A system for lateral adaptive cruise control for use in a vehicle includes a main body, a power source, and a brake. The system further includes an input device to receive an adaptive cruise control request. The system further includes an object sensor to detect lateral object data. The system further includes an ECU designed to determine a velocity of the lateral object or a relative distance to the lateral object based on the lateral object data, determine a lane entrance event corresponding to the lateral object traveling towards a current lane occupied by the main body based on the at least one of the velocity of the lateral object or the relative distance to the lateral object, and control at least one of the power source or the brake to adjust a current speed of the main body based on the lane entrance event.

An information processing device according to an embodiment includes one or more hardware processors. The processors generate a plurality of nodes at positions corresponding to an operation indicated by an avoidance pattern to avoid a first object on a first trajectory based on one or more avoidance patterns indicating one or more operations of a mobile object for avoiding an object. The processors search for a trajectory candidate whose moving cost is smaller than that of another trajectory candidate among a plurality of trajectory candidates connecting a plurality of nodes for each avoidance pattern. The processors select a trajectory candidate whose moving cost is smaller than that of another trajectory candidate from among one or more trajectory candidates searched for each avoidance pattern.

The present disclosure relates to a control apparatus and a control method of an adaptive cruise control system. The control apparatus of the adaptive cruise control system includes: an information collector configured to collect at least one of driving information about a host vehicle, information about an object positioned ahead of the host vehicle, and information about a road on which the host vehicle runs; a target selector configured to select a target vehicle based on the information about the object and to select a first driving route of the host vehicle based on the information about the road; a route corrector configured to generate a second driving route obtained by correcting the first driving route based on road structure information among the information about the road; an offset determinator configured to determine a lateral offset based on the second driving route and object information about the target vehicle; a target corrector configured to select the target vehicle as an ultimate target vehicle based on the lateral offset; and a signal outputter configured to output a control signal to avoid the ultimate target vehicle while the host vehicle runs on the second driving route.

A method for determining driving parameters includes: acquiring driving data of a driver; extracting driving features of the driver based on the driving data, where the driving features include first operation frequency of a first component of a vehicle and second operation frequency of a second component of the vehicle; determining, based on the driving features, a first probability that the driver has a first driving style and a second probability that the driver has a second driving style; and determining the driving parameters based on the first probability and the second probability, where the driving parameters include at least longitudinal acceleration and longitudinal deceleration. The method can dynamically adjust automated driving parameters to meet the driving style of the driver, thereby effectively improving user experience.

In order to provide a vehicle behavior prediction device and a vehicle behavior prediction method, and a driving assistance device that uses said vehicle behavior prediction device, which enables vehicle behavior to be predicted in a highly accurate manner, a vehicle control device is installed in a vehicle. This vehicle control device is provided with a distribution calculation unit and a vehicle behavior prediction unit. The distribution calculation unit determines, on the basis of driving condition information that has been collected, probability distributions for when deceleration behavior occurs and does not occur. The vehicle behavior prediction unit determines the relative positional relationships between the driving speed and acceleration of vehicles ahead with respect to the probability distributions, and, on the basis of the relative positional relationships that have been determined, predicts the behavior of a vehicle that is subject to prediction.

After determination of from which side, right or left, a second vehicle is approaching, a position of a collision point is determined, a position of a stop point is set from the determined collision point, and a warning is given at a position and timing of a warning point which is set to allow a first vehicle to stop before the set stop point.

According to an embodiment, there is provided a drive assist device including an index calculation unit configured to calculate an index relating to a relative relationship between a vehicle and a target object and a drive assist determination unit configured to determine whether to execute a drive assist control of the vehicle based on the index and as the vehicle width direction component of the relative speed between the vehicle and the target object decreases, the index calculation unit calculates the index with increasing a degree of influence of the relative relationship relating to the vehicle width direction component, or as the vehicle width direction component of the relative distance between the vehicle and the target object increases, the index calculation unit calculates the index with increasing the degree of influence of the relative relationship relating to the vehicle width direction component.

A vehicle control device executes a warning control for a driver when the driver is in an abnormal state, and executes a stop control for stopping an own vehicle when the abnormal state is continued for a predetermined time threshold or more from a time point at which the warning control is started. In a first period from a time point at which the warning control is started to a time point at which the stop control is started, the vehicle control device determines whether there is another vehicle behind the own vehicle, and when the control device determines that there is no other vehicle behind the own vehicle, a specific deceleration control that temporarily decelerates the own vehicle is executed.

The present invention obtains a processor and a processing method, a rider-assistance system, and a straddle-type vehicle capable of improving a rider's safety.

A processor (20) includes: an acquisition section that acquires surrounding environment information about straddle-type vehicle (100); a determination section that determines necessity of assistance operation executed by the rider-assistance system (1) to assist with the rider's operation; and a control section that makes an execution device (P) execute the assistance operation in the case where the determination section determines that the assistance operation is necessary. The determination section determines the necessity of the assistance operation by using a rear index value, which is an index value depending on information on the surrounding environment at the rear and is an index value of a collision possibility of an object located behind the straddle-type vehicle (100) against the straddle-type vehicle (100). The rear index value is a value that varies according to a relative distance and a relative speed of the object located behind to the straddle-type vehicle (100).

In a target track generation apparatus (10), a preceding vehicle position acquisition unit (1) acquires a relative position of a preceding vehicle. A subject vehicle state quantity acquisition unit (2) acquires a state quantity of a subject vehicle. A subject vehicle movement amount calculator (3) calculates a movement amount of the subject vehicle, based on the state quantity of the subject vehicle. A subject vehicle reference preceding vehicle position calculator (4) calculates a point group of subject vehicle reference preceding vehicle positions representing a history of the relative position of the preceding vehicle in a coordinate system using a current position of the subject vehicle as a reference, based on the relative position of the preceding vehicle and the movement amount of the subject vehicle. A target track generator (5) generates a target track of the subject vehicle, based on the point group of the subject vehicle reference preceding vehicle positions. A target track correction determination unit (6) determines whether or not correction of the target track is necessary, based on the point group of the subject vehicle reference preceding vehicle positions or the target track. A correction target track generator (7) generates a correction target track obtained by correcting the target track, based on the point group of the subject vehicle reference preceding vehicle positions or the target track, when it is determined that correction of the target track is necessary.