The present disclosure relates to an overtaking estimating system for estimation of a minimum overtaking speed of a vehicle. The overtaking estimating system determines in view of a host vehicle a remaining distance of an overtaking lane contiguous to a driving lane of the host vehicle. The system further determines a delta distance between the host vehicle and a preceding vehicle positioned in the host vehicle driving lane. Moreover, the system determines a delta time for the host vehicle to reach the preceding vehicle. The system further determines, based on the delta distance, the delta time and a determined host vehicle speed, a speed of the preceding vehicle. Furthermore, the system determines, based on the remaining distance, the delta distance, the preceding vehicle speed, and an overtaking-affecting parameter, a minimum overtaking speed of the host vehicle for overtaking the preceding vehicle in the remaining distance of the overtaking lane.

A system and method for controlling an autonomous vehicle to affect a view seen by an occupant of the autonomous vehicle is described. In one embodiment, a method for controlling an autonomous vehicle to affect a view seen by an occupant of the autonomous vehicle includes determining a navigation route, determining content associated with the navigation route, monitoring current conditions of the autonomous vehicle and the occupant, determining, based on the current conditions, whether to change a position of the vehicle to affect the view seen by the occupant, and when the current conditions permit, moving the autonomous vehicle to affect the view seen by the occupant.

A vehicle control system includes a vehicle estimator and a stop position setter. The vehicle estimator is configured to make determination on whether an entering vehicle entering an oncoming lane from an intersecting road is present, and estimate an overall length of the entering vehicle upon determining that the entering vehicle is present. The intersecting road intersects a traveling road where a vehicle to which the vehicle control system is applied is traveling. The stop position setter is configured to set a stop position of the vehicle based on the determination made by the vehicle estimator as to whether the entering vehicle is present and the estimated overall length of the entering vehicle.

A vehicle control device includes: a storage portion in which map information is stored, the map information showing a position where a roadside machine configured to transmit a radio signal including predetermined information is provided; a route setting portion configured to set a route where an autonomous driving vehicle is to travel when a current position, of the autonomous driving vehicle, that is measured by a positioning portion provided in the autonomous driving vehicle is included within a predetermined distance from the position of the roadside machine on the map information and the autonomous driving vehicle approaches the position where the roadside machine is provided, the route being set so that a communication portion provided in the autonomous driving vehicle can receive the radio signal; and a vehicle controlling portion configured to control the autonomous driving vehicle so that the autonomous driving vehicle travels along the route.

An autonomous vehicle can obtain sensor data. Upon determining that the autonomous vehicle is in a lane adjacent a shoulder, and there is an object in the shoulder, the autonomous vehicle can determine if performing a lane change maneuver out of the lane prior to the autonomous vehicle being positioned adjacent to the object is feasible. If it is, the lane change maneuver can be performed. If it is not, a nudge maneuver and/or a deceleration can be performed.

A processor unit (3) is configured for accessing speed data of a second vehicle (18), the speed data generated by a sensor of a first vehicle (1). The processor unit is also configured for creating a driving behavior profile of the second vehicle (18) based on the speed data and making a prediction about the future driving behavior of the second vehicle (18) based on the driving behavior profile of the second vehicle (18). Moreover, the processor unit is configured for determining a trajectory for the first vehicle (1) by executing an MPC algorithm, which includes a longitudinal dynamic model of the first vehicle and a cost function, such that the cost function is minimized. The prediction about the future driving behavior of the second vehicle (18) is taken into account in the determination of the trajectory.

A computer-implemented method of determining a series of control signals for controlling an autonomous vehicle to implement a planned speed change maneuver comprises: receiving from a maneuver planner a position target for the planned speed change maneuver; selecting, from a predetermined family of kinematic functions, a kinematic function for carrying out the planned speed change maneuver, each kinematic function being a first or higher order derivative of acceleration with respect to time; and using the selected kinematic function to determine a series of control signals for implementing the planned speed change maneuver; wherein the kinematic function is selected in a constrained optimization process as substantially optimizing a cost function defined for the speed change maneuver, subject to a set of hard constraints that: (i) require a final acceleration, speed and position corresponding to the selected kinematic function to satisfy, respectively, an acceleration target, a speed target and the position target, given an initial speed and acceleration of the autonomous vehicle, and (ii) impose a jerk magnitude upper limit on the selected kinematic function.

The present invention obtains a controller and a control method capable of improving safety of adaptive cruise operation in a motorcycle.

In the controller for operation of the motorcycle, to which a surrounding environment detector is mounted, an adaptive cruise operation performing section controls deceleration to be generated by the motorcycle in adaptive cruise operation to be equal to or lower than an upper limit value or to be lower than the upper limit value, determines a collision possibility of the motorcycle on the basis of the upper limit value during the adaptive cruise operation, and performs warning operation that acts on a tactile organ of a rider of the motorcycle when determining that the collision possibility is high.

In a preferred example embodiment of the present disclosure, a multi-agent control system includes: a malfunctioning-agent detector configured to detect a malfunctioning agent among a plurality of agents based on a malfunction signal received from each of the plurality of agents; and a multi-agent controller configured to control a neighboring agent around the malfunctioning agent to transmit a correction control signal to the malfunctioning agent such that the plurality of agents operate in a platoon.

A controller causes a host vehicle to decelerate when a velocity of an oncoming vehicle corresponding to a position of the oncoming vehicle distant from a stationary object by a predetermined distance is greater than or equal to a velocity threshold corresponding to the position of the oncoming vehicle distant from the stationary object by the predetermined distance in a case in which a passing position is present within a predetermined region, and causes the host vehicle to keep the velocity or accelerate when the velocity of the oncoming vehicle corresponding to the position of the oncoming vehicle distant from the stationary object by the predetermined distance is less than the velocity threshold corresponding to the position of the oncoming vehicle distant from the stationary object by the predetermined distance in the case in which the passing position is present within the region.