Abstract: The present application relates to a film wrapping equipment. The film wrapping equipment includes: a film wrapping assembly including two film wrapping rollers arranged opposite to each other in a first direction, and a film wrapping channel for a product to pass through formed between the two film wrapping rollers; a film pulling assembly arranged on one side of the film wrapping assembly in the first direction; a product loading assembly used to clamp the product and drive the product to pass through the film wrapping channel; and a strip cutting assembly used to cut off material strips located on two sides of the two film wrapping rollers in the first direction.

Abstract: In various examples, a current claimed set of points representative of a volume in an environment occupied by a vehicle at a time may be determined. A vehicle-occupied trajectory and at least one object-occupied trajectory may be generated at the time. An intersection between the vehicle-occupied trajectory and an object-occupied trajectory may be determined based at least in part on comparing the vehicle-occupied trajectory to the object-occupied trajectory. Based on the intersection, the vehicle may then execute the first safety procedure or an alternative procedure that, when implemented by the vehicle when the object implements the second safety procedure, is determined to have a lesser likelihood of incurring a collision between the vehicle and the object than the first safety procedure.

Abstract: In various examples, a current claimed set of points representative of a volume in an environment occupied by a vehicle at a time may be determined. A vehicle-occupied trajectory and at least one object-occupied trajectory may be generated at the time. An intersection between the vehicle-occupied trajectory and an object-occupied trajectory may be determined based at least in part on comparing the vehicle-occupied trajectory to the object-occupied trajectory. Based on the intersection, the vehicle may then execute the first safety procedure or an alternative procedure that, when implemented by the vehicle when the object implements the second safety procedure, is determined to have a lesser likelihood of incurring a collision between the vehicle and the object than the first safety procedure.

Abstract: In various examples, a yield scenario may be identified for a first vehicle. A wait element is received that encodes a first path for the first vehicle to traverse a yield area and a second path for a second vehicle to traverse the yield area. The first path is employed to determine a first trajectory in the yield area for the first vehicle based at least on a first location of the first vehicle at a time and the second path is employed to determine a second trajectory in the yield area for the second vehicle based at least on a second location of the second vehicle at the time. To operate the first vehicle in accordance with a wait state, it may be determined whether there is a conflict between the first trajectory and the second trajectory, where the wait state defines a yielding behavior for the first vehicle.

Abstract: To determine a path through a pose configuration space, trajectories of poses may be evaluated in parallel based at least on translating the trajectories along at least one axis of the pose configuration space (e.g., an orientation axis). A trajectory may include at least a portion of a turn having a fixed turn radius. Turns or turn portions that have the same turn radius and initial orientation can be translatively shifted along and processed in parallel along the orientation axis as they are translated copies of each other, but with different starting points. Trajectories may be evaluated based at least on processing variables used to evaluate reachability as bit vectors with threads effectively performing large vector operations in synchronization. A parallel reduction pattern may be used to account for dependencies that may exist between sections of a trajectory for evaluating reachability, allowing for the sections to be processed in parallel.

Abstract: Method and device for executing time critical processing in a non-real-time operating system. The method includes capturing a message by a packet capturing tool; analyzing whether the message is a sample value message associated with the time critical processing, and when the message is a sample value message associated with the time critical processing, writing a data unit included in the sample value message into a first buffer; preprocessing the data unit, the preprocessing includes arranging and combining bytes of the data unit so that the bytes indicate sample value is located at specific position; writing the preprocessed data unit from the first buffer into a second buffer and triggering a real-time dedicated thread at the same time, in response to the preprocessed data unit in the first buffer reaching the predetermined number; and executing the time critical processing by reading the preprocessed data unit from the second buffer.

