Disclosed herein are an apparatus and a method for autonomous vehicle negotiation based on Vehicle-to-Vehicle (V2V) communication, the method including requesting, by vehicles that enter a driving negotiation section, a driving negotiation token, acquiring, by a vehicle that enters the driving negotiation section first, among the entering vehicles, the driving negotiation token, performing driving negotiation based on whether the driving negotiation token is acquired, and returning, by a vehicle having acquired the driving negotiation token, the driving negotiation token when the vehicle arrives at a destination.

A processor is configured to execute instructions stored in a memory to determine, in response to identifying vehicle operational scenarios of a scene, an action for controlling the AV, where the action is from a selected decision component that determined the action based on level of certainty associated with a state factor; generate an explanation as to why the action was selected, such that the explanation includes respective descriptors of the action, the selected decision component, and the state factor; and display the explanation in a graphical view that includes a first graphical indicator of a world object of the selected decision component, a second graphical indicator describing the state factor, and a third graphical indicator describing the action.

Techniques are provided for autonomous vehicle operation using linear temporal logic. The techniques include using one or more processors of a vehicle to store a linear temporal logic expression defining an operating constraint for operating the vehicle. The vehicle is located at a first spatiotemporal location. The one or more processors are used to receive a second spatiotemporal location for the vehicle. The one or more processors are used to identify a motion segment for operating the vehicle from the first spatiotemporal location to the second spatiotemporal location. The one or more processors are used to determine a value of the linear temporal logic expression based on the motion segment. The one or more processors are used to generate an operational metric for operating the vehicle in accordance with the motion segment based on the determined value of the linear temporal logic expression.

In various examples, a yield scenario may be identified for a first vehicle. A wait element is received that encodes a first path for the first vehicle to traverse a yield area and a second path for a second vehicle to traverse the yield area. The first path is employed to determine a first trajectory in the yield area for the first vehicle based at least on a first location of the first vehicle at a time and the second path is employed to determine a second trajectory in the yield area for the second vehicle based at least on a second location of the second vehicle at the time. To operate the first vehicle in accordance with a wait state, it may be determined whether there is a conflict between the first trajectory and the second trajectory, where the wait state defines a yielding behavior for the first vehicle.

A vehicle configured to operate in an autonomous mode can obtain sensor data from one or more sensors observing one or more aspects of an environment of the vehicle. At least one aspect of the environment of the vehicle that is not observed by the one or more sensors could be inferred based on the sensor data. The vehicle could be controlled in the autonomous mode based on the at least one inferred aspect of the environment of the vehicle.

A system for an autonomous vehicle that predicts a location-based maneuver of a remote vehicle located in a surrounding environment includes one or more vehicle sensors collecting sensory data indicative of one or more vehicles located in the surrounding environment. The system also includes one or more automated driving controllers in electronic communication with the one or more vehicle sensors. The one or more automated driving controllers execute instructions to compare a lane of travel of the remote vehicle with a current lane of travel of the autonomous vehicle. In response to determining the lane of travel of the remote vehicle is a different lane than the current lane of the autonomous vehicle, the one or more automated driving controllers predict the location-based maneuver of the remote vehicle based on aggregated vehicle metrics that are based on historical data collected at the specific geographical location.

A driving assist method minimizes an incidence of lane changing within a circulatory roadway. In this driving assist method, a recognition assessment processor assesses the travel of a host vehicle, calculates a travel route over which the host vehicle is to travel, and executes a driving assist control based on the travel route. The recognition assessment processor further assesses whether the host vehicle has arrived at a roundabout having a circulatory roadway to which three or more radial roadways are connected. When an assessment has been made that the host vehicle has arrived at the roundabout, a position of a host vehicle entrance and a position of a host vehicle exit are specified. Furthermore, an entrance position is set based on a positional relationship between the host vehicle entrance and the host vehicle exit.

A driving assist device includes a driving assist controller. The driving assist controller is configured to perform driving assistance when the vehicle changes a course by crossing the oncoming lane. The driving assist controller sets a predicted travel region based on behavior of the oncoming vehicle when the oncoming vehicle is approaching the vehicle that enters an intersection. When the vehicle enters the predicted travel region in a travel path of the vehicle, the driving assist controller determines whether there is a possibility of contact between the vehicle and the oncoming vehicle based on the predicted travel region and the travel path of the vehicle. The driving assist controller causes the vehicle to stop outside of the predicted travel region when there is a possibility of the contact.

A driving assist device includes a driving assist controller. The driving assist controller includes an oncoming vehicle detection unit, a prediction determination unit, a predicted travel region setting unit and a stop controller. The oncoming vehicle detection unit is configured to, when a vehicle enters an intersection, determine whether an oncoming vehicle going to enter the intersection is present. The prediction determination unit is configured to, when the oncoming vehicle detection unit determines that the oncoming vehicle is going to enter the intersection, determine whether a course of the oncoming vehicle is predictable based on vehicle behavior of the oncoming vehicle. The predicted travel region setting unit is configured to set a predicted travel region of the oncoming vehicle based on the vehicle behavior. The stopping controller is configured to cause the vehicle to stop outside of the predicted travel region set by the predicted travel region setting unit.

A driver assistance device acquires information about vehicle-driving environment ahead of the vehicle to detect an intersection. Upon determining that the vehicle makes a right- or left-hand turn at the intersection, the driver assistance device sets a projected course of the vehicle and recognizes a moving object ahead in a direction in which the vehicle making a right- or left-hand turn is headed. The driver assistance device calculates a movement vector from positional changes of the moving object to calculate a meeting point of a path of the object and the projected course. When an interval between times at which the vehicle and the moving object reach the meeting point is found to fall within a predetermined range, the driver assistance device determines that there is a possibility of interference between the vehicle and the moving object and then causes the vehicle to halt short of the meeting point.