Abstract: Robot-assisted package delivery with integrated curbside parking monitoring and curb operations optimization is disclosed herein. An example method includes dispatching a delivery vehicle and delivery robot to a delivery location, the delivery location including a parking location for the delivery vehicle that allows for deployment of the delivery robot on a delivery mission, determining occupancy of the parking location, the delivery vehicle parking at the parking location when the parking location is unoccupied, the delivery robot being deployed upon parking of the delivery vehicle, and instructing the delivery vehicle to remain parked during the delivery mission or to leave the parking location and return at later point in time based on an estimated time of arrival of the delivery robot after the delivery mission.

Abstract: Systems and methods for mobility service demand prediction are disclosed herein. An example method includes determining trips of an existing transportation mode for a geo fenced area that are poorly served. The trips that are poorly served can include any one or more of the trips with a moderately high trip density, a moderately high ratio of transit-private vehicle trips, and/or a moderately high ratio of transit-time to private vehicle travel times. The method can include modeling trips of a new transportation service for a geofenced area, determining, based on the modeling, when the trips of the new transportation service have at least one improved travel parameter relative the trips that are poorly served, as well as generating a mobility service demand prediction that is indicates how likely users are to adopt new transportation service in view of the existing transportation mode.

Abstract: Robot-assisted package delivery with integrated curbside parking monitoring and curb operations optimization is disclosed herein. An example method includes dispatching a delivery vehicle and delivery robot to a delivery location, the delivery location including a parking location for the delivery vehicle that allows for deployment of the delivery robot on a delivery mission, determining occupancy of the parking location, the delivery vehicle parking at the parking location when the parking location is unoccupied, the delivery robot being deployed upon parking of the delivery vehicle, and instructing the delivery vehicle to remain parked during the delivery mission or to leave the parking location and return at later point in time based on an estimated time of arrival of the delivery robot after the delivery mission.

Abstract: Hybrid light personal electric vehicle analysis is disclosed herein. An example method includes determining empirical data from a light personal electric vehicle (LPEV) over a period of time, determining LPEV behaviors from the empirical data during the period of time, and building a hybrid simulation model over the period of time by switching between a pedestrian simulation model when the LPEV behaviors correspond to pedestrian behaviors and a vehicle simulation model when the LPEV behaviors correspond to vehicle behaviors.

Abstract: Geolocation based vehicle access systems and methods are disclosed herein. An example method includes receiving a blockchain ledger from a vehicle operating in a controlled area, the blockchain ledger including time-stamped, location and vehicle data. The method also includes comparing the time-stamped, location and vehicle data to database records that have control access parameters for controlled areas. In addition, the method includes generating a notice when the time-stamped, location and vehicle data matches control access parameters for the controlled area, which is one of the controlled areas. More so, the method includes providing the notice to the vehicle or a user of the vehicle.

Abstract: Hybrid light personal electric vehicle analysis is disclosed herein. An example method includes determining empirical data from a light personal electric vehicle (LPEV) over a period of time, determining LPEV behaviors from the empirical data during the period of time, and building a hybrid simulation model over the period of time by switching between a pedestrian simulation model when the LPEV behaviors correspond to pedestrian behaviors and a vehicle simulation model when the LPEV behaviors correspond to vehicle behaviors.