Abstract: Embodiments for self-managed adaptable models for prediction systems by one or more processors. One or more adaptive models may be applied to data streams from a plurality of data sources according to one or more data recipes such that the one or more adaptive models predict a plurality of target variables.

Abstract: Embodiments for targeted learning and recruitment by a processor. Attributes obtained from a user profile are used to identify a user as a potential candidate for performing an activity related to either the recruiting or the learning and providing a customized learning experience with targeted course suggestions for the user.

Abstract: A diagnosis system for an adaptive signal control system in a network, the diagnosis system including a traffic state identification device configured to estimate a traffic state describing a supply-demand mismatch by identifying a relationship between real time data feed from a sensor and a control strategy of the adaptive signal control system and a network transition model device configured to diagnose the supply-demand mismatch and an evolution of the supply-demand mismatch on a network level based on the relationship and infrastructure data of the network.

Abstract: Embodiments for network reconstruction from message data by a processor. A digital map may be created using one or more messages of a plurality of vehicles obtained at a plurality of control points of a route network. The digital map may be analyzed to estimate a feasibility of simultaneous trajectories of the plurality of vehicles between selected locations in the route network.

Abstract: Embodiments for self-managed adaptable models for prediction systems by one or more processors. One or more adaptive models may be applied to data streams from a plurality of data sources according to one or more data recipes such that the one or more adaptive models predict a plurality of target variables.

Abstract: Embodiments for network reconstruction from message data by a processor. A digital map may be created using one or more messages of a plurality of vehicles obtained at a plurality of control points of a route network. The digital map may be analyzed to estimate a feasibility of simultaneous trajectories of the plurality of vehicles between selected locations in the route network.

Abstract: Embodiments for targeted learning and recruitment by a processor. Attributes obtained from a user profile are used to identify a user as a potential candidate for performing an activity related to either the recruiting or the learning and providing a customized learning experience with targeted course suggestions for the user.

Abstract: A diagnosis system for an adaptive signal control system in a network, the diagnosis system including a traffic state identification device configured to estimate a traffic state describing a supply-demand mismatch by identifying a relationship between real time data feed from a sensor and a control strategy of the adaptive signal control system and a network transition model device configured to diagnose the supply-demand mismatch and an evolution of the supply-demand mismatch on a network level based on the relationship and infrastructure data of the network.

Abstract: A diagnosis system for an adaptive signal control system in a network, the diagnosis system including a traffic state identification device configured to estimate a traffic state describing a supply-demand mismatch by identifying a relationship between real time data feed from a sensor and a control strategy of said adaptive signal control system and a network transition model device configured to diagnose the supply-demand mismatch and an evolution of the supply-demand mismatch on a network level based on said relationship and infrastructure data of the network.

Abstract: Embodiments of the disclosure include a method for journey planning including receiving a journey planning request, the journey planning request having an origin and a destination in a transportation network. The method also includes calculating an optimized journey plan by identifying a plurality of routes through the transportation network from the origin to the destination and determining an uncertainty associated with each of the plurality of routes. Calculating an optimized journey plan also includes evaluating a robustness of each of the plurality of routes to the uncertainty associated with each of the plurality of routes and selecting the optimized journey plan based on the journey planning request and the robustness of each of the plurality of routes.

Abstract: A diagnosis system for an adaptive signal control system in a network, the diagnosis system including a traffic state identification device configured to estimate a traffic state describing a supply-demand mismatch by identifying a relationship between real time data feed from a sensor and a control strategy of said adaptive signal control system and a network transition model device configured to diagnose the supply-demand mismatch and an evolution of the supply-demand mismatch on a network level based on said relationship and infrastructure data of the network.

Abstract: A diagnosis system for an adaptive signal control system in a network, the diagnosis system including a traffic state identification device configured to estimate a traffic state describing a supply-demand mismatch by identifying a relationship between real time data feed from a sensor and a control strategy of said adaptive signal control system and a network transition model device configured to diagnose the supply-demand mismatch and an evolution of the supply-demand mismatch on a network level based on said relationship and infrastructure data of the network.

