A vehicle control device in an embodiment includes a recognition unit that recognizes a surrounding situation of a vehicle and a driving control unit that controls one or both of steering and acceleration or deceleration of the vehicle on the basis of the surrounding situation recognized by the recognition unit, and in a case where the vehicle merges into a second lane from a first lane in which the vehicle travels, and a section of the second lane before merging recognized by the recognition unit is downhill, the driving control unit makes a speed or acceleration of the vehicle higher than in a case where the section before merging is not downhill.

In various examples, a current claimed set of points representative of a volume in an environment occupied by a vehicle at a time may be determined. A vehicle-occupied trajectory and at least one object-occupied trajectory may be generated at the time. An intersection between the vehicle-occupied trajectory and an object-occupied trajectory may be determined based at least in part on comparing the vehicle-occupied trajectory to the object-occupied trajectory. Based on the intersection, the vehicle may then execute the first safety procedure or an alternative procedure that, when implemented by the vehicle when the object implements the second safety procedure, is determined to have a lesser likelihood of incurring a collision between the vehicle and the object than the first safety procedure.

A method for calculating a lateral position of an ego motor vehicle on a traffic lane includes calculating a first theoretical lateral position of the ego vehicle, calculating a second theoretical lateral position of the ego vehicle, calculating a third theoretical lateral position of the ego vehicle, calculating the lateral position of the ego vehicle using a weighted average of the first lateral position, the second lateral position, and the third lateral position.

A graph representation of a tactical map representing a plurality of static components of an environment of a vehicle is generated. Nodes of the graph represent static components, and edges represent relationships between multiple static components. Different edge types are used to indicate respective relationship semantics among the static components. Individual nodes are represented as having the same number and types of edges in the graph. Using the graph as input to a neural network based model, a set of results is obtained. A motion control directive based at least in part on the results is transmitted to a motion-control subsystem of the vehicle.

A vehicle recording device includes: a mode acquisition unit configured to acquire a signal indicative of an operating mode of an autonomous driving processing unit; a recording target setting unit configured to change a recording target in accordance with the operating mode; and a recording processing unit configured to store information of the recording target set by the recording target setting unit into a data storage unit. The recording target setting unit is further configured to: set a face image of an occupant in a driver's seat as the recording target when the autonomous driving processing unit operates in a level 3 mode; and not set the face image as the recording target when the autonomous driving processing unit operates in an occupant involvement mode.

A method may include obtaining, by an autonomous driving system, input information relating to an autonomous vehicle (AV). The method may include determining, by the autonomous driving system, one or more driving signals that describe operations of the AV. The method may include instructing the AV to move according to the driving signals and simulating, by a virtual driving system, movement of the AV based on the driving signals, wherein the simulating the movement of the AV occurs concurrently with the AV moving according to the driving signals as instructed.

An object detection device includes a processor. The processor acquires or generates a first disparity image generated on the basis of an output of a stereo camera mounted in a mobile object. In the first disparity image, pixels representing disparities are arranged on a two-dimensional plane formed by a first direction corresponding to a base-length direction of the stereo camera and a second direction intersecting the first direction. The processor approximates a relationship between a coordinate, in the second direction, of a road surface in a direction of travel of the mobile object and a disparity representing the road surface with two straight lines, the relationship being included in the first disparity image.

Predicting future infrastructure performance of a pathway article based on data for infrastructure performance features that influence predicted infrastructure performance at a future point in time. To predict infrastructure performance at a future point in time, a computing device receives one or more sets of infrastructure performance data for a pathway article that correspond respectively to infrastructure performance features. The infrastructure performance features may influence predicted infrastructure performance of the pathway article at a future point in time and the infrastructure performance data may correspond to a roadway portion. The computing device may generate, based at least in part on applying the one or more sets of infrastructure performance data to a model, at least one infrastructure performance prediction value that indicates predicted infrastructure performance of the pathway article at the future point in time.

This disclosure relates to a system and method for detecting vehicle events. Some or all of the system may be installed in a vehicle, operate at the vehicle, and/or be otherwise coupled with a vehicle. The system includes one or more sensors configured to generate output signals conveying information related to the vehicle. The system receives contextual information from a source external to the vehicle. The system detects a vehicle event based on the information conveyed by the output signals from the sensors and the received contextual information.

A system for executing functionally equivalent applications. The system includes a cloud system including a plurality of cloud instances, the plurality of cloud instances being set up in each case to execute a functionally equivalent application in each case based on the same input data, the respective execution including a processing of the input data by the respective application in order to output an application result in each case, and a comparison device, which is set up to compare the respective application results in order to ascertain a comparison result and to output the comparison result that has been ascertained. A method for executing functionally equivalent applications, a computer program, and a machine-readable storage medium, are also described.