A method and system for automated transportation mode recognition based on sensory data measured by a plurality of sensors of a cellular mobile device of a user, the plurality of sensors at least comprising an accelerometer and a gyroscope, the plurality of sensors being connected to a monitoring mobile node application of the mobile device, wherein the mobile device measures time series of sensory parameter values based on measuring parameters obtained from the sensors, the measuring parameters comprise time series of sensory parameter values of a 3-axis accelerometer as sensor and time series of sensory parameter values of GPS-based speed measurements of a GPS receiver as sensor, and wherein the measured time series of sensory parameter values trigger the automated transportation mode recognition as input feature values to a gradient boosting machine-learning classifier, the transportation modes at least comprising the modes public transportation and/or motorcycle and/or cycling and/or train and/or tram and/or plane and/or car and/or skiing and/or boat, and the transportation mode recognition generating a transport mode label for a transport mode movement pattern of a trip.

Systems and methods for restricting the use of vehicle operator's electronic device are provided. In a method by a telematics server, the server determines that a vehicle's engine is running and that the operator registered with the vehicle is in the driver's seat. In response, the server sends a message to the vehicle operator's electronic device for disabling at least one feature thereof. In a method by a vehicle operator's electronic device, the electronic device determines that the vehicle is running and that the operator is in the driver's seat. In response, the electronic device disables at least one feature thereof. The systems and methods can be used to discourage or restrict the use of electronic devices by drivers sitting in a vehicle with the engine running in accordance with laws in certain jurisdictions.

Aspects of the disclosure relate to determining and responding to an internal state of a self-driving vehicle. For instance, an image of an interior of the vehicle captured by a camera mounted in the vehicle is received. The image is processed in order to identify one or more visible markers at predetermined locations within the vehicle. The internal state of the vehicle is determined based on the identified one or more visible markers. A responsive action is identified action using the determined internal state, and the vehicle is controlled in order to perform the responsive action.

Provided are methods for providing escalation based responses, which can include obtaining sensor data and determining whether the data satisfies at least one of one or more criteria. Some methods described also include determining a violation parameter and/or a response indicative of an escalation of a policy violation. Systems and computer program products are also provided.

An electric vehicle state control device of the present disclosure relates to an electric vehicle state notification device having, as states for operation safety related to parking/stopping, a key-on state in which a throttle is inactivated, a startup state in which the throttle is activated, and a driving state, and may comprise: a driving parameter confirmation unit for collecting measurement values of parameters related to the driving of an electric vehicle; a driving state determination/transition unit for determining the driving state of the electric vehicle from the collected measurement values of parameters related to the driving; and a driver notification unit for intuitively notifying a driver of the determined driving state of the electric vehicle.

Aspects of the disclosure relate to determining and responding to an internal state of a self-driving vehicle. For instance, an image of an interior of the vehicle captured by a camera mounted in the vehicle is received. The image is processed in order to identify one or more visible markers at predetermined locations within the vehicle. The internal state of the vehicle is determined based on the identified one or more visible markers. A responsive action is identified action using the determined internal state, and the vehicle is controlled in order to perform the responsive action.

Systems and methods for navigating a host vehicle are disclosed. In one implementation, a system includes a processor configured to receive from a camera onboard the host vehicle a captured image representative of an environment of the host vehicle. The captured image is provided to a trained system. The trained system is configured to infer an output from the captured image a presence of a curved road segment in the captured image, wherein the curved road segment is associated with a road on which the host vehicle is traveling. The processor is configured to receive the output provided by the training system. The output includes at least one speed value for the host vehicle. The at least one speed value output from the trained system is based on a proximity of the host vehicle to the curved road segment and based on at least one characteristic of the curved road segment represented in the captured image. The processor is configured to cause the host vehicle to take at least one navigational action based on the determined at least one speed value.

Controlling autonomous vehicle (AV) functions includes receiving occupant identification data from device(s) of an AV and identifying occupant(s) of the AV based on the received occupant identification data, determining a respective prioritization level for each occupant of the occupant(s), the prioritization level for each occupant dictating priority of the AV in performing commands provided to the AV by that occupant to control AV functions, receiving, from an occupant, input of a command for performance by the AV to control a function of the AV, determining whether to perform the command to control the function of the AV based on the prioritization level for the occupant, and performing processing based on the determining whether to perform the command.

A control apparatus includes a Wi-Fi communication module, a processor, a controller that controls a component of a vehicle, and a memory, wherein the memory stores at least one piece of position information corresponding to a position in the vehicle, and at least one registered pattern of a gesture, face, or shape, the Wi-Fi communication module transmits a transmission signal to the position corresponding to the at least one piece of position information by a Wi-Fi communication method at a preset frequency and receives a reflection signal reflected from an object in response to the transmission signal, the processor acquires an input pattern of a gesture, face, or shape of the object by analyzing the reflection signal, and retrieves a registered pattern matching the input pattern from the at least one registered pattern, and the controller controls the component according to an instruction corresponding to the retrieved registered pattern.

The present specification relates to a vehicle for monitoring an occupant's behavior, wherein the vehicle may: acquire sensing information related to a state of an occupant through a sensing unit; on the basis of the sensing information, define objects associated with the occupant, by using a monitoring model of the vehicle; and on the basis of the defined objects, generate context information indicating the state of the occupant. Furthermore, one or more of an autonomous driving vehicle, a user terminal, and a server of the present specification may be linked with an artificial intelligence module, a drone (unmanned aerial vehicle (UAV)) robot, an augmented reality (AR) device, a virtual reality (VR) device, a device related to 5G services, and the like.