An autonomous vehicle (AV) includes features that allows the AV to comply with applicable regulations and statutes for performing safe driving operation. An example method includes detecting that a group of motorcycles is operating on a roadway on which the AV is located. The group of motorcycles are each located within a pre-determined distance away from one another. The method further includes determining an aggregate footprint area that surrounds respective locations of the group of motorcycles. The method further includes causing navigation of the autonomous vehicle that avoids penetration of the aggregate footprint area based on transmitting navigation instructions to one or more subsystems of the autonomous vehicle.

An example method includes detecting, via sensor data collected from sensors located on the AV, an upcoming object located on a roadway. The method further includes determining, from the sensor data, a relative distance and a relative direction of the upcoming object with respect to the autonomous vehicle. The method further includes mapping the upcoming object to an absolute location with respect to the roadway based on map data that describes upcoming topology of the roadway and a location of the autonomous vehicle. The method further includes associating the upcoming object with a lane of the roadway based on the absolute location mapped to the upcoming object and based on lane geometry data for the roadway. The method further includes operating the autonomous vehicle based on a relationship between the lane associated with the upcoming object and a current lane in which the autonomous vehicle is located.

An autonomous vehicle (AV) includes features that allows the AV to perform safe driving operations. An example method includes detecting that a motorcycle is operating on a roadway on which the autonomous vehicle is located. The method further includes classifying a behavior state of the motorcycle based on a location of the motorcycle relative to a split zone that extends between and into two adjacent lanes of the roadway. The behavior state indicates whether the motorcycle is lane splitting. The method further includes determining, based on the behavior state of the motorcycle, a lane permission parameter that controls whether a given trajectory for the autonomous vehicle can extend into one of the two adjacent lanes. The method further includes causing the autonomous vehicle to operate in accordance with a trajectory that satisfies the lane permission parameter based on transmitting instructions related to the trajectory to subsystems of the autonomous vehicle.

A method includes obtaining, using at least one processing device, a refined boundary identifying a specified portion of a detected object within a scene, where the refined boundary is associated with image data. The method also includes repeatedly, during multiple iterations and using the at least one processing device, (i) identifying multiple regions within the refined boundary and (ii) determining a similarity of the image data contained within the multiple regions. In addition, the method includes identifying, using the at least one processing device, one or more locations of one or more components of the detected object based on the identified regions and the determined similarities.

A method includes obtaining, using at least one processing device, image data associated with a scene. The method also includes identifying, using the at least one processing device, multiple line segments based on the image data. The method further includes identifying, using the at least one processing device, one or more boundaries around one or more objects detected in the image data. In addition, the method includes estimating, using the at least one processing device, a position of a vanishing point associated with the image data based on multiple collections of the line segments while excluding, from the multiple collections, one or more of the line segments that overlap with or that are included within the one or more boundaries.

Disclosed herein is a system and method for controlling a moveable device utilizing risk control barrier functions. In one example, a system for controlling a moveable device includes a processor and memory containing programming executable by the processor. The programming is configured to receive various information about the moveable device and receive a risk tolerance for a user and calculate a risk control barrier function. The programming is configured to receive a command from the user to alter the state of the moveable device; calculate a dynamic coherent risk measurement based on the risk tolerance of the user and in respect to the risk control barrier function in respect to the command from the user to alter the state of the moveable device; determine whether the dynamic coherence risk measurement is beyond a tuning parameter at the current state of the moveable device.

A control device associated with an autonomous vehicle detects that a person is altering traffic on a road using a hand signal. The control device determines an interpretation of the hand signal. The control device determines a proposed trajectory according to the interpretation of the hand signal. The control device transmits the proposed trajectory to an oversight server. The oversight server determines whether the hand signal is in use to alter the traffic. The oversight server also determines whether the proposed trajectory causes the autonomous vehicle to go out of a pre-mapped area where the autonomous vehicle is able to autonomously travel. In response to determining that the hand signal is in use and that the proposed trajectory does not cause the autonomous vehicle to go out of the pre-mapped area, the oversight server transmits an instruction that indicates to perform the proposed trajectory to the control device.

A control device associated with an autonomous vehicle detects that a construction worker is altering traffic on a road using a construction zone-related hand signal to divert the traffic from a construction site. The control device determines an interpretation of the construction zone-related hand signal. The control device determines a proposed trajectory for the autonomous vehicle according to the interpretation of the construction zone-related hand signal. In certain embodiments, the control device may navigate the autonomous vehicle according to the interpretation of the construction zone-related hand signal. In certain embodiments, the control device may transmit the proposed trajectory to an oversight server for confirmation. In certain embodiments, the oversight may confirm or override the proposed trajectory.

A system for interactive hypothesis estimation of multi-vehicle traffic for autonomous driving is provided. The system includes a sensor upon a host vehicle providing data regarding an operating environment of the host vehicle and a computerized device. The computerized device is operable to monitor the data from the sensor, identify a road surface based upon the data, and identify a neighborhood object based upon the data. The computerized device is further operable to determine a pressure score for the neighborhood object based upon a likelihood that the neighborhood object will conflict with the host vehicle based upon the road surface and the neighborhood object, selectively track the neighborhood object based upon the pressure score, and navigate the host vehicle based upon the tracking of the neighborhood object.

A drive assistance device includes an automatic brake unit configured to perform automatic brake control, a brake hold unit configured to perform a brake hold control keeping the vehicle stopped, a brake hold cancel unit configured to cancel the brake hold control when it is determined that a predetermined cancel condition is satisfied, a surroundings information obtaining unit configured to obtain surroundings information indicating a situation around the vehicle, a maneuver information obtaining unit configured to obtain maneuver information about a driving maneuver performed by a driver of the vehicle, a maneuver determination unit configured to determine, based on the surroundings information and the maneuver information whether the driving maneuver performed during the brake hold control is appropriate for the situation around the vehicle, and a prohibition unit configured to prohibit cancelling the brake hold control as long as it is determined that the driving maneuver is inappropriate.