A method for steering a vehicle along a path in a driveway and around obstacles between a starting position into a target position, comprises the steps of determining the vehicle dimensions, steering and driving capabilities, carrying out a path optimization step to evaluate, based on a predetermined cost function, the least costly path between the starting position and the target position avoiding any collisions with obstacles. The method further comprises the further step of applying a path improver step, smoothening the trajectory obtained by the path optimization method by means of numerical optimization while fulfilling dynamical constraints on acceleration and steering rate of the vehicle through planning lateral and longitudinal movement of the vehicle in a joint optimization problem or by means of separate optimization problems.

The traffic flow control method includes: receiving, by a traffic flow control device, traffic control request signaling sent by an in-vehicle device of a first vehicle, where the traffic control request signaling includes travel information of the first vehicle and a travel intention of the first vehicle; determining, by the traffic flow control device, traffic command signaling based on the traffic control request signaling and traffic control phase information of a target intersection, where the target intersection is an intersection through which the first vehicle is to pass; and sending, by the traffic flow control device, the traffic command signaling to the in-vehicle device of the first vehicle. The traffic flow control method, the traffic flow control device, the in-vehicle device, and the computer-readable storage medium in the internet of vehicles can help a vehicle in the internet of vehicles travel safely and efficiently at an intersection.

In one embodiment, a cognitive load driving assistant increases driving safety based on cognitive loads. In operation, the cognitive load driving assistant computes a current cognitive load of a driver based on sensor data. If the current cognitive load exceeds a threshold cognitive load, then the cognitive load driving assistant modifies the driving environment to reduce the cognitive load required to perform the primary driving task and/secondary task(s), such as texting via a cellular phone. The cognitive load driving assistant may modify the driving environment indirectly via sensory feedback to the driver or directly through reducing the complexity of the primary driving task and/or secondary tasks. In particular, if the driver is exhibiting elevated cognitive loads typically associated with distracted driving, then the cognitive load driving assistant modifies the driving environment to allow the driver to devote appropriate mental resources to the primary driving task, thereby increasing driving safety.

A setting device including a processor is provided. The processor is configured to, when occurrence of a secondary disaster is predicted after occurrence of a disaster, set a region in which the secondary disaster is predicted to a charging-prohibited zone in which use of a charging facility for charging a battery installed in a vehicle is prohibited.

A traffic signal recognition method and a traffic signal recognition device acquire a result sequence consisting of a plurality of determination results in time-series order obtained by determining a display state of a traffic signal based on a plurality of images of a traveling direction of a vehicle, set a first threshold as a number threshold if a specific determination result which is a latest determination result among the determination results is a determination result of a permission display that allows a passage of the stop line corresponding to the traffic signal, set a second threshold smaller than the first threshold as the number threshold if the specific determination result is other than a determination result of the permission display, and output the specific determination result if a number of determination results identical to the specific determination result is greater than the number threshold.

The refueling vehicle routing system can use a refueling vehicle routing application to compute a set of fuel delivery routes for a fleet of refueling vehicles for multiple different target vehicles to be serviced via cooperating with a refueling scenario simulator. The refueling scenario simulator can run scenarios of different sets of refueling routes to refuel target vehicles in light of an available set of assets, and then the application can supply results of how the versions of the set of refueling routes for the fleet of refueling vehicles are going to satisfy anticipated refueling needs for the target vehicles; to indicate any refueling stops that could be late, early, and/or missed entirely, for a service window of time; as well as to show a measure of how cost effective each of the refueling routes are at the satisfying of the needs for the target vehicles.

A roadway complexity awareness system for a vehicle, comprising a processor, an augmented reality interface disposed in communication with the processor, and a memory for storing executable instructions. The processor is programmed to execute the instructions to receive roadway status information from an infrastructure processor associated with a roadway, obtain, from a vehicle sensory system, sensory information indicative of roadway route complexity, and determine a likelihood of roadway route complexity based on the roadway status information and the sensory information. The system may select an augmented reality message indicative of the roadway route complexity, and generate the augmented reality message using an augmented reality interface device, wherein the augmented reality message is visible to a vehicle operator.

The disclosure provides for systems and methods for communicating messages from one vehicle to another vehicle. An input device, such as a cell phone, can be configured to generate and transmit a signal that corresponds with a message to an output device for display of messages. The messages can be displayed in a rearward direction, allowing drivers to communicate with vehicles located behind them on a roadway.

A work vehicle guidance display system comprising: at least one imaging device disposed on a work vehicle; a display disposed in the work vehicle configured to display images from the imaging device; and a controller configured to: select a field of view of the imaging device to display; receive a static dimension associated with the work vehicle; receive a dynamic dimension associated with the work vehicle; and display on the display a field view with a first machine travel path based on the static dimension and a second machine travel path based on the dynamic dimension.

One or more processors may be configured to determine one or more prospective routes of an ego vehicle being at least partially controlled by a human driver; receive first sensor data, representing one or more attributes of a second vehicle; determine a danger probability of the one or more prospective routes of the first vehicle using the at least the one or more attributes of the second vehicle from the first sensor data; and if each of the one or more prospective routes of the first vehicle has a danger probability outside of a predetermined range, send a signal representing a safety intervention. Whenever a safety intervention signal is sent, the one or more processors may be configured to increment or decrement a counter.