In an approach to improve mobile computation while traveling by dynamically generating one or more routes base on computing resource requirements of one or more endpoint devices. Embodiments identify, in real time, a plurality of autonomous vehicles, wherein the plurality of autonomous vehicles are traveling along a common route. Further embodiments, adjust, in real time, relative positions and speeds of the plurality of autonomous vehicles to maintain the plurality of autonomous vehicles within a predetermined geographic area while traveling along the common route, and wherein the predetermined geographic area is sufficient to collectively provide an amount of edge computing resources to satisfy one or more computing resource requirements of the one or more endpoint devices located within a first autonomous vehicle. Additionally, embodiments adjust, in real time, a route of the first autonomous vehicle based on the common route of the plurality of autonomous vehicles providing the edge computing resources.

A lane-borrowing vehicle driving method includes generating, by a control center, a first lane-borrowing driving policy of the vehicle based on a lane-borrowing requirement, a moving trend of the vehicle, and a preset traffic rule, where the lane-borrowing requirement includes a lane-borrowing driving reason, and the first lane-borrowing driving policy includes an instruction for controlling lane-borrowing driving of the vehicle, and sending, by the control center, the first lane-borrowing driving policy to the vehicle. The embodiments of this application are used for temporary lane-borrowing driving and lane-borrowing driving on a tidal lane.

A transport system includes a plurality of transport vehicles and a controller. The transport vehicle includes a travel unit and transfer unit. The controller performs a blocking control to prohibit transport vehicles other than the transport vehicle from entering a blocking zone corresponding to the area occupied by the transport vehicle when transferring an article in a plan view. To transfer an article from/to a placement table, the transport vehicle travels along the route to the placement table in a first direction. An area of the blocking zone when the transport vehicle accesses to the placement table in the first direction is equal to or less than an area of the blocking zone identified when the transport vehicle accesses to the placement table in the second direction different from the first direction.

A controller, first automated guided vehicle, second automated guided vehicle and methods of guiding a platoon of automated guided vehicles. The method includes providing by the controller a first target position and a first target orientation to the first automated guided vehicle having sensors used for person safety and navigation that is configurable or configured to lead a platoon of automated guided vehicles, and sending by the controller to the second automated guided vehicle not having sensors used for person safety and navigation a command to join the platoon of automated guided vehicles and/or to follow the first automated guided vehicle in the platoon of automated vehicles.

A controller is configured to acquire primary information indicating that an emergency vehicle during emergency driving has satisfied the condition that the emergency vehicle has entered a particular area in which right of way may be given and/or the condition that the emergency vehicle has shifted into a specific driving mode in which right of way may be given within the particular area. Upon acquisition of the primary information, the controller stops a siren of the emergency vehicle or reduces the volume of the siren of the emergency vehicle.

Methods and systems are provided for belief space planning for multiple robots at an initial belief state, for reducing belief space uncertainty, including receiving multiple, candidate, multi-robot paths, each including one or more pose constraints; generating a candidate factor graph for each candidate multi-robot path, and generating from each candidate factor graph a topology graph; calculating a signature metric from each topology graph, wherein the signature metric is one of a Von Neumann (VN) metric and a spanning tree (ST) metric; selecting a multi-robot path having the greatest signature metric from among the candidate, multi-robot paths; and instructing the multiple robots to proceed according to the selected multi-robot path.

An example operation may include one or more of identifying various transports with an assigned destination location, determining the transports assigned to the destination location exceeds a number of available parking spaces at the destination location, identifying alternative parking spaces in an area adjacent to the destination location, and assigning at least one of the alternative parking spaces to at least one of the transports based on a priority of the at least one transport.

A method for replacing a first module (30, 40) of a vehicle (1) with a new module (30, 30′, 40). The vehicle (1) includes: at least one drive module (30); and at least one functional module (40). The vehicle (1) has a unique vehicle identity. The method includes: setting (s101) the vehicle (1) into a maintenance mode indicating that the vehicle (1) is not available for operation; and preparing (s102) the vehicle (1) for physical disconnection of the first module (30, 40); when the first module (30, 40) has been physically disconnected from the vehicle (1) and the new module (30, 30′, 40) has been physically connected to the vehicle (1): establishing (s103) an electrical connection between the new module (30, 30′, 40) and the vehicle (1); assigning (s104) the new module (30, 30′, 40) the unique vehicle identity of the vehicle (1); setting (s105) the vehicle (1) into an operational mode; and verifying s106) the electrical connection of the new module (30, 30′, 40).

Disclosures herein may be directed to a method, technique, or apparatus directed to a computer-assisted or autonomous driving (CA/AD) vehicle that includes a system controller, disposed in a first CA/AD vehicle, to manage a collaborative three-dimensional (3-D) map of an environment around the first CA/AD vehicle, wherein the system controller is to receive, from another CA/AD vehicle proximate to the first CA/AD vehicle, an indication of at least a portion of another 3-D map of another environment around both the first CA/AD vehicle and the another CA/AD vehicle and incorporate the at least the portion of the 3-D map proximate to the first CA/AD vehicle and the another CA/AD vehicle into the 3-D map of the environment of the first CA/AD vehicle managed by the system controller.

Increased robotic sophistication and more efficient autonomous operation is implemented by providing separate physical autonomous robots shared and remote access to the sensory array and information from the sensory array of one another. Each robot can access a sensor of any other robot, or scans or other information obtained from the sensor of any other robot. The robots leverage the shared sensory access in order to perform batch order fulfillment, dynamic rearrangement of item or tote locations, and opportunistic charging. These coordinated robotic operations based on the shared sensory access increase the efficiency and productivity of the robots without adding resources or hardware to the robots, increasing the speed of the robots, or increasing the number of deployed robots.