driver status sensor configured to acquire a driver's behavioral data; and a controller. The controller is configured to identify a carelessness status of the driver based on the driver's behavioral data and to activate a velocity control mode when the carelessness status of the driver is detected in the activation status of the driver assistance system.

Proposed is an electronic risk measuring and scoring system, in particular for mobile telematics devices and method thereof. In particular, an electronic risk measuring and scoring system which measures an ADAS risk score measure measuring the impact of ADAS features to the accident risk associated with a motor vehicles, and which rates and calibrates a risk-transfer user-specifically thereby capturing the impact of ADAS features in measures of risk-transfer claims frequency and severity.

A vehicle-based safety intervention system receives sensor data collected or generated by an onboard computing system of a vehicle. The sensor data is divided into a plurality of blocks, each of the blocks having a duration. A driver behavioral model is applied to one or more of the plurality of blocks to generate one or more driver behavioral parameters. A trend of the one or more driver behavioral parameters is extracted from the plurality of blocks. Based on the extracted trend, it is determined that a driver's performance when operating the vehicle is unsatisfactory or will be unsatisfactory in the future. A vehicle-based intervention is generated based on the determination that the driver's performance is unsatisfactory or will be unsatisfactory in the future.