A method is provided. The method includes: obtaining first environmental information and second environmental information, where the first environmental information and the second environmental information are acquired by different sensors; determining, based on the first environmental information, information about a first lane of a first traffic object in the first environmental information, and determining; and determining whether the first traffic object and the second traffic object have an association relationship.

A target dangerous travel scene existing on a target road section is acquired. Reference information corresponding to the target road section is acquired. The reference information is determined according to a detection record corresponding to each of N dangerous travel scenes detected on the target road section within a target time period. N is an integer greater than 1. The detection record corresponds to each dangerous travel scene being used for reflecting time at which the corresponding dangerous travel scene is detected. An associated dangerous travel scene correlated to the target dangerous travel scene from the N dangerous travel scenes is determined according to the reference information. A prompt operation according to the target dangerous travel scene and the associated dangerous travel scene is performed.

A traffic warning method and apparatus includes: obtaining driving status information of a dangerous vehicle on a target road and pavement status information of the target road; determining potential collision strength of the dangerous vehicle against a first vehicle according to driving status information of the first vehicle on the target road, the driving status information of the dangerous vehicle, and the pavement status information of the target road; correcting the potential collision strength of the dangerous vehicle against the first vehicle according to a difference between a performance parameter of the dangerous vehicle and a performance parameter of a non-dangerous vehicle on the target road; and performing traffic warning according to the corrected potential collision strength of the dangerous vehicle against the first vehicle.

A system and method for alerting a driver of a motor vehicle or a person walking along a road or hiking on a trail of potentially dangerous hazards in their path. Hazards may be deep water, ice, oil slicks or other hazards. In the case of a motor vehicle, the system uses cameras mounted on or within the vehicle to detect potential hazards and then analyzes the images combined with the known topography of the location to evaluate the ability of the vehicle to safely traverse the hazard. In the case of a person walking or hiking, the person may use the camera on a personal mobile device to capture images of the hazard and to combine the images with the known topography at the location to evaluate the danger presented by the hazard.

An advice target location at which a user had a predetermined emotion, for example, is determined based on location information, user biological information, and user transportation means information, which have been acquired by a terminal device (20) being used by the user. Advice information containing information indicating an advice presentation region set by a server device (50) is generated based on the advice target location. This advice information is supplied from the server device (50) to the terminal device (20), so that the terminal device (20) presents advice. With this, advice as to locations pedestrians find dangerous can be presented to drivers, and advice as to locations drivers find dangerous can be presented to pedestrians. Accordingly, accidents and the like can be prevented.

Systems and methods are disclosed for monitoring or affecting movement of a vehicle using a traffic device. An event data source may have a processor and/or a transceiver. The event data source may transmit, via the transceiver and to a vehicle and infrastructure computing device, information indicative of an event affecting a portion of road. The vehicle and infrastructure computing device may comprise a vehicle and infrastructure control computer. The vehicle and infrastructure computing device may receive, from the event data source, the information indicative of the event affecting the portion of road. The computing device may determine one or more traffic devices associated with the portion of road and configured to control traffic for the portion of road. Based on the information indicative of the event affecting the portion of road, the computing device may send, to the one or more traffic devices associated with the portion of road, instructions to change one or more characteristics of the one or more traffic devices.

Example aspects of the present disclosure describe a scene generator for simulating scenes in an environment. For example, snapshots of simulated traffic scenes can be generated by sampling a joint probability distribution trained on real-world traffic scenes. In some implementations, samples of the joint probability distribution can be obtained by sampling a plurality of factorized probability distributions for a plurality of objects for sequential insertion into the scene.

A method, apparatus and computer program product are provided to determine lane status confidence indicators of lane status predictions such as closures and/or shifting. Lane statuses and corresponding confidence indicators are determined based on probe data, such as probe data collected from vehicle and/or mobile devices traveling along a road segment. Probe data may be partitioned into clusters and compared to partitioned subsets of the probe data. Cluster stability for the segment and corresponding lane status confidence indicators can be determined based on the comparison. Accordingly, determinations of whether to transmit predicted lane statuses to another system, service, and/or user device may be made.

Systems and methods for navigating a host vehicle. The system may perform operations including receiving, from an image capture device, at least one image representative of an environment of the host vehicle; analyzing the at least one image to identify an object in the environment of the host vehicle; determining a location of the host vehicle; receiving map information associated with the determined location of the host vehicle, wherein the map information includes elevation information associated with the environment of the host vehicle; determining a distance from the host vehicle to the object based on at least the elevation information; and determining a navigational action for the host vehicle based on the determined distance.

The disclosure relates to a method for training a first neural network, in particular for generating training data for at least one second neural network, using a controller, wherein measurement data ascertained by at least one surroundings sensor or artificially generated data of initially ten traffic scenarios is received, the received measurement data is fed to the first neural network as input data in order to train the first neural network, and the first neural network which is trained on the basis of the input data is used to generate data of traffic scenarios which differ from the initial traffic scenarios. Furthermore, the disclosure relates to a method for training at least one second neural network, to a controller, to a computer program, and to a machine-readable storage medium.