Apparatuses, methods and storage medium associated with computer-assisted or autonomous driving (CA/AD) vehicles are disclosed herein. In embodiments, CA/AD vehicles are members of a CA/AD vehicle social network (CASN) in which various CA/AD vehicles may form connections or relationships with one another. CA/AD vehicles that have an existing relationship or connection may share CASN information with one another. The CASN information may include authenticated and/or proprietary information. Other embodiments are also described and claimed.

Aspects of the disclosure provide for generating distributions for hypothetical or potentially occluded objects. For instance, a location for which to generate one or more distributions may be identified. Observations of road users by perception systems of a plurality of autonomous vehicles may be accessed. Each of these observations may identify a characteristic of one of the road users. A distribution of the characteristic for the location may be determined based on the observations. The distribution may be provided to one or more autonomous vehicles in order to enable the one or more autonomous vehicles to use the distribution to generate a characteristic for a hypothetical occluded road user and to respond to the hypothetical occluded road user.

Methods and systems for autonomous and semi-autonomous vehicle control, routing, and automatic feature adjustment are disclosed. Sensors associated with autonomous operation features may be utilized to search an area for missing persons, stolen vehicles, or similar persons or items of interest. Sensor data associated with the features may be automatically collected and analyzed to passively search for missing persons or vehicles without vehicle operator involvement. Search criteria may be determined by a remote server and communicated to a plurality of vehicles within a search area. In response to which, sensor data may be collected and analyzed by the vehicles. When sensor data generated by a vehicle matches the search criteria, the vehicle may communicate the information to the remote server.

An example operation includes one or more of determining, by a transport at a first location, that the transport is not in use, determining, by the transport, a second location to transfer energy stored in the transport, maneuvering, by the transport, to the second location, discharging, by the transport, the stored energy to the second location, and maneuvering, by the transport, to the first location.

Methods and systems for deploying autonomous vehicles to form a barricade in a coordinated response to an imminent threat are described. In one embodiment, a method for deploying autonomous vehicles to form a barricade is described. The method includes determining at least one location for a barricade and determining a plurality of autonomous vehicles that are available to form the barricade. The method also includes sending instructions to the plurality of autonomous vehicles to form the barricade at the at least one location. In response to the instructions, the plurality of autonomous vehicles are configured to move to the at least one location and form the barricade.

A modular mobility base for a modular autonomous bot apparatus transporting an item being shipped including a mobile base platform, a component alignment interface, a mobility controller, a propulsion and steering system, and sensors. The component alignment interface provides an alignment channel into which another modular component can be placed and secured on the platform. The mobility controller generates propulsion control signals for controlling speed of the modular mobility base and steering control signals for navigation of the modular mobility base. The propulsion system is connected to the platform and responsive to the propulsion control signal. The steering system is connected to the mobile base platform and is responsive to the steering control signal to cause changes to directional movement of the modular mobility base. The sensors are disposed on the platform provide feedback sensor data to the mobility controller about a condition of the modular mobility base.

A method for finding at least one trigger for human intervention in a control of a vehicle, the method may include receiving, from a plurality of vehicles, and by an I/O module of a computerized system, visual information acquired during situations that are suspected as situations that require human intervention in the control of at least one of the plurality of vehicles; determining, based at least on the visual information, the at least one trigger for human intervention; and transmitting to one or more of the plurality of vehicles, the at least one trigger.

Described herein is a method for setting up and/or reconfiguring an industrial plant, in particular for the manufacture of motor vehicles or sub-assemblies thereof. The method includes providing a plurality of mobile processing stations, each mobile processing station comprising a palletisable platform and at least one interface unit provided on the palletisable platform and configured for the coupling of the mobile processing station with one or more further adjacent mobile processing stations; arranging mobile processing stations according to a pre-set layout; and coupling at least one interface unit of each mobile processing station with the at least one interface unit of one or more further mobile processing adjacent stations thereto. Each interface unit includes at least one of the following: an electrical and/or electronic coupling device; a fluidic coupling device; and a mechanical coupling device.

The present teaching relates to system, method, medium for in-situ perception in an autonomous driving vehicle. A plurality of types of sensor data are received, which are acquired by a plurality of types of sensors deployed on the vehicle to provide information about surrounding of the vehicle. Based on at least one model, one or more surrounding items are tracked from a first of the plurality of types of sensor data acquired by a first type sensors. At least some of the tracked items are automatically labeled via cross validation and are used to locally adapt, on-the-fly, the at least one model. Model update information is received which from a model update center, which is derived based on the labeled at least some items. The at least one model is updated using the model update information.

An autonomous lawn mower includes removable batteries, one or more electric motors, a cutting blade, one or more wheels, an angle sensor, and a controller. The cutting blade is driven by one of the electric motors. The wheels are driven by one of the electric motors. The controller is configured to allow the lawn mower to perform a grass cutting function at a jobsite without human interaction. The controller is configured to determine whether a roll angle is greater than a first predefined amount using data from the angle sensor. In response to determining the roll angle is greater than the first predefined amount, the controller is configured to stop operation of one of the one or more electric motors configured to provide rotational drive power to the cutting blade.