A system configured to, and method of, generating and providing a data product using data supplied by a multitude of vehicles that includes receiving a plurality of geographical locations; carrying out a geographical location obfuscation process in order to obtain processed connected vehicle data, wherein the geographical location obfuscation process includes: (i) identifying a road segment based on the received geographical location; (ii) determining an associated road type of the road segment; (iii) determining whether to obfuscate the received geographical location based at least in part on the associated road type; and (iv) when it is determined to obfuscate the received geographical location, obfuscating the received geographical location so as to obtain an obfuscated geographical location, wherein the obfuscated geographical location is included in the processed connected vehicle data; generating the data product using the processed connected vehicle data; and providing the data product to a third party.

A system includes a processor and a memory storing instructions which when executed by the processor configure the processor to receive telemetry data from a vehicle being driven in a road segment, detect lane changes made by the vehicle in the road segment based on the telemetry data, and characterize the road segment and driver behavior based on the lane changes and the telemetry data.

An accident risk diagnosis apparatus stores travel data that is data indicating a travel state of each of a plurality of vehicles for each date and time and information on past accidents of the plurality of vehicles, extracts the travel data for a predetermined period before an accident day and the travel data on the accident day from among the travel data, generates training data for each trip that is a period from activation to termination of a vehicle based on an extracted travel data, generates an accident risk diagnosis model that is a machine learning model for diagnosing an accident risk using the training data, inputs a feature in a trip of a vehicle to be diagnosed to the accident risk diagnosis model to diagnose the accident risk, and transmits a diagnosis result to an in-vehicle device mounted on the vehicle.

A vehicle control system for providing information to support an overtaking maneuver by a first vehicle, the vehicle control system includes: a processing circuitry adapted to be operatively connected to a traffic view camera and configured to: receive image data of at least one other vehicle in traffic by the traffic view camera; determine, based on the image data of the at least one other vehicle in traffic, overtaking support data indicative of at least one gap in the traffic suitable for an overtaking maneuver; and provide the overtaking support data to the first vehicle for supporting an overtaking maneuver by the first vehicle.

A method is provided for controlling a transmit power of at least one active vehicle surround sensor of a vehicle driven in an at least partially automated manner, at least one automated driving function of the vehicle being implemented on the basis of surroundings data acquired by the active vehicle surround sensor and/or on the basis of data received from an infrastructure. The method includes: receiving at least one first message from an infrastructure; generating, depending on information in the received first message, control signals for reducing the transmit power of an active vehicle surround sensor, and outputting the control signals; verifying, on the basis of surroundings conditions, whether the transmit power of the active vehicle surround sensor can be increased again; generating, depending on the verification, control signals for increasing the transmit power of the active vehicle surround sensor, and outputting the control signals.

Disclosed embodiments are related to techniques for implementing Collective Perception Services in Intelligent Transport Systems. Embodiments include technologies for sharing layered costmaps and/or sharing perceived object clusters in Collective Perception Messages. Other embodiments may be described and/or claimed.

An information processing apparatus, which is provided to display advertisement information on a display apparatus installed with a display surface directed to a road, is configured to execute acquisition of a traveling situation of a vehicle which travels on the road; selection of a first display form or a second display form having an amount of information larger than that of the first display form, as the display form of the advertisement information on the basis of the traveling situation; and display of the advertisement information on the display apparatus in the display form selected on the basis of the traveling situation.

System and methods for automated sign data collection and reporting while operating a vehicle on the road using a device. The device automatically determines when to collect, store, process and transmit data. Additionally, a system and method for further storing, transmitting, processing, organizing and accessing the information with respect to the collected data.

The disclosure presents a system for remotely managing emergency equipment through wireless network and methods to use this system to monitor emergency equipment and deliver emergency information to subscribers. The system for remotely managing emergency equipment includes at least a node, also called as end user emergency equipment, a remote server, and a plurality of direct and indirect subscriber devices. The remote server receives data collected from each node, processes the node data, and sends the processed data to direct and indirect subscribers to manage emergency equipment. The system can improve the efficiency on collision avoidance, emergency warning, and emergency vehicle dispatch management.

Systems and methods for determining autonomous vehicle user boarding times are provided. In one example embodiment, a computer implemented method includes obtaining location data associated with a user device associated with a user. The method includes determining an estimated time until the user starts boarding the autonomous vehicle based at least in part on the location data associated with the user device. The method includes obtaining data associated with the user. The method includes determining an estimated time of boarding duration for the user based at least in part on the data associated with the user. The method includes determining an estimated time until the user completes boarding of the autonomous vehicle based at least in part on the estimated time until the user starts boarding the autonomous vehicle and the estimated time of boarding duration for the user.