Disclosed herein are system, method, and computer program product embodiments for switching between local and remote guidance instructions for autonomous vehicles. For example, the method includes, in response to monitoring one or more actions of objects detected in a scene in which the autonomous robotic system is moving, causing the autonomous robotic system to slow or cease movement in the scene. The method includes detecting a trigger condition based on movement of the autonomous robotic system in the scene. In response to the one or more monitored actions and detecting the trigger condition, the method includes transmitting a remote guidance request to a remote server. After transmitting the remote guidance request, the method includes receiving remote guidance instructions from the remote server and causing the autonomous robotic system to begin operating according to the remote guidance instructions.

A vehicle running control method includes: calculating, by a controller, a lateral velocity of an adjacent vehicle that travels in a lane adjacent to a traveling lane in which an autonomous vehicle travels in the road-width direction, and a longitudinal velocity of the adjacent vehicle in the direction in which the adjacent lane extends; specifying, by the controller, a predetermined road section based on the longitudinal velocity and calculating a first path on the assumption that an offset distance of the adjacent vehicle in the adjacent lane in the road-width direction is maintained within the road section; and applying, by the controller, the lateral velocity to the first path to calculate a second path corresponding to a predicted traveling path of the adjacent vehicle.

A control system includes a controller configured to determine a target speed between a first target position of a haul vehicle relative to a harvester and a second target position of the haul vehicle relative to the harvester based on a flow rate of agricultural product through a conveyor of the harvester. The haul vehicle is coupled to a storage compartment, an outlet of the conveyor is aligned with a first unloading point within the storage compartment while the haul vehicle is positioned at the first target position, and the outlet of the conveyor is aligned with a second unloading point within the storage compartment while the haul vehicle is positioned at the second target position. Furthermore, the controller is configured to output a control signal indicative of instructions to direct the haul vehicle from the first target position to the second target position at the target speed.

A control requirement determiner includes: a storage that stores at least one piece of location information and at least one piece of behavior information as past data in which the location information and the behavior information are associated with each other, the location information indicating a geographic location, the behavior information being related to a behavior exhibited by a vehicle body of a vehicle at the location indicated by the location information when the vehicle traveled in the past; and processing circuitry that determines, based on the behavior information associated with the location information of the past data, a control requirement to be imposed on a control target of a rough terrain vehicle at the location indicated by the location information of the past data during travel of the rough terrain vehicle.

When executing the autonomous lane change control of lane change of the subject vehicle from the subject vehicle lane in which the subject vehicle travels to adjacent lane, the autonomous lane change control is executed so as to accelerate the lateral speed of the subject vehicle in the subject vehicle lane and thereafter decelerate the lateral speed in the subject vehicle lane. As a result, it takes longer for the driver of the following vehicle to confirm the lateral movement of the preceding subject vehicle during the lane change of the subject vehicle from the start of the lane change than a lane change in which the lateral speed is decelerated in the adjacent lane. Therefore, it becomes easier to recognize the lane change.

A driver assistance system plans movement for a motor vehicle, wherein a safe state of the motor vehicle is a state of the motor vehicle in a first time step from which the motor vehicle can be transferred, as a function of a movement capability of the motor vehicle in at least one second time step which follows the first time step, into a further safe state without colliding with a road user. The driver assistance system is configured to determine for at least one future time step starting from a current state of the motor vehicle, at least one possible future state of the motor vehicle and of the road user, and to select safe future states of the motor vehicle from the possible future states of the motor vehicle and of the road user, and to plan a movement for the motor vehicle as a function of the safe future states.

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.

Provided is an apparatus for providing obstacle information and reliability information to vehicle based on information received from roadside units. The apparatus includes a communication module that receives obstacle information from multiple roadside units, each roadside unit including multiple sensors for detecting obstacles within a predetermined field of view. A reliability judgement unit in the apparatus determines a reliability of the received obstacle information to output a reliability value based on a number of roadside units detecting a same obstacle, a number of sensor of one roadside unit detecting a same obstacle, and a difference value of detection of the same obstacle between different roadside units or different sensors.

Example embodiments relate to a method for cut-in identification and classification. An example embodiment includes a obtaining operational data about one or more vehicles; based on the operational data, identifying the presence of one or more cut-ins within the operational data; extracting, from the operational data, cut-in data that depicts one or more of the cut-ins identified within the operational data; and, based on the extracted cut-in data, training a model for controlling an autonomous vehicle. Identifying the presence of a given cut-in includes: determining that at least one vertex of a bounding box surrounding a vehicle was located more than a threshold distance within a lane being navigated by a given vehicle; and determining that the ability of the given vehicle to maintain its course and speed was impeded by the presence of the particular additional vehicle within the lane.

Provided are methods for motion planner constraint generation based on road surface hazards, which can include receiving information about an object, identifying the object as a particular road hazard, generating one or more motion constraints based on the road hazard, and controlling a vehicle based on the motion constraints. Systems and computer program products are also provided.