Techniques for determining an uncertainty metric associated with an object in an environment can include determining the object in the environment and a set of candidate trajectories associated with the object. Further, a vehicle, such as an autonomous vehicle, can be controlled based at least in part on the uncertainty metric. The vehicle can determine a traversed trajectory associated with the object and determine a difference between the traversed trajectory and the set of candidate trajectories. Based on the difference, the vehicle can determine an uncertainty metric associated with the object. In some instances, the vehicle can input the traversed trajectory and the set of candidate trajectories to a machine-learned model that can output the uncertainty metric.

The technology relates to controlling a vehicle in an autonomous driving mode in accordance with behavior predictions for other road users in the vehicle's vicinity. In particular, the vehicle's onboard computing system may predict whether another road user will perform a “continuing” lane driving operation, such as going straight in a turn-only lane. Sensor data from detected/observed objects in the vehicle's nearby environment may be evaluated in view of one or more possible behaviors for different types of objects. In addition, roadway features, in particular whether lane segments are connected in a roadgraph, are also evaluated to determine probabilities of whether other road users may make an improper continuing lane driving operation. This is used to generate more accurate behavior predictions, which the vehicle can use to take alternative (e.g., corrective) driving actions.

A mobile object control system includes: a storage device configured to store instructions; and one or more processors, wherein the one or more processors execute the instructions stored in the storage device to: acquire an image in which a road surface around the mobile object is imaged; recognize support information for supporting walking of a specific traffic participant who is a traffic participant having a predetermined attribute obtained from the road surface imaged in the image and the traffic participant imaged in the image; predict a behavior of the recognized traffic participant based on the support information; and control the behavior of the mobile object based on the support information and the prediction result.

A mobile object control system includes: a storage device configured to store instructions; and one or more processors, wherein the one or more processors execute the instructions stored in the storage device to: acquire an image in which a road where a mobile object is present is imaged; recognize support information for supporting movement of a specific traffic participant who is a traffic participant having a predetermined attribute appearing on a road surface included in the image; recognize a road structure included in the image or a road structure which is a structure provided on the road; move the mobile object at least based on a trajectory determined using the support information when the support information is recognized; and move the mobile object based on a trajectory determined using the road structure without using the support information when the support information has not been recognized.

In a vehicle control device for an autonomous driving vehicle that autonomously travels based on an operation command, a gesture image of a person around the autonomous driving vehicle is acquired, and a stored reference gesture image is collated with the acquired gesture image. At this time, when it is discriminated that the gesture of the person around the autonomous driving vehicle is a gesture requesting the autonomous driving vehicle to stop, it is determined whether a disaster has occurred. When it is determined that the disaster has occurred, the autonomous driving vehicle is caused to stop around the person requesting the autonomous driving vehicle to stop.

A control apparatus includes a communication unit configured to receive motion data indicating motion of at least one user outside a vehicle that moves along a route including at least one road, and a controller configured to make a boarding determination of determining whether the at least one user will board the vehicle based on the motion data received by the communication unit and execute, upon determining in the boarding determination that the at least one user will board the vehicle, control for opening a door of the vehicle.

Systems/methods for operating an autonomous vehicle. The methods comprise, by a computing device: using sensor data to track an object that was detected in proximity to the autonomous vehicle; classifying the object into at least one dynamic state class of a plurality of dynamic state classes; transforming the at least one dynamic state class into at least one goal class of a plurality of goal classes; transforming the at least one goal class into at least one proposed future intention class of a plurality of proposed future intention classes; determining at least one predicted future intention of the object based on the proposed future intention class; and/or causing the autonomous vehicle to perform at least one autonomous driving operation based on the at least one predicted future intention determined for the object.

A vehicle control apparatus including a detection part configured to detect an external situation around a subject vehicle, and an electronic control unit including a microprocessor and a memory connected to the microprocessor. The microprocessor is configured to perform generating a map around the subject vehicle, based on an information on the external situation detected by the detection part, acquiring a travel information of the subject vehicle, extracting a specific information from among the travel information, adding the specific information to a landmark on the map, the landmark being a point on the map where the specific information has been obtained, and assisting in a driving based on the specific information added to the landmark.

A trajectory generation device 1 determines first to third predicted trajectories by using model formulas (1) to (20) that model a trajectory of a host vehicle 3 on the basis of peripheral information of an information detection device 4, calculates a risk potential R_p_mi_vj_v_r by using the first to third predicted trajectories, and determines moving average values P_c1 to P_c3 so that the risk potential R_p_mi_vj_v_r decreases. In a case where the moving average values P_c1 and P_c2 have the same sign, the first predicted trajectory is determined while reflecting the moving average value P_c2 for correcting the second predicted trajectory.

A control device for a mobile object includes a recognizer capable of recognizing a situation in a periphery of a mobile object, and a controller configured to control acceleration or deceleration of the mobile object based on the recognized situation in the periphery, and, when (1) there is a first obstacle that makes it difficult to recognize a situation on an opposite side in recognition of the situation in an extending direction of a road, (2) an end of the first obstacle is recognized and the first obstacle extends a first predetermined distance forward from the end, and (3) there is no second obstacle that makes it difficult to recognize the situation on the opposite side over a second predetermined distance on a traveling direction side of the mobile object from the end, the controller sets a risk area at a reference position based on the end of the first obstacle, and controls at least a speed of the mobile object based on the set risk area.