Abstract: Embodiments of the disclosure include a computer system for journey planning, the computer system includes a journey planning server configured to perform a method. The method includes receiving a journey planning request, the journey planning request having an origin and a destination in a transportation network. The method also includes calculating an optimized journey plan by identifying a plurality of routes through the transportation network from the origin to the destination and determining an uncertainty associated with each of the plurality of routes. Calculating an optimized journey plan also includes evaluating a robustness of each of the plurality of routes to the uncertainty associated with each of the plurality of routes and selecting the optimized journey plan based on the journey planning request and the robustness of each of the plurality of routes.

Abstract: Embodiments of the disclosure include a method for journey planning including receiving a journey planning request. The request includes an origin and a destination in a transportation network. The method also includes calculating an optimized journey plan based on the journey planning request and a route map corresponding to the transportation network and identifying a potential event in the transportation. The method further includes monitoring the transportation network for the potential event and based on detecting an execution of the potential event, calculating an improved journey plan.

Abstract: Embodiments of the disclosure include a method for providing a consolidated estimated time of arrival in a scheduled transportation system. The method includes receiving at least one of a scheduled time of arrival, a real-time estimated time of arrival and a predictive estimated time of arrival and assigning a weight to each of the scheduled time of arrival, the real-time estimated time of arrival and the predictive estimated time of arrival. The method also includes calculating a confidence level and the consolidated estimated time of arrival based on the weights and the scheduled time of arrival, the real-time estimated time of arrival and the predictive estimated time of arrival.

Abstract: Embodiments of the disclosure include a method for providing a consolidated estimated time of arrival in a scheduled transportation system. The method includes receiving at least one of a scheduled time of arrival, a real-time estimated time of arrival and a predictive estimated time of arrival and assigning a weight to each of the scheduled time of arrival, the real-time estimated time of arrival and the predictive estimated time of arrival. The method also includes calculating a confidence level and the consolidated estimated time of arrival based on the weights and the scheduled time of arrival, the real-time estimated time of arrival and the predictive estimated time of arrival.

Abstract: A system and method for workload generation include a processor for identifying a workload model by determining each of a hierarchy for workload generation, time scales for workload generation, and states and transitions at each of the time scales, and defining a parameter by determining each of fields for user specific attributes, application specific attributes, network specific attributes, content specific attributes, and a probability distribution function for each of the attributes; a user level template unit corresponding to a relatively slow time scale in signal communication with the processor; an application level template corresponding to a relatively faster time scale in signal communication with the processor; a stream level template corresponding to a relatively fastest time scale in signal communication with the processor; and a communications adapter in signal communication with the processor for defining a workload generating unit responsive to the template units.

Abstract: Embodiments of the disclosure include a method for de-noising data in a scheduled transportation system, the method includes receiving a plurality of digital traces that correspond to a piece of equipment in the scheduled transportation system. The method also includes identifying a plurality of journeys from the plurality of digital traces, wherein each of the plurality of journeys corresponds to the piece of equipment traversing one of a plurality of routes and generating a route map and schedule for the scheduled transportation system from the plurality of journeys and the plurality of digital traces.

Abstract: Embodiments of the disclosure include a method for providing a consolidated estimated time of arrival in a scheduled transportation system. The method includes receiving at least one of a scheduled time of arrival, a real-time estimated time of arrival and a predictive estimated time of arrival and assigning a weight to each of the scheduled time of arrival, the real-time estimated time of arrival and the predictive estimated time of arrival. The method also includes calculating a confidence level and the consolidated estimated time of arrival based on the weights and the scheduled time of arrival, the real-time estimated time of arrival and the predictive estimated time of arrival.

Abstract: Embodiments of the disclosure include a method for providing a consolidated estimated time of arrival in a scheduled transportation system. The method includes receiving at least one of a scheduled time of arrival, a real-time estimated time of arrival and a predictive estimated time of arrival and assigning a weight to each of the scheduled time of arrival, the real-time estimated time of arrival and the predictive estimated time of arrival. The method also includes calculating a confidence level and the consolidated estimated time of arrival based on the weights and the scheduled time of arrival, the real-time estimated time of arrival and the predictive estimated time of arrival.