An apparatus for forward collision avoidance assist-junction turning of a vehicle includes a sensor for acquiring at least one of a steering angle, a steering angle speed, or a yaw rate of a vehicle, or a size, a position, or a speed of an opposite target. A traveling path area for a left-turn or a right-turn is calculated by a controller based on the steering angle or the yaw rate of the vehicle. The traveling path area is then corrected by the controller based on at least a portion of the steering angle, the steering angle speed, or the yaw rate of the vehicle, or the size, the position, and the speed of the opposite target. A warning against the collision between the vehicle and the opposite target and a control operation to prevent the collision are performed based on the corrected traveling path area.

A vehicle drive assist apparatus for a vehicle includes a surrounding-condition-information acquiring unit that acquires surrounding condition information, a vehicle-state-information acquiring unit that acquires vehicle state information, a traveling control processor that executes traveling control in accordance with traffic lane designation, a DDI detector, and a control switch. The DDI detector detects a DDI in a front region of the vehicle on the basis of the surrounding condition information and determines whether the vehicle is entering or exiting from the DDI on the basis of the surrounding condition information and the vehicle state information. The control switch switches the traveling control from standard traveling control to non-standard traveling control when the vehicle entering the DDI is detected, and from the non-standard traveling control to the standard traveling control when the vehicle exiting from the DDI is detected on the basis of the result of the DDI determination.

A vehicle drive assist apparatus includes a surrounding-condition-information acquiring unit that acquires surrounding condition information, a vehicle-state-information acquiring unit that acquires vehicle state information, a light-distribution control processor that executes light distribution control, a traveling control processor that executes traveling control in accordance with traffic lane designation, a DDI detector that detects a DDI in a front region based on the surrounding condition information and determines whether the vehicle is entering or exiting from the DDI based on the surrounding condition information and the vehicle state information, and a control switch. When the vehicle entering the DDI is detected, the control switch switches the traveling control and the light distribution control from standard traveling control to non-standard traveling control. When the vehicle exiting from the DDI is detected, the control switch switches the traveling control and the light distribution control from the non-standard traveling control to the standard traveling control.

Aspects of the disclosure relate to determining whether a feature of map information. For example, data identifying an object detected in a vehicle's environment and including location coordinates is received. This information is used to identify a corresponding feature from pre-stored map information based on a map location of the corresponding feature. The corresponding feature is defined as a curve and associated with a tag identifying a type of the corresponding object. A tolerance constraint is identified based on the tag. The curve is divided into two or more line segments. Each line segment has a first position. The first position of a line segment is changed in order to determine a second position based on the location coordinates and the tolerance constraint. A value is determined based on a comparison of the first position to the second position. This value indicates a likelihood that the corresponding feature has changed.

A vehicle control device includes a crossing vehicle detection sensor configured to detect a crossing vehicle approaching an own vehicle while the own vehicle is traveling in an intersecting lane, the intersecting lane being a lane that intersects an own vehicle lane at an intersection at a time the own vehicle approaches the intersection, the crossing vehicle being a vehicle travelling in the intersecting lane; and a controller configured to automatically brake the own vehicle to avoid a collision between the own vehicle and the crossing vehicle under a condition that the own vehicle enters the intersecting lane. The controller is configured to set, between the own vehicle and the crossing vehicle, a virtual area that moves with the crossing vehicle and that extends in an advancing direction of the crossing vehicle, and automatically brake the own vehicle to prevent the own vehicle from contacting the virtual area.

There is disclosed a control system and a method for a host vehicle operable in an autonomous mode. The control system comprises one or more controllers. The speed and/or path of the vehicle in the autonomous mode is appropriate to a driving context.

A travel path data generation apparatus includes an intersection feature data generator that, by using data of travel paths outside intersections, generates intersection feature data representing features of the intersections and a sample data generator that associates the intersection feature data with motion trajectory data showing actual motion trajectories of vehicles inside intersections and generates sample data serving as samples of association between the feature of the intersection and the actual motion trajectories inside the intersection; and a travel path data generator that searches the sample data for the sample that to corresponds to specific intersection feature data representing a feature of a given intersection; specifies the motion trajectory data associated with the specific intersection feature data; and provides the specified motion trajectory data as data of travel paths inside intersections that corresponds to the given intersection.

Systems and methods described herein relate to estimating risk associated with a vehicular maneuver. One embodiment acquires a geometric representation of an intersection including a lane in which a vehicle is traveling and at least one other lane; discretizes the at least one other lane into a plurality of segments; determines a trajectory along which the vehicle will travel; estimates a probability density function for whether a road agent external to the vehicle is present in the respective segments; estimates a traffic-conflict probability of a traffic conflict in the respective segments conditioned on whether an external road agent is present; estimates a risk associated with the vehicle following the trajectory by integrating a product of the probability density function and the traffic-conflict probability over the at least one other lane and the plurality of segments; and controls operation of the vehicle based, at least in part, on the estimated risk.

To operate an autonomous vehicle, a rail agent is detected in a vicinity of the autonomous vehicle using a detection system. One or more tracks are determined on which the detected rail agent is possibly traveling, and possible paths for the rail agent are predicted based on the determined one or more tracks. One or more motion paths are determined for one or more probable paths from the possible paths, and a likelihood for each of the one or more probable paths is determined based on each motion plan. A path for the autonomous vehicle is then determined based on a most probable path associated with a highest likelihood for the rail agent, and the autonomous vehicle is operated using the determined path.

A vehicle control device includes an oncoming vehicle detection sensor and a controller that automatically applies brakes to avoid a collision with the oncoming vehicle, under a condition that the own vehicle is at least partially in an opposite lane or a planned path of the own vehicle is at least partially in the opposite lane. The controller sets a virtual area that moves with the oncoming vehicle and that extends in an advancing direction of the oncoming vehicle, and automatically brakes to avoid to avoid a collision. In response to the sensor detecting first and second oncoming vehicles, the controller sets first and second virtual areas, and automatically brakes the own vehicle to prevent coming into contact with the first virtual area and the second virtual area once the own vehicle traverses the opposite lane.