A prediction method and apparatus for an autonomous driving manual takeover, and a system are provided. One example method includes: A first vehicle sends a first message to a second vehicle when detecting that the first vehicle has a manual takeover requirement, where the first message includes information about a first location of the first vehicle, and the information about the first location is used to indicate a location of the first vehicle when the first vehicle detects that the first vehicle has the manual takeover requirement.

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.

The present disclosure relates to a method for predicting a behavior of a target vehicle in a maneuvering space, in which a plurality of maneuvers which can be executed in the future are provided for the target vehicle, in the maneuvering space, the target vehicle located in the maneuvering space being observed by a plurality of observation vehicles, for each maneuver of the target vehicle that can be executed in the future, a single probability distribution for the relevant maneuver that can be executed in the future being determined, on the basis of an observation performed by a relevant observation vehicle, for each maneuver of the target vehicle that can be executed in the future, a total probability distribution for the relevant maneuver of the target vehicle that can be executed in the future being established from a plurality of single probability distributions.

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.

In a crack detection device (10), an image acquisition unit (21) acquires image data acquired by taking an image of a road surface from an oblique direction with respect to the road surface, An image classification unit (22) classifies image data acquired into an acceptable range with a resolution higher than a standard value, and an unacceptable range with a resolution equal to or less than the standard value. A data output unit (23) outputs acceptable data being image data of a part classified into the acceptable range as data to detect a crack on the road surface. An image display unit (24) displays data output.

Connected and automated vehicles (CAVs) have shown the potential to improve safety, increase road throughput, and optimize energy efficiency and emissions in several complicated traffic scenarios. This invention describes a mixed-integer programming (MIP) optimization method for global multi-vehicle decision making and motion planning of CAVs in a highly dynamic environment that consists of multiple human-driven, i.e., conventional or manual, vehicles and multiple conflict zones, such as merging points and intersections. The proposed approach ensures safety, high throughput and energy efficiency by solving a global multi-vehicle constrained optimization problem. The solution provides a feasible and optimal time schedule through road segments and conflict zones for the automated vehicles, by using information from the position, velocity, and destination of the manual vehicles, which cannot be directly controlled. Despite MIP having combinatorial complexity, the proposed formulation remains feasible for real-time implementation in the infrastructure, such as in mobile edge computers (MECs).

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.

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.

A method for operating at least one automated vehicle, including the steps: detecting road users by sensors with the aid of the at least one automated vehicle and/or with the aid of sensor systems in an infrastructure; ascertaining predicted traffic routes for the road users with the aid of a computing device based on defined criteria; transmitting control data corresponding to the predicted traffic route to the automated vehicle; and operating the automated vehicle according to the control data.