A vehicle control method includes recognizing a periphery of a vehicle, a first vehicle and a second vehicle present in the periphery, setting a target area between the first vehicle and the second vehicle based on a reference position of a first type of the first vehicle present in a lane of a lane change destination and a reference position of the first type of the second vehicle behind the first vehicle and present in the lane, and controlling the vehicle to enter the target area set based on a reference position of a second type of the first vehicle and a reference position of the second type of the second vehicle.

A vehicle control method of an autonomous vehicle for a right and left turn at a crossroad includes: determining whether a second vehicle intends to change a lane while passing a front or a rear of a first vehicle in order to move to a target lane for the right and left turn at the crossroad; controlling the first vehicle to decelerate when it is determined that the second vehicle intends to change the lane while passing the front of the first vehicle; determining whether the second vehicle is entering the first lane toward the front or the rear of the first vehicle; calculating a steering amount of the second vehicle when it is determined that the second vehicle is entering the first lane toward the front of the first vehicle; and controlling the first vehicle to decelerate according to the steering amount.

A roadmanship system comprises a computational device and a vehicle comprising a plurality of sensors and a vehicle control system in communication with the computational device and the plurality of sensors. The computational device can be configured to: (i) receive driving data from a group of vehicles; (ii) calculate a regression curve based on the driving data; (iii) calculate a threshold value of an engineering parameter based on the regression curve and a predetermined roadmanship level; and (iv) output the threshold value to the vehicle control system. The vehicle control system can be configured to: (a) receive the threshold value from the computational device; (b) receive operational information associated with at least one of the vehicle and a driving environment surrounding the vehicle from the plurality of sensors; and (c) cause the vehicle to perform a vehicle maneuver based on the threshold value and the operational information.

A vehicle control device, a vehicle control method, and a vehicle control system according to the present invention obtain an inter-vehicle time based on a relative distance between a first vehicle traveling, in front of an own vehicle, in a second lane adjacent to a first lane in which the own vehicle travels and a second vehicle traveling in the second lane in front of the first vehicle and based on a relative velocity of the first vehicle relative to the second vehicle, obtain a relative acceleration of the first vehicle relative to the second vehicle, set the first vehicle as a high-stress vehicle based on a lane change space that is based on the inter-vehicle time, the relative acceleration, and a relative distance between the second vehicle and a third vehicle traveling in the first lane in front of the own vehicle, and output a control command for changing a driving state of the own vehicle based on a relative distance between the high-stress vehicle and the own vehicle. This makes it possible to improve the driving safety of a vehicle on a road with multiple lanes in each direction.

A traffic congestion determination unit is configured to determine whether a traffic congestion occurs in an automatic travel period in which the vehicle travels by an automatic driving function. A cut-in prediction unit is configured to detect a sign of cut-in of an adjacent vehicle, which is adjacent to a subject vehicle as the vehicle, on determination by the traffic congestion determination unit that a traffic congestion occurs. A provision restricting unit is configured to restrict display of content provided in the automatic travel period on detection of a sign of cut-in of the adjacent vehicle by the cut-in prediction unit.

Techniques to predict object behavior in an environment are discussed herein. For example, such techniques may include inputting data into a model and receiving an output from the model representing a discretized representation. The discretized representation may be associated with a probability of an object reaching a location in the environment at a future time. A vehicle computing system may determine a trajectory and a weight associated with the trajectory using the discretized representation and the probability. A vehicle, such as an autonomous vehicle, can be controlled to traverse an environment based on the trajectory and the weight output by the vehicle computing system.

Traveling environment information is recognized. A predicted traveling path is calculated based on a driving condition of a vehicle. An oncoming-vehicle predicted traveling path is calculated based on behavior of an oncoming vehicle. It is determined whether the vehicle has an intention to enter a first intersecting road at an intersection. When the vehicle cannot enter the first intersecting road, the predicted traveling path is corrected to a limit traveling path. It is determined whether the oncoming vehicle has an intention to enter a second intersecting road at the intersection. When the oncoming vehicle cannot enter the second intersecting road, the oncoming-vehicle predicted traveling path is corrected to an oncoming-vehicle limit traveling path. The oncoming vehicle is set as a control target against which emergency braking is executed when the predicted traveling path and the oncoming-vehicle predicted traveling path overlap each other at least in part.

An indication of an intention of making a lane change to an adjacent lane that is issued from a preceding vehicle that travels in the same lane as an own vehicle is sensed while causing the own vehicle to travel while following the preceding vehicle. When the indication of the intention of making the lane change is sensed, deviation of the preceding vehicle toward the adjacent lane from an occupied region that is occupied by the own vehicle in traveling in the lane is sensed. Then, when deviation of the preceding vehicle from the occupied region is sensed, acceleration suppression for causing the own vehicle to travel while following the preceding vehicle is canceled.

An assistance system for a vehicle capable of automated operation has a controller having a processor and tangible, non-transitory memory on which instructions are recorded. The vehicle is located on a first lane in a vicinity of one or more neighboring vehicles, the first lane merging with a second lane at a merging trajectory location. The controller is adapted to selectively execute a leader determination module when a distance of the vehicle to the merge starting point is less than a threshold value. This includes determining an estimated arrival time of the vehicle to a merge starting point of the merging trajectory location. The controller is adapted to select a leader vehicle from the neighboring vehicles based in part on their respective estimated arrival times to the merge starting point. Operation of the vehicle is controlled based in part on the leader vehicle.

The present disclosure relates to an autonomous vehicle, a station system, and a door control method for the autonomous vehicle. An exemplary embodiment of the present disclosure provides an autonomous vehicle, comprising a processor configured to control opening and closing of a door of the autonomous vehicle depending on existence of an object around the door of the autonomous vehicle and whether an object outside and inside a station reaches a boarding zone of the autonomous vehicle within a predetermined time when the autonomous vehicle is stopped, and a storage configured to store data and algorithms driven by the processor.