A system for transportation includes a vehicle having a user interface, and a robotic process automation system wherein a set of data is captured for each user in a set of users as each user interacts with the user interface, and wherein an artificial intelligence system is trained using the set of data to interact with the vehicle to automatically undertake actions with the vehicle on behalf of the user.

A method of optimizing an operating state of a vehicle includes classifying, using a first neural network of a hybrid neural network, social media data sourced from a plurality of social media sources as affecting a transportation system. The method further includes predicting, using a second neural network of the hybrid neural network, one or more effects of the classified social media data on the transportation system. The method further includes optimizing, using a third neural network of the hybrid neural network, a state of at least one vehicle of the transportation system, wherein the optimizing addresses an influence of the predicted one or more effects on the at least one vehicle.

A navigation prompt message method includes acquiring a planned driving path including a first intersection and a second intersection to be passed successively. The method further includes, in response to the second intersection being located within a distance threshold of the first intersection, acquiring lane information of a connecting road between the first intersection and the second intersection. In response to the second intersection being located within a distance threshold of the first intersection, the method further includes determining a recommended driving lane on the connecting road based on the lane information, and generating, before a vehicle passes through the first intersection, a navigation prompt message indicating the recommended driving lane the navigation prompt message guiding the vehicle to drive on the recommended driving lane after passing through the first intersection.

A movable body control system (SYS) includes first and second movable bodies (1#1, 1#2) that are movable in a predetermined area (TA) in which a wireless communication network (NW) is built; and a control apparatus (3) for controlling the first and second movable bodies through the wireless communication network, the control apparatus includes: a storage unit (32) for storing a first communication quality information that indicates a communication quality in the predetermined area when the first movable body exists in each of a plurality of different locations in the predetermined area; a generation unit (311) for generating, based on the first communication quality information, a target moving route (TGT#2) that allows the second movable body to move while avoiding a first low quality location (DA_low1) at which the communication quality does not reach a desired quality due to the first movable body; and a control unit (312) for controlling the second movable body so that the second movable body moves along the target moving route.

A method for matching a vehicle with a user including receiving a user ride request for a vehicle from a plurality of available vehicles from a user, receiving a threshold vehicle risk score preference for the user, receiving a user risk score for the user, receiving a threshold user risk score preference for the plurality of available vehicles, identifying a subset of the plurality of available vehicles having a vehicle risk score at or below the threshold vehicle risk score preference of the user and a threshold user risk score preference at or above the user risk score of the user, and presenting the user with ride options for selecting one of the subset of the plurality of available vehicles of the subset of available vehicles for the user ride request.

Systems and methods in accordance with aspects of this disclosure may be provided to determine and calculate an overall driving risk index value corresponding to a driver and scene configuration. The overall driving risk index value may provide driving risk modeling and estimation at a personalized driving level. In some cases, the overall driving risk index value may be determined using a risk-predictive modeling system with weighting and machine learning and may include one or more of: a driver score system, a driver-contextual risk score system, and a conflict index system.

Described herein are technologies relating to computing a likelihood of an operation-influencing event with respect to an autonomous vehicle at a geographic location. The likelihood of the operation-influencing event is computed based upon a prediction of a value that indicates whether, through a causal process, the operation-influencing event is expected to occur. The causal process is identified by means of a model, which relates spatiotemporal factors and the operation-influencing events.

Current data for a geographic area is accessed. The current data comprises at least one of (a) current traffic data for the geographic area, (b) current incident data for the geographic area, or (c) current weather data for the geographic area. Based on the current data, autonomous driving instructions are determined for the geographic area. A notification comprising the autonomous driving instructions is provided such that the notification is received by a vehicle apparatus located within the geographic area or expected to enter the geographic area based on a route being traversed by a vehicle corresponding to the vehicle apparatus. The vehicle apparatus is onboard the vehicle and is configured to control the vehicle in accordance with the autonomous driving instructions.

A system for preventing abnormal acceleration of a vehicle includes a device configured such that in a state in which the vehicle is stopped while the vehicle is turned on, the device is configured to determine whether abnormal acceleration prevention is necessary based on a final destination or a current position of the vehicle before the vehicle is turned off to thereby limit a vehicle speed. The system and a method for preventing abnormal operation of the vehicle can prevent a vehicle accident due to the abnormal acceleration caused by misoperation by a driver, such as misoperation of an accelerator pedal of the vehicle.

An apparatus, method and computer program product are provided for providing signature reduction for a vehicle. For example, the apparatus receives a destination for a vehicle as input, selects a subset from a plurality of road segments as a route from a location to the destination, and outputs the route or a portion thereof. The subset is selected based on association of each of the plurality of road segments with respect to a source, and the source is capable of acquiring vehicle signature information.