An autonomous vehicle uses probabilistic neural networks to predict hidden context attributes associated with traffic entities. The hidden context represents behavior of the traffic entities in the traffic. The probabilistic neural network is configured to receive an image of traffic as input and generate output representing hidden context for a traffic entity displayed in the image. The system executes the probabilistic neural network to generate output representing hidden context for traffic entities encountered while navigating through traffic. The system determines a measure of uncertainty for the output values. The autonomous vehicle uses the measure of uncertainty generated by the probabilistic neural network during navigation.

A vehicle running control method includes: when a junction section lane is present adjacent to a traveling lane of a host vehicle, collecting, by a processor, vehicle information of at least one vehicle traveling in the junction section lane; determining, by the processor, the possibility of cut-in of junction section lane vehicles based on the collected vehicle information and whether the traveling lane is congested; and controlling, by the processor, at least one of the traveling path or the traveling velocity of the host vehicle based on the result of determination in order to display an intention to yield.

A power supply facility includes a wireless communication unit capable of wirelessly communicating with a plurality of electric vehicles traveling in line, a plurality of power supply coils installed at a predetermined interval, and an inter-vehicle calculation unit configured to acquire a plurality of pieces of information including power supply coil interval information indicating a distance of the predetermined interval, information on an entire length of a vehicle body of each of the plurality of electric vehicles, and information on a position of a power reception coil installed in each of the vehicle bodies, and calculate an inter-vehicle distance for leading each of the plurality of electric vehicles to be parked in accordance with the acquired plurality of pieces of information so as to align the plurality of power supply coils with the power reception coils to face each other.

The present disclosure relates to a driver controlling system for a vehicle, a vehicle comprising such a driver controlling system, a driver controlling method for a vehicle and a computer program element for such a driver controlling system.

The driver controlling system comprises a longitudinal control means, a lateral control means and a control unit. The longitudinal control means and the lateral control means are arrangeable in the vehicle. The control unit is configured to determine at least one of a longitudinal adjustment parameter and a later adjustment parameter to propel the vehicle in an automated mode. The control unit is configured to prompt the longitudinal control means to apply the longitudinal adjustment parameter of the vehicle and/or the lateral control means to apply the lateral adjustment parameter in the automated mode. The control unit is further configured to modify at least one of the longitudinal adjustment parameter and the lateral adjustment parameter to be applied in the vehicle by a defined rate of deviation for causing a reaction of the driver.

A vehicle for collecting image data of a target object for generating a classifier. The vehicle includes an image sensor and an electronic processor. The electronic processor is configured to determine a plurality of potential trajectories of the vehicle, determine, for each of the plurality of potential trajectories of the vehicle, a total number of views including the target object that would be captured by the image sensor as the vehicle moved along the respective trajectory, and determine a key trajectory of the vehicle from the plurality of potential trajectories based on the total number of views including the target of the key trajectory.

A control device of a display device that displays a traveling position of a predetermined vehicle relative to a preceding vehicle in platoon traveling, includes: a detector that detects a candidate preceding vehicle to follow from among one or more vehicles traveling around the predetermined vehicle; a calculator that calculates, with respect to the detected candidate preceding vehicle, a reduction effect of energy consumption obtained by the predetermined vehicle when the predetermined vehicle travels following the candidate preceding vehicle; and a controller that executes display control to display, on the display device, a recommended travel area based on the reduction effect of energy consumption as an area in which the predetermined vehicle is recommended to travel. Further, the recommended travel area is an area indicating a predetermined inter-vehicle distance behind the candidate preceding vehicle.

An apparatus and method for controlling driving of a vehicle are disclosed. The disclosed method includes: determining, by a determinator, whether smart cruise driving of a vehicle is performed; determining, by the determinator, whether a rear vehicle performs a lane change when the vehicle is in a smart cruise driving state; determining, by the determinator, a collision possibility based on whether the rear vehicle performs the lane change; determining, by the determinator, whether a front vehicle is present; based on the determined collision possibility; and calculating, by a controller, a target distance or a target speed when there is a front vehicle.

Among other things, we describe techniques for operation of a vehicle based on measured load characteristics and/or passenger comfort. One or more sensors of the vehicle can measure passenger data and/or load data of the vehicle. The passenger data and/or load data of the vehicle can be used by the vehicle to determine how to navigate within the surrounding environment.

A method of operating an autonomous vehicle includes detecting, based on an input received from a sensor of an autonomous vehicle that is being navigated by an on-board computer system, an occurrence of a driving event, making a determination by the on-board computer system, upon the detecting the occurrence of the driving event, whether or how to alter the path planned by the on-board computer system according to a set of rules, and performing further navigation of the autonomous vehicle based on the determination until the driving event is resolved. The driving event may include a presence of an object in a shoulder area of the road. The driving event may include accumulation of more than a certain number of vehicles behind the autonomous vehicle. The driving event may include a slow vehicle ahead of the autonomous vehicle. The driving event may include a do-not-change-lane zone is within a threshold.

A system for controlling platooning by a following vehicle includes a main body of the following vehicle. The system further includes a pressure sensor located in or on the main body and configured to detect a pressure corresponding to a pressure wake from a leading vehicle. The system further includes an electronic control unit (ECU) located in or on the main body, coupled to the pressure sensor, and configured to determine an optimal distance from the following vehicle to the leading vehicle based on the detected pressure. The optimal distance corresponding to a distance at which drag applied to the following vehicle is reduced based on the pressure wake from the leading vehicle.