Abstract: In various examples, systems and methods are disclosed for weighting one or more optional paths based on obstacle avoidance or other safety considerations. In some embodiments, the obstacle avoidance considerations may be computed using a comparison of trajectories representative of safety procedures at present and future projected time steps of an ego-vehicle and other actors to ensure that each actor is capable of implementing their respective safety procedure while avoiding collisions at any point along the trajectory. This comparison may include filtering out a path(s) of an actor at a time step(s)—e.g., using a one-dimensional lookup—based on spatial relationships between the actor and the ego-vehicle at the time step(s). Where a particular path—or point along the path—does not satisfy a collision-free standard, the path may be penalized more negatively with respect to the obstacle avoidance considerations, or may be removed from consideration as a potential path.

Abstract: In various examples, a current claimed set of points representative of a volume in an environment occupied by a vehicle at a time may be determined. A vehicle-occupied trajectory and at least one object-occupied trajectory may be generated at the time. An intersection between the vehicle-occupied trajectory and an object-occupied trajectory may be determined based at least in part on comparing the vehicle-occupied trajectory to the object-occupied trajectory. Based on the intersection, the vehicle may then execute the first safety procedure or an alternative procedure that, when implemented by the vehicle when the object implements the second safety procedure, is determined to have a lesser likelihood of incurring a collision between the vehicle and the object than the first safety procedure.

Abstract: Systems and methods allow for incident data collection and management system based on unmanned aerial vehicles (UAVs), that is, drones to help accelerate the data collection and analytics, information dissemination, and decision support at incident sites. The system architecture may include onsite, server, and offline components including flight planning subsystem, flight execution and mission control subsystem, information dissemination subsystem to travelers and traveler information services, the interface with traffic management center, and the data analytic, visualization, and training subsystems. Other embodiments include the video-based 3D incident site reconstruction methods, site positioning and scaling methods with pre-collected static background infrastructure data, data management and user charging methods, and training methods with the generated 3D model.

Abstract: Embodiments of the present disclosure relate to behavior planning for autonomous vehicles. The technology described herein selects a preferred trajectory for an autonomous vehicle based on an evaluation of multiple hypothetical trajectories by different components within a planning system. The various components provide an optimization score for each trajectory according to the priorities of the component and scores from multiple components may form a final optimization score. This scoring system allows the competing priorities (e.g., comfort, minimal travel time, fuel economy) of different components to be considered together. In examples, the trajectory with the best combined score may be selected for implementation. As such, an iterative approach that evaluates various factors may be used to identify an optimal or preferred trajectory for an autonomous vehicle when navigating an environment.

Abstract: In various examples, a current claimed set of points representative of a volume in an environment occupied by a vehicle at a time may be determined. A vehicle-occupied trajectory and at least one object-occupied trajectory may be generated at the time. An intersection between the vehicle-occupied trajectory and an object-occupied trajectory may be determined based at least in part on comparing the vehicle-occupied trajectory to the object-occupied trajectory. Based on the intersection, the vehicle may then execute the first safety procedure or an alternative procedure that, when implemented by the vehicle when the object implements the second safety procedure, is determined to have a lesser likelihood of incurring a collision between the vehicle and the object than the first safety procedure.

Abstract: In various examples, sensor data may be collected using one or more sensors of an ego-vehicle to generate a representation of an environment surrounding the ego-vehicle. The representation may include lanes of the roadway and object locations within the lanes. The representation of the environment may be provided as input to a longitudinal speed profile identifier, which may project a plurality of longitudinal speed profile candidates onto a target lane. Each of the plurality of longitudinal speed profiles candidates may be evaluated one or more times based on one or more sets of criteria. Using scores from the evaluation, a target gap and a particular longitudinal speed profile from the longitudinal speed profile candidates may be selected. Once the longitudinal speed profile for a target gap has been determined, the system may execute a lane change maneuver according to the longitudinal speed profile.

Abstract: Systems and methods allow for incident data collection and management system based on unmanned aerial vehicles (UAVs), that is, drones to help accelerate the data collection and analytics, information dissemination, and decision support at incident sites. The system architecture may include onsite, server, and offline components including flight planning subsystem, flight execution and mission control subsystem, information dissemination subsystem to travelers and traveler information services, the interface with traffic management center, and the data analytic, visualization, and training subsystems. Other embodiments include the video-based 3D incident site reconstruction methods, site positioning and scaling methods with pre-collected static background infrastructure data, data management and user charging methods, and training methods with the generated 3D model.

