An image projection apparatus that can be attached to a vehicle and can be effectively utilized for acquisition of road surface condition information, detection of a hidden vehicle, and the like is provided. The image projection apparatus that projects an image includes: an acquisition unit that acquires information related to a vehicle; an image projection unit that projects an image based on the information acquired by the acquisition unit; and imaging means that acquires an image outside the vehicle, the image projection unit projects light in a wavelength band centered on a wavelength of 1.4 μm and the imaging means provides the information related to the vehicle by imaging an image projected based on the light in the wavelength band centered on the wavelength of 1.4 μm.

According to one embodiment, when a predicted trajectory is received, a set of one or more features are extracted from at least some of the trajectory points of the predicted trajectory. The predicted trajectory is predicted using a prediction method or algorithm based on perception data perceiving an object within a driving environment surrounding an autonomous driving vehicle (ADV). The extracted features are fed into a predetermined DNN model to generate a similarity score. The similarity score represents a difference or similarity between the predicted trajectory and a prior actual trajectory that was used to train the DNN model. The similarity score can be utilized to evaluate the prediction method that predicted the predicted trajectory.

A system includes a processor and a memory. The memory stores instructions executable by the processor to receive an image from a stationary camera. The memory stores instructions to determine location coordinates of an object identified in the image based on location coordinates specified for the image. The memory stores instructions to operate a vehicle based on the object location coordinates.

Methods, computer programs, apparatuses, a transportation vehicle, and a traffic entity for updating an environmental model at a transportation vehicle. The method for a transportation vehicle and for updating an environmental model of the transportation vehicle includes obtaining an environmental model of the transportation vehicle, the environmental model having static and dynamic objects in the environment of the transportation vehicle along at least a part of the trajectory of the transportation vehicle; assigning information related to correctness probabilities at least to dynamic objects of the environmental model; determining at least one dynamic object for which the information related to the correctness probability indicates a correctness probability below a threshold; and transmitting a broadcast message to the environment to request further information on the at least one dynamic object.

Systems and methods are provided for processing reports received from vehicles. A processing device perform operations comprising receiving a first report from a first vehicle, the first report generated by the first vehicle for a first hazard detected by the first vehicle; receiving a second report from a second vehicle, the second report generated by the second vehicle for a second hazard detected by the second vehicle; analyzing the first report and the second report to make a determination that the first report and the second report identify a related hazard; aggregating the first report and the second report into a consolidated report based on the determination that the first report and the second report identify a related hazard; and processing the consolidated report to identify a contributing factor to the related hazard.

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.

Provided is a position estimation device capable of highly accurate position estimation. A position estimation device 1 of the present invention is the position estimation device 1 which estimates a current position of a moving object 100 equipped with an imaging device 12, estimates the current position of the moving object 100, create a plurality of virtual positions based on the current position, creates virtual images at the plurality of virtual positions, respectively, compares the plurality of virtual images with an actual image to calculate a comparison error, calculates a weight based on at least one of information acquired by the imaging device 12 and information of a current position error of the moving object, performs weighting on the comparison error using the weight, and corrects the current position based on the comparison error to be weighted.

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 control apparatus includes a risk area specification unit to specify a risk area outside a movable object, a transmission control unit to perform control to transmit alert information related to a position of the risk area to an outside of the movable object, a reception control unit to perform control to receive response information including information related to a position of another movable object that is response information to the alert information which is transmitted by the other movable object, and a control unit to execute control of the movable object based on position information of the risk area and the information related to the position of the other movable object which is acquired, in which the alert information includes information for controlling a mode related to a transmission cycle of the response information to be transmitted by the other movable object which has received the alert information.