Systems and methods use cameras to provide autonomous navigation features. In one implementation, a method for navigating a user vehicle may include acquiring, using at least one image capture device, a plurality of images of an area in a vicinity of the user vehicle; determining from the plurality of images a first lane constraint on a first side of the user vehicle and a second lane constraint on a second side of the user vehicle opposite to the first side of the user vehicle; enabling the user vehicle to pass a target vehicle if the target vehicle is determined to be in a lane different from the lane in which the user vehicle is traveling; and causing the user vehicle to abort the pass before completion of the pass, if the target vehicle is determined to be entering the lane in which the user vehicle is traveling.

A cruise control device 10 includes a cutting-in/deviation determination unit 12 for performing cutting-in determination and deviation determination of another vehicle. The cutting-in/deviation determination unit 12 calculates a lateral position that is a position in a vehicle width direction of a forward vehicle 51 traveling ahead of an own vehicle 50, and determines the forward vehicle 51 traveling on an adjacent lane 64 to be a cutting-in vehicle into an own lane 63 and determines the forward vehicle 51 traveling on the own lane 63 to be a deviating vehicle from the own lane 63 on the basis of the calculated lateral position. The cutting-in/deviation determination unit 12 determines whether or not the own vehicle 50 is in a predetermined own vehicle turning state that is either one of a state before starting a turn or a state of turning, and determines permission of performing of cutting-in determination and deviation determination of the other vehicle on the basis of the determination result.

A method of operating a vehicle, such as an autonomous vehicle, includes the steps of receiving a message from roadside infrastructure via an electronic receiver and providing, by a computer system in communication with said electronic receiver, instructions based on the message to automatically implement countermeasure behavior by a vehicle system. Additionally or alternatively, the method may include the steps of receiving a message from another vehicle via an electronic receiver and providing, by a computer system in communication with said electronic receiver, instructions based on the message to automatically implement countermeasure behavior by a vehicle system.

According to one aspect, systems and techniques for lane selection may include receiving a current state of an ego vehicle and a traffic participant vehicle, and a goal position, projecting the ego vehicle and the traffic participant vehicle onto a graph network, where nodes of the graph network may be indicative of discretized space within an operating environment, determining a current node for the ego vehicle within the graph network, and determining a subsequent node for the ego vehicle based on identifying adjacent nodes which may be adjacent to the current node, calculating travel times associated with each of the adjacent nodes, calculating step costs associated with each of the adjacent nodes, calculating heuristic costs associated with each of the adjacent nodes, and predicting a position of the traffic participant vehicle.

Aspects of the disclosure relate to testing predictions of an autonomous vehicle relating to another vehicle or object in a roadway. For instance, one or more processors may plan to maneuver the autonomous vehicle to complete an action and predict that the other vehicle will take a responsive action. The autonomous vehicle is then maneuvered towards completing the action in a way that would allow the autonomous vehicle to cancel completing the action without causing a collision between the first vehicle and the second vehicle, and in order to indicate to the second vehicle or a driver of the second vehicle that the first vehicle is attempting to complete the action. Thereafter, when the first vehicle is determined to be able to take the action, the action is completed by controlling the first vehicle autonomously using the determination of whether the second vehicle begins to take the particular responsive action.

Systems and methods for controlling an autonomous vehicle are provided. In one example embodiment, a computer-implemented method includes obtaining sensor data indicative of a surrounding environment of the autonomous vehicle, the surrounding environment including one or more occluded sensor zones. The method includes determining that a first occluded sensor zone of the occluded sensor zone(s) is occupied based at least in part on the sensor data. The method includes, in response to determining that the first occluded sensor zone is occupied, controlling the autonomous vehicle to travel clear of the first occluded sensor zone.

Specifications are input, comprising: a plurality of lanes in an environment for a controlled system; a plurality of lane maneuvers associated with the plurality of lanes; a plurality of lane subconditions associated with the controlled system; and a rule set comprising a plurality of rules, wherein a rule in the rule set specifies a rule condition and a rule action to take when the rule condition is satisfied, wherein the rule condition comprises a corresponding set of lane subconditions, and wherein the rule action comprises a corresponding lane maneuver. The controlled system is automatically navigated dynamically, at least in part by: monitoring the plurality of lane subconditions; evaluating rule conditions associated with the plurality of rules in the rule set to determine one or more rules whose corresponding rule conditions has been met; and executing one or more lane maneuvers that correspond to the one or more determined rules.

Systems and methods are provided for predicting blind spot incursions for a host vehicle. In one implementation, a navigation system for a host vehicle may comprise a processor. The processor may be programmed to receive, from an image capture device located on a rear of the host vehicle, at least one image representative of an environment of the host vehicle. The processor may be programmed to analyze the at least one image to identify an object in the environment of the host vehicle and to determine kinematic information associated with the object. The processor may further be programmed to predict, based on the kinematic information, that the object will travel in a region outside of a field of view of the image capture device and perform a control action based on the prediction.

A vehicle may transmit, to a network entity, a lane use request message associated with a lane for the vehicle. The network entity may identify lane information associated with a lane for a vehicle. The network entity may identify vehicle information associated with the vehicle. The network entity may transmit, to the vehicle, and the vehicle may receive, from the network entity, a lane use grant message based on at least one of the identified lane information or the identified vehicle information. The lane use grant message may be indicative of a permission for the vehicle to use the lane. The vehicle may not be permitted to use the lane without the permission. The lane may correspond to a flexible direction lane, an emergency lane, a road shoulder, an HOV lane, or a passing lane.

An example method of providing an at least partially automatic driving function and/or a personalized function in a motor vehicle as well as to the motor vehicle may include establishing a communication link between a communication interface of the motor vehicle and a communication interface of a mobile terminal, which is associated with a user of the motor vehicle; receiving terminal data transferred via the communication link in the motor vehicle, which is recorded on the mobile terminal and which describes at least navigation information and/or user information relating to the user; and providing an at least partially automatic driving function of a driver assistance system of the motor vehicle and/or a personalized function in the motor vehicle by evaluating the received terminal data.