A vehicle navigation system includes an electronic control unit. The electronic control unit receives image data regarding a source of a traffic jam on a roadway from a plurality of sensors of a plurality of vehicles in a mesh network. Moreover, the electronic control unit generates a bird's eye view of the traffic jam based on the image data, wherein the bird's eye view includes a graphical representation of the source of the traffic jam and a graphical representation of vehicles on the roadway within the traffic jam. A display device displays the bird's eye view.

A vehicle takes and evaluates an image of the surroundings of the vehicle. If the result of the evaluation is that the image possibly contains a static object that could be suitable as a landmark, then the image and a position of the vehicle ascertained by the vehicle at the location at which the image is taken are transmitted to a data processing station. Image analysis of the received image allows the data processing station to establish whether the supposedly static object is suitable as a landmark. When the object has been verified as a landmark, the data processing station creates a data record describing the object, which data record is transmitted to the vehicle.

There is provided a signal processing apparatus, a signal processing method for appropriate driving control. The signal processing apparatus includes a safety determination unit that determines safety of a preceding vehicle on a basis of sensor-related information related to a sensor provided in the preceding vehicle, the sensor being relevant to a safety function, and a control signal generation unit that generates, on a basis of a result of the determination of the safety, a control signal for controlling a host vehicle.

A roadway complexity awareness system for a vehicle, comprising a processor, an augmented reality interface disposed in communication with the processor, and a memory for storing executable instructions. The processor is programmed to execute the instructions to receive roadway status information from an infrastructure processor associated with a roadway, obtain, from a vehicle sensory system, sensory information indicative of roadway route complexity, and determine a likelihood of roadway route complexity based on the roadway status information and the sensory information. The system may select an augmented reality message indicative of the roadway route complexity, and generate the augmented reality message using an augmented reality interface device, wherein the augmented reality message is visible to a vehicle operator.

The present application relates to a method for providing vehicle functions in a motor vehicle, the vehicle functions being provided in a computing device of said motor vehicle on the basis of sensor data from a sensor device of the motor vehicle. The invention provides that the vehicle functions in the motor vehicle are coupled to the sensor device via an integration component, and the integration component procures the sensor data from one sensor unit or a plurality of sensor units of the sensor device independent of the vehicle functions by means of a respective sensor-specific detection routine and generates respective state data therefrom and each of the vehicle functions respectively retrieves at least some of the provided state data from the integration component by means of a sensor-independent retrieval routine.

Disclosures herein may be directed to a method, technique, or apparatus directed to a computer-assisted or autonomous driving (CA/AD) vehicle that includes a system controller, disposed in a first CA/AD vehicle, to manage a collaborative three-dimensional (3-D) map of an environment around the first CA/AD vehicle, wherein the system controller is to receive, from another CA/AD vehicle proximate to the first CA/AD vehicle, an indication of at least a portion of another 3-D map of another environment around both the first CA/AD vehicle and the another CA/AD vehicle and incorporate the at least the portion of the 3-D map proximate to the first CA/AD vehicle and the another CA/AD vehicle into the 3-D map of the environment of the first CA/AD vehicle managed by the system controller.

The present disclosure describes an intelligent roadside unit and a control method thereof, comprising: a circular camera array, including a plurality of cameras for capturing images in different road directions respectively; a circular radar array, including a plurality of radars for detecting obstacle information in different road directions respectively; and a controller configured to determine whether a vehicle is approaching according to the obstacle information detected by the radars, to turn on a camera corresponding to the radar that has detected the approaching of the vehicle to capture an image, and to control the cameras corresponding to the radars that have not detected the approaching of the vehicle to be in a standby state.

A path providing device configured to provide a path information to a vehicle includes: a communication unit configured to receive, from a server, map information including a plurality of layers of data, an interface unit configured to receive sensing information from one or more sensors disposed at the vehicle, a processor, and an event data recorder (EDR) configured to store vehicle status information including first sensor data sensed by a first sensor associated with an operation of the vehicle, and second sensor data sensed by a second sensor associated with surrounding information of the vehicle. The processor is configured to determine an optimal path for guiding the vehicle from an identified lane, generate autonomous driving visibility information, update the optimal path based on dynamic information and the autonomous driving visibility information, and include the vehicle status information stored in the EDR in the autonomous driving visibility information.

A system for location risk determination and ranking based on vehicle events and/or an accident database includes an interface and a processor. The interface is configured to receive accident data and/or event data. The processor is configured to determine a set of incident groups, wherein an incident group of the set of incident groups is associated with a set of accidents of the accident data and/or a set of events of the event data that are grouped by location proximity. The processor is further configured to determine a set of traffic estimations, wherein a traffic estimation of the set of traffic estimations is associated with the incident group of the set of incident groups; and determine a ranking of the set of incident groups based at least in part on the set of accidents, the set of events, and the set of traffic estimations.

A method for assessing possible trajectories of road users in a traffic environment includes capturing the traffic environment with static and dynamic features, identifying at least one traffic user, determining at least one possible trajectory for at least one road user in the traffic environment, and assessing the at least one determined possible trajectory for the at least one road user with an adapted/trained recommendation service and the captured traffic environment.