A system for evaluating performance of a driver of a vehicle with an electronic control unit is provided. The system includes an evaluation processor configured to access driving dynamics data regarding operation of the vehicle, and a driver monitoring sensor in communication with the evaluation processor to generate driver status data that relates to a position, orientation, or condition of the driver. One or more external monitoring sensors are in communication with the evaluation processor to generate external interaction data relating to interaction of the driver with an external environment. The evaluation processor is configured to generate a driver rating based upon the driving dynamics data and the driver status data and the external interaction data. A method for evaluating performance of a driver of a vehicle is also provided.

The present invention comprises a tool and a method for use in CDL training. The tool comprises a flat plane segmented into sections designated as levels. Each level comprises a one or more parking lanes to support the designated level. The size of each level is customized to support the backup training level. The tool can further comprise a software application to provide simulated backup instruction for the user.

The present application provides a virtual reality-based derailment accident passenger comfort degree monitoring system and method, wherein the system comprises a train dynamics calculation module, a train operation state virtual simulation module, a six-degree-of-freedom motion platform, a train seat, a head-mounted display, a human body monitoring sensor system and a monitoring data storage terminal. The system establishes a database of the injury degrees of passengers with different ages under the train derailment; the test cost is low, the safety coefficient is high, and the repeatability of the test conditions is good, wherein the comfort degree test data of the passengers under the same derailment inducement can be repeatedly obtained; the safety risk in the actual test is eliminated, so that the authenticity of the test result is ensured, and the test cost is low and the repeatability is high.

A method and a device for planning and/or controlling and/or simulating the operation of a construction machine, in particular in the form of a crane, using a structure data model which contains digital information on a structure to be erected and/or to be worked on. A construction machine which can be linked to such a structure data model and/or can be controlled using such a structure data model. A construction machine data model which contains digital information on different construction machine models is linked to the structure data model or the BIM, characteristics of the available construction machines are already taken into consideration during the planning process, a simulator for training construction machine tasks is configured using the structure data model, and the controller of the construction machine is adapted to the structure data model with respect to specific control functions.

Present invention provides a system and method that includes installation of one or more cameras at various locations on a smart driving yard or in a parking lot. These cameras capture activity of a vehicle in the smart driving yard and perform an analysis using Computer Vision and machine learning. In some embodiments, one or more drones may also be employed for capturing the vehicle activity. The vehicle location is identified based on the individual pose of markers installed on the vehicle for easier object localization. The vehicle is then localized and its location is marked on a 2-dimensional map of the yard. Subsequently, a lane model is applied to identify driving violations or errors that a driver commits while driving. Subsequently, a lane model based on decision trees algorithm is trained to identify if the vehicle touches/intersects any of the parking line markings or any zones of interest.

A monitoring and maintenance system that utilizes imperial and theoretical data to compare parts, vehicles, users, regions, wear intensity indexes over time and tracking information to provide a sophisticated data collection system for heavy-duty equipment or rental equipment. This tracking is designed to better the specifications, designs, training, preventative maintenance, and replacement wear understanding of fleet management.

A method is provided for providing a tutorial message to a driver in a vehicle using an in-vehicle tutorial system including a multimodal user interface. The method includes assigning an area of improvement, including at least one tutorial task, to the tutorial system, identifying a driving context for which a tutorial task is to be performed, based on the tutorial task and the driving context, selecting a tutorial message encouraging a desired driving behavior, and providing the selected tutorial message to the driver using the multimodal user interface.

A circuit driving guide device includes at least one camera unit, disposed in a first vehicle, for acquiring driving information of the first vehicle driven on a driving route of a circuit and circuit information provided for each event occurring during driving on the driving route of the circuit, a communication module, disposed inside the first vehicle, for receiving, from a circuit server, map information of the driving route of the circuit and driving information of a second vehicle among one or more other vehicles driven on the driving route of the circuit, and a driving guide processor, disposed inside the first vehicle, for guiding a user in driving by analyzing the driving information of the first vehicle and the circuit information acquired from the at least one camera unit, and the map information and the driving information of the second vehicle provided from the communication module, and by applying an analyzed result value, obtained from the analyzing of the driving guide processor, to a driving rule of a preset circuit.

Techniques are described for providing educational media content. According to an embodiment, a system for providing, by a processor, educational media content items based on a determined context of a vehicle or driver of the vehicle is described. The system can comprise a context component that can determine a context of a vehicle or a driver of the vehicle, with the context component employing at least one of artificial intelligence or machine learning to facilitate inferring intent of the driver. The system can comprise a vehicle education component that can perform a utility-based analysis in connection with selecting a media content item relating to a feature of the vehicle based on the determined context, the inferred driver intent and the utility-based analysis. Further, the system can comprise a media component that can output the selected media content item.

A method for adjusting a safety margin threshold of one or more driver support functions of a vehicle, to be suitable for a driving zone in which the vehicle is—or is to be—positioned comprises determining a geographical position of the vehicle, determining a driving zone associated with the vehicle position, which driving zone is selected from one or more pre-defined geographical driving zones, deriving previous statistical driving behaviour data indicative of one or more statistical driving style safety indicators associated with the driving zone, and adjusting a safety margin threshold of at least a first driver support function of the vehicle, based on the one or more statistical driving style safety indicators. The disclosure also relates to a driver support threshold adapting system in accordance with the foregoing, and a vehicle at least partly comprising such a driver support threshold adapting system.