Abstract: Systems and methods allow for incident data collection and management system based on unmanned aerial vehicles (UAVs), that is, drones to help accelerate the data collection and analytics, information dissemination, and decision support at incident sites. The system architecture may include onsite, server, and offline components including flight planning subsystem, flight execution and mission control subsystem, information dissemination subsystem to travelers and traveler information services, the interface with traffic management center, and the data analytic, visualization, and training subsystems. Other embodiments include the video-based 3D incident site reconstruction methods, site positioning and scaling methods with pre-collected static background infrastructure data, data management and user charging methods, and training methods with the generated 3D model.

Abstract: Systems and methods allow for incident data collection and management system based on unmanned aerial vehicles (UAVs), that is, drones to help accelerate the data collection and analytics, information dissemination, and decision support at incident sites. The system architecture may include onsite, server, and offline components including flight planning subsystem, flight execution and mission control subsystem, information dissemination subsystem to travelers and traveler information services, the interface with traffic management center, and the data analytic, visualization, and training subsystems. Other embodiments include the video-based 3D incident site reconstruction methods, site positioning and scaling methods with pre-collected static background infrastructure data, data management and user charging methods, and training methods with the generated 3D model.

Abstract: In various examples, a current claimed set of points representative of a volume in an environment occupied by a vehicle at a time may be determined. A vehicle-occupied trajectory and at least one object-occupied trajectory may be generated at the time. An intersection between the vehicle-occupied trajectory and an object-occupied trajectory may be determined based at least in part on comparing the vehicle-occupied trajectory to the object-occupied trajectory. Based on the intersection, the vehicle may then execute the first safety procedure or an alternative procedure that, when implemented by the vehicle when the object implements the second safety procedure, is determined to have a lesser likelihood of incurring a collision between the vehicle and the object than the first safety procedure.

Abstract: Systems and methods allow for incident data collection and management system based on unmanned aerial vehicles (UAVs), that is, drones to help accelerate the data collection and analytics, information dissemination, and decision support at incident sites. The system architecture may include onsite, server, and offline components including flight planning subsystem, flight execution and mission control subsystem, information dissemination subsystem to travelers and traveler information services, the interface with traffic management center, and the data analytic, visualization, and training subsystems. Other embodiments include the video-based 3D incident site reconstruction methods, site positioning and scaling methods with pre-collected static background infrastructure data, data management and user charging methods, and training methods with the generated 3D model.

Abstract: A system and method for determining a path for autonomous navigation based on user input is described. The vehicle can include one or more sensors to collect data for generating a three-dimensional (3D) model of the vehicle's surroundings. A two-dimensional (2D) occupancy grid map can be generated from the 3D model and displayed at a computing device. In some examples, the occupancy grid map can be displayed at a user interface of the electronic device. The user interface can further accept user input in the form of one or more of a user-defined path, an endpoint, a vehicle pose, or a series of waypoints. Based on the user input, a finalized path for autonomous vehicle travel can be determined. Determining a finalized path can include determining an optimal, minimum-distance path, applying a smoothing algorithm, and/or applying a constraint to maintain a minimum distance from any static obstacles near the vehicle.

Abstract: A system that performs a method is disclosed. The system operates a vehicle in a first automation level corresponding to a first plurality of modes for operating the vehicle. The first plurality of modes comprises logic for performing automated driving operations, wherein the first automation level is associated with a first logic for transitioning between the first plurality of modes. While operating the vehicle in the first automation level, the system determines that automation level change criteria for transitioning from the first automation level to a second automation level are satisfied. In response to the determination, the system operates the vehicle in the second automation level corresponding to a second plurality of modes for operating the vehicle. The second plurality of modes comprises logic for performing automated driving operations, wherein the second automation level is associated with a second logic for transitioning between the second plurality of modes.