A system for identifying desired information from collected sensor data includes a collection device and a processing module. The collection device collects sensor data, coarsely filters the sensor data according to predefined rules to generate filter matched data, and securely transmits the filter matched data to the processing module. The processing module finely filters the filter matched data to generate desired information, provides the desired information to an authorized actor, and deletes the filter matched data.

Techniques are described for dynamically selecting vehicles to perform road friction probing maneuvers and estimating road friction based on sensor data collected while a vehicle performs the road friction probing maneuvers. In one example, a computing system is configured to select, from a plurality of vehicles, based on an amount of elapsed time since each respective vehicle of the plurality of vehicles has performed a road friction probing maneuver, a vehicle to perform the road friction probing maneuver within a road segment of a roadway, and responsive to selecting the vehicle, output, to the vehicle, a command causing the vehicle to perform the road friction probing maneuver within the road segment.

According to one embodiment, a method, computer system, and computer program product for using mobile devices for anomaly detection in a vehicle. The present invention may include a computer receives sensor data from at least one mobile device associated with the vehicle, where the mobile device having one or more sensors. The computer analyzes data from the one or more sensors to identify an anomaly associated with the vehicle. The computer identifies a message associated with the anomaly. The computer determines an urgency value of the message based on the anomaly. The computer transfers the message with the urgency value to the vehicle and causes the vehicle to notify the message using a vehicle notification device.

A method for operating a motor vehicle having a camera device that records the area ahead of the vehicle and an associated control device for evaluating images taken by the camera device, wherein the control device evaluates the images in order to detect at least one hand gesture performed by a person shown in the images, wherein, when a hand motion describing a calling gesture that indicates a stop request is detected, in the case of a self-driving motor vehicle, the motor vehicle is controlled to stop in the vicinity of the person, or in the case of a non-self-driving motor vehicle, the driver of the motor vehicle is given a signal indicating the stop request.

Methods, devices and a computer-readable medium comprising instructions for determining applicable traffic regulations for a motor vehicle are provided. In some embodiments, the position and direction of movement of the motor vehicle are determined. The position and direction of movement of the motor vehicle are then transmitted to a back end by a transmission apparatus of the motor vehicle. In response to the information transmitted to the back end, information concerning traffic regulations applicable to the position of the motor vehicle is received by the transmission apparatus. The transmission of the position and direction of movement of the motor vehicle to the back end is carried out in a cyclical manner or in accordance with information concerning the validity of the traffic regulations, which is included in the information concerning the traffic regulations applicable at the position of the motor vehicle.

The present invention relates to a method of cooperatively coordinating future driving maneuvers of a vehicle with fellow maneuvers of at least one fellow vehicle, wherein trajectories for the vehicle are rated with an effort value each, trajectories and fellow trajectories of the fellow vehicle are combined into tuples, the trajectory and the associated effort value of a collision-free tuple are selected as reference trajectory and reference effort value, trajectories with a lower effort value than the reference effort value are classified as demand trajectories, trajectories with higher effort value than the reference effort value are classified as alternative trajectories, and a data packet having a trajectory set consisting of the reference trajectory and the associated reference effort value as well as at least one trajectory from a group comprising the demand trajectories and the alternative trajectories as well as the respective effort values is transmitted to the fellow vehicle.

A device can receive, from a client device, information identifying a location of the client device and determine at least one of an expected future location of the client device or the expected route of the client device based on the information identifying the location of the client device and at least one of: information identifying one or more expected possible routes e associated with the client device, or information identifying a route history associated with the client device, determine, based on the expected future location of the client device, information representing a map fragment and can determine speed limit information associated with the map fragment and, transmit, to the client device, the information representing the map fragment and the speed limit information, wherein the client device is to use the information representing the map fragment and the speed limit information to determine a speeding event associated with a vehicle.

An example operation includes one or more of receiving, via a transport, a transport audio, classifying, via the transport, a subset of the transport audio as an atypical transport audio, determining, via the transport, a possible source location of the atypical transport audio, transmitting, via the transport, the atypical transport audio and the possible source location to a server, determining, via the server, a set of potential causes of the atypical transport audio and receiving, via the transport, the set of potential causes of the atypical transport audio.

This application discloses an object control system (OCS) to control navigation of a moving vehicle when exiting from its own road or freeway to a new road or freeway. The new road or freeway is an underpass or overpass and have no physical junction with the moving vehicle's own road or freeway. The moving vehicles obtains its navigation information data from the IoT network it is registered with and a plurality of stationary objects near and in vicinity of an exit. The stationary objects during the time slots assigned to them by OCS transmit variety of information data that assist moving vehicle navigating to the right lane and exit. These stationary objects also provide an operation information data that is used in the new road or freeway in case the vehicle exits to a road or freeway that belongs to a new cell with different operation information data.

A method predicts a switch state and/or a switch time point of a signaling system. The method includes collecting first and second state data, the first and second state data influencing the switch state and/or switch time point. The collection of the first state data includes reading of state data from a signaling system control device of the signaling system by a signaling system interface. The collection of the second state data includes reading in of the state data. A prediction model is provided and configured to make a prediction of the switch time point and/or the switch state of the signaling system based on first and second state data. The switch state and/or the switch time point of the signaling system is predicted via the prediction model using the first and second state data. The predicted switch state and/or switch time point of the signaling system is outputted.