Abstract: An augmented navigational system is provided for autonomous vehicles. The augmented navigational system may further be coupled to an artificial intelligence system that provides object recognition and image recognition. A machine learning system may provide further feedback as to whether the pickup and drop off location was appropriate, and whether the recognition of one or more objects was appropriate.

Abstract: The device may be enabled to be connected to a first and second cellular network at two different towers simultaneously to provide more reliable connections, or to split voice and data traffic. The devices may further be enabled to selectively turn off radios and place such radios in wait states or low power listen states based on the network connectivity, application rules and application hierarchies. Sensors may forward packets to a mobile device when in the vicinity and these packets may be synchronized selectively with a network server when the mobile device is connected to a network and has sufficient or cheap bandwidth. Various IoT and sensor devices may use non reliable transmit and receive protocols in addition to TCP/IP for uncritical data.

Abstract: An artificial intelligence-based routing and path optimization module is enabled for autonomous AVs. The AV is enabled to navigate to surface roads based on the computational complexity of the navigation and the computational power within the autonomous self-driving AV, a cloud infrastructure, and/or an edge device. An AI based model is implemented to determine which navigational approaches are appropriate for an autonomous AV to pursue based on compute resources available and compute resources required. A module implemented in a cloud based server and/or within an autonomous AV is enabled to match the computational complexity of routes with the navigation. The autonomous AV is enabled to create a navigational prediction movement model for these objects to determine the likely behavior of the objects. The AV may include autonomous cars, autonomous trucks, vertical take off and landing (VTOL) devices, electric VTOL, electric bikes, flying cars, and other transportation devices.

Abstract: An autonomous transport device system is enabled for one or more autonomous vehicles and autonomous surface delivery devices. Specific pickup and drop off zones for package delivery and user transport may be defined. The system leverages an artificial intelligence based learning algorithm to understand various environments. Packages may be dropped off in the geofenced areas. In some instances, packages may be stored in hidden areas that are purposely cached local to a likely delivery area. Some areas may be marked for pickup and drop off. Shippers may cache certain packages proximate to locations based on demand, joint distribution centers, and the presence of multiple transport devices including rovers, drones, UAVs, and autonomous vehicles.

Abstract: Windows including sunroofs of a car may be enabled to display cinematic video, still pictures, opaque content, or picturesque content such as the countryside to simulate various environments while driving. On the outside of the autonomous vehicle advertising content may be shown on digital displays to pedestrians, bystanders, and other vehicle, autonomous vehicle or semi-autonomous vehicle passengers. Advertising revenue may offset vehicle leasing, maintenance, fuel, and ridesharing costs. Ad networks may send local offers content for presentation on the vehicle, autonomous vehicle or semi-autonomous vehicle's windows. Passengers may order food and interact with ads on the car window. The car windows may be multi-touch enabled to allow for various gestures and interactivity with the vehicle, autonomous vehicle or semi-autonomous vehicle. Chairs in the car may be rotated to allow for better positioning of the passenger to window screens.