Embodiments of the present invention provide computer-implemented methods, computer program products, and systems. Embodiments of the present invention can be used to receive position information for one or more user devices and location information for an area. Embodiments of the present invention can predict one or more locations of the one or more user devices. Embodiments of the present invention can, in response to a request for navigation services, dynamically navigate a first user device of the one or more devices to a second user device of the one or more devices within the area.

Techniques to predict object behavior in an environment are discussed herein. For example, such techniques may include inputting data into a model and receiving an output from the model representing a discretized representation. The discretized representation may be associated with a probability of an object reaching a location in the environment at a future time. A vehicle computing system may determine a trajectory and a weight associated with the trajectory using the discretized representation and the probability. A vehicle, such as an autonomous vehicle, can be controlled to traverse an environment based on the trajectory and the weight output by the vehicle computing system.

Method and system for providing carbon offset sources. For example, the method includes determining an amount of total carbon emission of a user, receiving a desired percentage of carbon offset, determining a total number of carbon offset units corresponding to a predetermined carbon offset source, providing multiple carbon offset sources, receiving a respective number of carbon offset units corresponding to the predetermined carbon offset source for each of the multiple carbon offset sources, determining a respective cost for each of the multiple carbon offset sources, and providing a total amount of cost based upon the respective cost for each of the multiple carbon offset sources, where a total of the respective number of carbon offset units is equal to the total number of carbon offset units.

A method and an apparatus are disclosed for providing navigation instructions. The method may include receiving, from a user apparatus, a first location and a destination location; calculating a first route from the first location to the destination location; generating, for a predetermined time period, a first set of maneuvering data corresponding to the first route, the first set of maneuvering data comprising playback cues based on a predicted user apparatus location; transmitting the first set of maneuvering data to the user apparatus; receiving, from the user apparatus, a second location; generating, for a subsequent predetermined time period, a second set of maneuvering data, the second set of maneuvering data comprising playback cues based on a further predicted user apparatus location; calculating an update set of maneuvering data based on the first and second set of maneuvering data; and transmitting the update set of maneuvering data to the user apparatus.

A method for providing guided navigation for personal transport devices is described. In one embodiment, the method includes providing a list of predetermined destinations associated with a geographic area, projecting directions to one or more of the destinations on a ground surface located in front of a personal transport device, and providing an option to a user of the personal transport device to select between at least two different destinations. A direction associated with each destination of the at least two destinations may be projected on the ground surface located in front of the personal transport device. The method also includes receiving an input from the user indicating a selection of one of the at least two different destinations and projecting directions to the selected destination on the ground surface located in front of the personal transport device to guide the user to the selected destination.

A method, apparatus and computer program product are provided for improving user experiences for autonomous driving. In context of a method, the method determines one or more autonomous transition region parameters for a respective autonomous transition region along a route. The method also, based on the one or more autonomous transition region parameters, determines whether an action is to be performed by a vehicle in accordance with user preference data associated with a user. The method also causes the vehicle to perform the action in accordance with a determination that the action is to be performed by the vehicle.

A system and a computer-implemented method employ an appointment optimization and route planning system (AORPS) for optimizing home-visit appointments and related travel for delivering patient care. The AORPS receives registration and patient data from patients and client input including information about healthcare providers, onsite care coordinators, health plans, appointment types, and success rates from a client. The AORPS collates the patient data and generates an input matrix from the client input and the collated patient data. The AORPS generates a predictive model for appointments, capitation, and return on investment for delivering patient care based on appointment and patient history, feedback, and healthcare data. The AORPS generates an appointment schedule with travel routes dynamically based on optimization factors derived from the client input, the collated patient data, the input matrix, the healthcare data, and the predictive model, incorporating real-time changes in patient data, the client input, the optimization factors, and appointments.

A system includes at least one non-transitory storage medium storing a set of instructions and at least one processor in communication with the at least one non-transitory storage medium. When executing the set of instructions, the at least one processor may be directed to cause the system to obtain a service request signal sent from a user terminal via wireless communication, wherein the service request signal encodes identifier data, a first departure location, and a first departure time; retrieve one or more historical records related to the identifier data, wherein a historical record includes a historical departure location, historical departure time and a historical destination location; determine, using a pre-stored destination matching algorithm, a selection probability of the one or more historical destination location; determine, based on the selection probability, a suggested destination location, which is the same as the one or more historical destination locations.

In some implementations, a computing device can provide a map application providing a representation of a physical structure of venues (e.g., shopping centers, airports) identified by the application. In addition, the application can provide an inside view that includes the physical layout and geometry of the venue's structure as well as the location, structure and layout of points of interest (e.g., stores, security check points, restrooms) within the venue. The views become more detailed as the user zooms into the venue to reveal points of interest and to give the user a feel for traversing the venue.

Systems and methods are provided for estimating travel time and distance. Such method may comprise obtaining a vehicle trip dataset comprising an origin, a destination, a time-of-day, a trip time, and a trip distance associated with each of a plurality of trips, and training a neural network model with the vehicle trip dataset to obtain a trained model. The neural network model may comprise a first module and a second module, the first module may comprise a first number of neuron layers, the first module may be configured to obtain the origin and the destination as first inputs to estimate a travel distance, the second module may comprise a second number of neuron layers, and the second module may be configured to obtain the information of a last layer of the first module and the time-of-day as second inputs to estimate a travel time.