G06Q10/047

Network computer system to position transport providers using provisioning level determinations

A computer system operates to receive transport service requests from computing devices of requesters within a geographic region. The system matches each transport service request with an available transport provider operating a service vehicle within the geographic region, and determines a location bias for a first transport provider that operates a corresponding vehicle within the geographic region, the location bias being associated with a preferred location of the first transport provider. The system may then match the first transport provider to a transport service request based on (i) the location bias of the first transport provider, and (ii) a destination of the transport service request which, upon fulfilling the transport service request, results in the first transport provider being positioned to arrive at the preferred location within a future time interval.

SYSTEM AND METHOD FOR ENHANCED VIRTUAL QUEUING

A system and method for managing virtual queues. A cloud-based queue service manages a plurality of queues hosted by one or more entities. The queue service is in constant communication with the entities providing queue management, queue analysis, and queue recommendations. The queue service is likewise in direct communication with queued persons. Sending periodic updates while also motivating and incentivizing punctuality and minimizing wait times based on predictive analysis. The predictive analysis uses “Big Data” and other available data resources, for which the predictions assist in the balancing of persons across multiple queues for the same event or multiple persons across a sequence of queues for sequential events.

SOLVING ROUTING PROBLEMS USING MACHINE LEARNING

The techniques disclosed herein enable systems to solve routing problems using machine learning augmented by optimization modules. To plot a route, a system receives a plurality of nodes from a problem space. The plurality of nodes is then analyzed by an optimization module and ranked based on various criteria such as distance from a reference node and deadline. Based on the ranking, the optimization module can select a smaller subset of nodes that is then processed by a machine learning model. The machine learning model can then select a node from the subset of nodes for addition to a route. This process can be repeated until a route is plotted for the full set of nodes within the problem space. In addition, the system can be configured to monitor current conditions of the problem space to modify the route in response to changes.

SYSTEM AND METHOD FOR ENHANCED VIRTUAL QUEUING

A system and method for managing virtual queues. A cloud-based queue service manages a plurality of queues hosted by one or more entities. The queue service is in constant communication with the entities providing queue management, queue analysis, and queue recommendations. The queue service is likewise in direct communication with queued persons. Sending periodic updates while also motivating and incentivizing punctuality and minimizing wait times based on predictive analysis. The predictive analysis uses “Big Data” and other available data resources, for which the predictions assist in the balancing of persons across multiple queues for the same event or multiple persons across a sequence of queues for sequential events. Furthermore, the system utilizes a virtual agent engine and various predictive models to schedule and execute callbacks between a person in a virtual queue and a virtual agent based on predictive model results.

Management system and management method

It is possible to manage information on a city area in a centralized manner and reduce a processing load. A management system includes: information acquisition means that is provided in infrastructure of a predetermined city area and acquire information on the city area; service providing means sending instructions to respective mobile bodies for providing a plurality of different conveyance services, each of the mobile bodies including a sensor configured to detect the information on the city area and moving in the city area based on the information detected by the sensor, thereby providing each of the conveyance services; and instruction means for sending an instruction to the service providing means based on the information on the city area acquired by the information acquisition means.

Task allocation for vehicles

Methods and apparatus are provided for allocating tasks to be performed by one or more autonomous vehicles to achieve a mission objective. Generally, a task allocation system identifies a final task associated with a given mission objective, identifies predecessor tasks necessary to complete the final task, generates one or more candidate tasks sequences to accomplish the mission objective, generates a task allocation tree based on the candidate task sequences, and searches the task allocation tree to find a task allocation plan that meets a predetermined selection criteria (e.g., lowest cost). Based on the task allocation plan, the task allocation system determines a task execution plan and generates control data for controlling one or more autonomous vehicles to complete the task execution plan.

Parallel solution generation
11694129 · 2023-07-04 · ·

The application describes parallel solution generation. A data processing apparatus includes a memory including a computer program code, and at least two processors configured to execute the computer program code. The computer program code includes a component program run in parallel on at least two processors to generate solution components compiled in parallel of points, and to store the added solution components in the memory; and a solution program run in parallel on at least two processors to generate a solution by adding one solution component at a time, read from the memory, to the solution based on a key point, and to store the added solution component to the solution in the memory.

Parallel solution generation
11694129 · 2023-07-04 · ·

The application describes parallel solution generation. A data processing apparatus includes a memory including a computer program code, and at least two processors configured to execute the computer program code. The computer program code includes a component program run in parallel on at least two processors to generate solution components compiled in parallel of points, and to store the added solution components in the memory; and a solution program run in parallel on at least two processors to generate a solution by adding one solution component at a time, read from the memory, to the solution based on a key point, and to store the added solution component to the solution in the memory.

Automatic discovery of optimal routes for flying cars and drones
11692837 · 2023-07-04 · ·

One or more potential drone and/or flying car (DFC) corridors are identified based on the topology of a road network. Trajectories traveled by vehicles are determined from a plurality of instances of probe data received from a plurality of vehicle apparatuses onboard the vehicles. A volume of traffic for a path through the road network and corresponding to a potential DFC corridor is determined based on the trajectories. A delay metric for the path through the road network and corresponding to the potential DFC corridor is determined based on the trajectories. A traffic metric is then determined for the path based on a combination of the volume of traffic, the delay metric and a measure of the topology of the road network. The one or more potential DFC corridors are ranked by their corresponding traffic metrics.

Automatic discovery of optimal routes for flying cars and drones
11692837 · 2023-07-04 · ·

One or more potential drone and/or flying car (DFC) corridors are identified based on the topology of a road network. Trajectories traveled by vehicles are determined from a plurality of instances of probe data received from a plurality of vehicle apparatuses onboard the vehicles. A volume of traffic for a path through the road network and corresponding to a potential DFC corridor is determined based on the trajectories. A delay metric for the path through the road network and corresponding to the potential DFC corridor is determined based on the trajectories. A traffic metric is then determined for the path based on a combination of the volume of traffic, the delay metric and a measure of the topology of the road network. The one or more potential DFC corridors are ranked by their corresponding traffic metrics.