Methods and devices for controlling operation of a Self-Driving Car (SDC) are disclosed. The method includes, at a first moment in time during an approach of the SDC to a crosswalk: identifying, an object-inclusion zone in proximity to the crosswalk, determining presence of an object in the object-inclusion zone, determining an interval of time for the object based on movement data of the object, using the interval of time and movement data of the SDC for determining operation-control data for controlling operation of the SDC, and assigning decision data to the object-inclusion zone indicative of a decision.

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.

A hardware processor of a mobile object executes the program stored in a storage device to acquire information indicating a behavior of a mobile object which is capable of moving on both a roadway and a predetermined region different from the roadway; to recognize whether the mobile object is moving on the roadway or the predetermined region; to recognize presence of a contact portion between the predetermined region and the roadway in a traveling direction of the mobile object; to control the speed of the mobile object at least partially; to limit a speed at which the mobile object is moving on the roadway to a first speed; to limit a speed at which the mobile object is moving on the predetermined region to a second speed slower than the first speed; and to bring a speed of the mobile object closer to the second speed when the mobile object is moving on the roadway, the contact portion is recognized within a predetermined range from the mobile object, and a behavior of the mobile object satisfies a predetermined condition.

A control system includes an obtainer that obtains sensing data output from a sensor that performs sensing of an outside of a mobile body, a detector that detects a position of an object outside the mobile body based on the sensing data, a movement predictor that predicts a movement of the object based on the sensing data, a costmap generator that generates a first costmap based on the position detected of the object and a second costmap based on the movement predicted of the object, a path generator that generates a path for the mobile body based on the first costmap, a determination generator that generates a movement determination of the mobile body based on the second costmap and the path generated, and a controller that controls the movement of the mobile body in accordance with the path generated and the movement determination.

A vehicle control apparatus, a vehicle control method, and a program that can curb unnecessary driving control are provided. The vehicle control apparatus includes a pedestrian recognition unit configured to recognize a crossing pedestrian crossing a road on which a vehicle travels, a space recognition unit configured to recognize whether there is a space having a predetermined width or more between a lane on which the vehicle travels and an oncoming lane, and a driving control unit configured to execute avoidance support for avoiding contact between the vehicle and the crossing pedestrian recognized by the pedestrian recognition unit based on a behavior of the crossing pedestrian and a behavior of the vehicle, in which the driving control unit is configured to determine whether the crossing pedestrian recognized by the pedestrian recognition unit is moving from the oncoming lane side to a space recognized by the space recognition unit, and curb the avoidance support upon determination that the crossing pedestrian is moving to the space.

A feature avoidance system for a vehicle including at least one ultrasonic sensor disposed on a vehicle and communicatively coupled to a vehicle controller. A dynamic vehicle model is stored in the controller. The dynamic vehicle model is a computer model of current and expected dynamic vehicle component positioning. An analysis module configured cause at least one of the controller and a remote processing system to identify a feature at least partially via data from the at least one ultrasonic sensor, compare a predicted feature position and an estimated vehicle component position, and generate an output in response to the predicted feature position and the estimated vehicle component position intersecting.

Aspects of the disclosure relate to evaluating quality of a predetermined pullover location for an autonomous vehicle. For instance, a plurality of inputs for the predetermined pullover location may be received. The plurality of inputs may each include a value representative of a characteristic of the predetermined pullover location. The plurality of inputs may be combined to determine a pullover quality value for the predetermined pullover location. The pullover quality value may be provided to a vehicle in order to enable the vehicle to select a pullover location for the vehicle.

Systems and methods are provided for autonomous vehicle navigation. The systems and methods may map a lane mark, may map a directional arrow, selectively harvest road information based on data quality, map road segment free spaces, map traffic lights and determine traffic light relevancy, and map traffic lights and associated traffic light cycle times.

A method, system and device are disclosed for determining safety conflicts in redundant subsystems of autonomous vehicles. Each redundant subsystem calculates a world model or path plan, including locations, dimensions, and orientations of moving and stationary objects, as well as projected travel paths for moving objects in the future. The travel paths and projected future world models are subsequently compared using a geometric overlay operation. If at future time moments the projected world models match within predefined margins, the comparison results in a match. In case of a mismatch at a given future moment between projected world models, a determination is made as to whether the autonomous vehicle and all road users in this future moment are safe from collision or driving off the drivable space or road based on a geometric overlay operation.

Aspects of the disclosure relate to generating a speed plan for an autonomous vehicle. As an example, the vehicle is maneuvered in an autonomous driving mode along a route using pre-stored map information. This information identifies a plurality of keep clear regions where the vehicle should not stop but can drive through in the autonomous driving mode. Each keep clear region of the plurality of keep clear regions is associated with a priority value. A subset of the plurality of keep clear regions is identified based on the route. A speed plan for stopping the vehicle is generated based on the priority values associated with the keep clear regions of the subset. The speed plan identifies a location for stopping the vehicle. The speed plan is used to stop the vehicle in the location.