A micromobility transit vehicle service task management system and related methods are disclosed. In one embodiment, a system determines service tasks to be executed based on a level of availability of one or more micromobility transit vehicles. A value for each of the tasks is determined based on a cost to perform the task and value generated by an increase in availability of the one or more micromobility transit vehicles, for dynamic transportation matching, from execution of the task. The tasks may be prioritized into an order of execution that maximizes a total of the values of the tasks. The determined values of the tasks may be adjusted in the prioritization of the tasks based on the order of execution of the tasks. A navigational task route may be generated based on the prioritized tasks and assigned to a technician device to guide a technician to each of the tasks.

A computer-implemented method of generating and broadcasting telematics and/or image data is provided. Telematics and/or image data may be collected, with customer permission, in real-time by a mobile device (or a Telematics App running thereon) traveling within an originating vehicle. The telematics data may include acceleration, braking, speed, heading, and location data associated with the originating vehicle. The mobile device may generate an updated telematics data broadcast including up-to-date telematics data at least every few seconds; and then broadcast the updated telematics data broadcast at least every few seconds via wireless communication to another computing device to facilitate alerting another vehicle or driver of an abnormal traffic condition or event that the originating vehicle is experiencing. An amount that an insured uses or otherwise employs the telematics data-based risk mitigation or prevention functionality may be used with usage-based insurance, or to calculate or adjust insurance premiums or discounts.

Systems and methods are directed to allocating unused or otherwise under-utilized computing resources of autonomous vehicles. In one example, a computer-implemented method obtaining, by a computing system, data describing a computational status of each autonomous vehicle of one or more autonomous vehicles describing a current or forecasted computational load. The method includes determining, by the computing system, an amount of excess computational capacity of each autonomous vehicle of the one or more autonomous vehicles, the amount of excess computational capacity for each autonomous vehicle of the one or more autonomous vehicles based at least in part on the computational status of the autonomous vehicle and a total computational capacity of the autonomous vehicle. The method includes allocating, by the computing system, at least a portion of the amount of excess computational capacity of each autonomous vehicle to processing operations associated with participation in a distributed ledger.

Aspects of the present disclosure include a navigation system and computer-implemented methods for proactively re-routing vehicles based on an analysis of input component data obtained from the navigation-enabled devices. The navigation system scores the input component data to obtain a measure of frustration (e.g., a feeling of being upset or annoyed) of the user of the navigation-enabled device. The navigation system may provide a detour suggestion for display on the navigation-enabled device to persuade the user of the device to direct their vehicle to depart from its current location or route in an effort to remove the vehicle from traffic, and thereby reduce the frustration level of the user. The detour suggestion may include an alternative route to the original destination, or an alternative destination.

An information processing apparatus determines a pickup point and a drop-off point for a first user traveling to a destination in a vehicle carrying a plurality of unspecified users. The apparatus includes a controller that obtains information on the place of departure and the destination of the first user; determines a pickup point for the first user based on the place of departure of the first user; defines a predetermined field including the destination of the first user and determines a drop-off point for the first user from a plurality of points except the destination, the points being included in the predetermined field; and transmits the determined pickup point and drop-off point for the first user to a device associated with the vehicle.

The present disclosure relates to a method and system for monitoring on route transportations. The method includes obtaining a driving route of a target vehicle; obtaining a reference position on the driving route away from a first current position of the target vehicle; determining a second current position of the target vehicle after a reference time; determining a distance between the second current position and the reference position is greater than a preset distance; and sending a signal to a target terminal indicating that the target vehicle is off-route.

Location technologies are combined with other information systems to provide augmented information for individuals such as a traveler in an automobile.

An autonomous drive instruction device shortens the time required for vehicles to arrive at a designated location from a parking location in a parking lot without a navigation map. The autonomous drive instruction device includes a travel-direction determiner and an autonomous drive instructor. The travel-direction determiner determines one path as the travel direction of the vehicle on the basis of the designated location and information on paths in a branch area. The one path corresponds to an extension direction that forms a smaller one of angles formed by extension directions of the paths from the branch area and a designated-location direction from the branch area to the designated location. The autonomous drive instructor outputs instruction information including information on the travel direction to the autonomous drive control device such that the autonomous dive control device controls the vehicle to move in the travel direction by autonomous driving.

A navigation method, an electronic device, and a storage medium, which are related to a field of artificial intelligence, such as depth learning, maps, and navigation. The specific implementation scheme includes: obtaining a parking space located in an indoor parking lot in response to an operation acquired based on a map application, generating an indoor-outdoor navigation route in the map application by taking the parking space as a destination address in the indoor-outdoor navigation route, and navigating a vehicle driven by a user to the parking space according to the indoor-outdoor navigation route.

The present disclosure may provide a method for route planning. The method may include obtaining a start location and a destination of a target vehicle. The method may also include obtaining a map of a target region including the start location and the destination. The map may include node information of each of a plurality of nodes. Further, the method may include obtaining motion status information associated with one or more vehicles other than the target vehicle in the target region. The method may further include determining a target route of the target vehicle based at least in part on the start location, the destination, the motion status information associated with the one or more vehicles, and the map.