Aspects concern a method for controlling a transport system comprising determining historical data of a multiplicity of transport trips performed by the transport system, training a neural network to perform an invertible mapping of transport trips to latent representations to fulfil, by the distribution of the latent representations of the multiplicity of transport trips, a predetermined fitting criterion with respect to a predetermined latent representation base distribution, sampling a multiplicity of latent representations from the base distribution, mapping each of the sampled latent representations to a respective transport trip by using the trained neural network to perform the inverse of the invertible mapping to generate a multiplicity of synthetic transport trips, determining a control scheme for the transport system using the multiplicity of synthetic transport trips and controlling the transport system using the determined control scheme.

An information processing apparatus includes a controller. When a cancellation of a reservation for use of an on-demand bus occurs, the controller determines a cancellation fee to be charged to a user who makes the cancellation, based on timing of occurrence of the cancellation.

Disclosed herein are system, method, and computer program product embodiments for ride hailing an autonomous vehicle by a third party. For example, the method includes: receiving, from a user device associated with a user account of a user for an autonomous vehicle service, (i) a request to add a rider profile associated with a rider other than the user to the user account and (ii) rider information associated with the rider; generating, based on the rider information, the rider profile; receiving, from the user device, a pick-up request associated with (i) the user account and (ii) the rider profile; assigning, based on the pick-up request, an autonomous vehicle to pick-up the rider; and providing, to the autonomous vehicle assigned to pick-up the rider, based on the rider profile, an indication of a type of identification to use to identify the rider and/or unlock the autonomous vehicle when picking-up the rider.

A method of generating a travel order includes: receiving a first gesture collected by a first terminal device and a location of the first terminal device; in response to a request for a travel order triggered by the first gesture, receiving a second gesture collected by the first terminal device; generating the travel order including a departure address and a destination address, wherein the destination address matches the second gesture, and the departure address is associated with the location of the first terminal device; and sending the travel order.

A method of generating a travel order includes: receiving a first gesture collected by a first terminal device and a location of the first terminal device; in response to a request for a travel order triggered by the first gesture, receiving a second gesture collected by the first terminal device; generating the travel order including a departure address and a destination address, wherein the destination address matches the second gesture, and the departure address is associated with the location of the first terminal device; and sending the travel order.

A vehicle control device for controlling a vehicle is configured to stop in response to a request from a prospective passenger and allow the prospective passenger to board. The vehicle control device includes: a stop candidate location extraction unit configured to extract a candidate location for a stop location where the vehicle is to be stopped in order to allow the prospective passenger to board; a first movement time calculation unit configured to calculate a first movement time that is a time required for the prospective passenger to move to the candidate location; a second movement time calculation unit configured to calculate a second movement time that is a time required for the vehicle to move to the candidate location; a standby time calculation unit configured to calculate a standby time of the vehicle at the candidate location based on the first movement time and the second movement time; and a stop location determination unit configured to determine, when the standby time is equal to or shorter than a predetermined allowable stop time at the candidate location, the candidate location as the stop location.

Systems and methods are described for generating transactions based upon rideshare data and updating a distributed ledger. The method may include (1) monitoring a distributed ledger for an indication of an accident, the indication of the accident identifying at least a user and a time period; (2) obtaining rideshare data from the distributed ledger, wherein the rideshare data: identifies one or more rideshare companies for which the user offered driving services during the time period; and (3) verifying, based upon the rideshare data, a controlling party, wherein the controlling party is one of the user or one of the one or more rideshare companies.

A network computer system operates to estimate a quantity of service vehicles operating in a geographic region during a future time interval. For the future time interval, the network computer system determines a current forecast of a provisioning level for a service provided by the projected quantity of service vehicles in each of multiple subregions of the geographic region. The network computer system also determines a location bias for one or more service providers, each operating a corresponding vehicle within the given geographic region. Additionally, the network computer system matches each service provider to a service request based on (i) the location bias of the service provider, (ii) a service location of the service request, and (iii) a determination as to an effect of matching the service provider on the current forecast for the provisioning level.

Embodiments provide techniques, including systems and methods, for assignment and/or reassignment of transport requests received within a request matching time period. For example, transport requests received during a request matching time period, as well as requests determined to be eligible during the request matching time period for reassignment, are associated with a location identifier (e.g., geohash) and are pooled at a dynamic transportation matching system in order for a dynamic assignment and/or reassignment that may reduce a metric (e.g., an overall estimated time of arrival (ETA) for requests) associated with the dynamic transportation matching system.

A transport network management system identifies a service objective for a plurality of VTOL aircraft and retrieves VTOL data including locations of the plurality of VTOL aircraft. An estimate of demand for transport services to be provided at least in part by one of the VTOL aircraft is generated and routing data for the plurality of VTOL aircraft is determined based on the estimated demand and the service objective. Routing instructions based on the routing data are sent to at least a subset of the VTOL aircraft.