Abstract: Systems and methods for allocating resources in a transportation system are disclosed. A vehicle of the transportation system may be dispatched by one or more processors; first and second portions of the vehicle are allocated to first and second groups of users. A parameter of the first group of users may be tracked at a first location. Part of the second portion of the vehicle may be reallocated to the first group of users, in real-time, when the tracked parameter of the first group of users exceeds a threshold.

Abstract: The disclosed embodiments illustrate methods and systems for predicting demand of vehicles in a transportation network. The method includes determining demand events at each of one or more locations for time intervals based on historical demand data. The demand events correspond to a demand of vehicles at one or more locations during plurality of time intervals throughout a day. The method includes creating a graph comprising nodes, and edges connecting nodes, each node being representative of a demand event from demand events. An edge is representative of dependency between two demand events from demand events. The method includes predicting demand of vehicles at a location from one or more locations during a predetermined time interval based on the graph and a real time demand of vehicles associated with other demand event. The method includes displaying demand prediction on a computing device at one or more locations of transportation network.

Abstract: The disclosed embodiments illustrate a method for real time management of transportation services. The method includes determining a discrete control process with respect to a plurality of states of a vehicle. Each state in the plurality of states corresponds to a station and a count of vacant seats in the vehicle at the station. A set of rules is generated to maximize a key performance parameter of the vehicle, based on at least the determined discrete control process. A valuation parameter is determined, in real time, for one or more vacant seats in the vehicle at each of one or more subsequent stations based on the generated set of rules. The determined valuation parameter for the one or more vacant seats corresponding to each of the one or more subsequent stations is transmitted to a plurality of mobile computing devices associated with a plurality of commuters.

Abstract: The disclosed embodiments illustrate methods and systems for predicting demand of vehicles in a transportation network. The method includes determining demand events at each of one or more locations for time intervals based on historical demand data. The demand events correspond to a demand of vehicles at one or more locations during plurality of time intervals throughout a day. The method includes creating a graph comprising nodes, and edges connecting nodes, each node being representative of a demand event from demand events. An edge is representative of dependency between two demand events from demand events. The method includes predicting demand of vehicles at a location from one or more locations during a predetermined time interval based on the graph and a real time demand of vehicles associated with other demand event. The method includes displaying demand prediction on a computing device at one or more locations of transportation network.

Abstract: The disclosed embodiments illustrate methods and systems for predicting demand of vehicles in a transportation network. The method includes determining demand events at each of one or more locations for time intervals based on historical demand data. The demand events correspond to a demand of vehicles at one or more locations during plurality of time intervals throughout a day. The method includes creating a graph comprising nodes, and edges connecting nodes, each node being representative of a demand event from demand events. An edge is representative of dependency between two demand events from demand events. The method includes predicting demand of vehicles at a location from one or more locations during a predetermined time interval based on the graph and a real time demand of vehicles associated with other demand event. The method includes displaying demand prediction on a computing device at one or more locations of transportation network.

Abstract: Systems and methods for allocating resources in a transportation system are disclosed. A vehicle of the transportation system may be dispatched by one or more processors; first and second portions of the vehicle are allocated to first and second groups of users. A parameter of the first group of users may be tracked at a first location. Part of the second portion of the vehicle may be reallocated to the first group of users, in real-time, when the tracked parameter of the first group of users exceeds a threshold.

Abstract: The disclosed embodiments illustrate methods and systems for determining an effect of a weather condition on a transportation network. The method includes receiving one or more parameters of the weather condition in a geographical area for a predetermined time-period. The method further includes determining a delay from a scheduled time of arrival of one or more vehicles, associated with the transportation network, at a location from one or more locations, in the transportation network, in the geographical area for the predetermined time-period. Thereafter, a sensitivity of the one or more locations to the weather condition of the geographical area is determined by correlating the delay with the one or more parameters of the weather condition. Further, the sensitivity of the one or more locations is displayed, through a user interface, as a first layer overlaid on a map of the geographical area.

Abstract: Methods and systems for tracking a target vehicle. GPS data can be obtained from multiple vehicles in the vicinity of a target vehicle. Such GPS data can include GPS signals associated with the multiple vehicles and GPS signals associated with the target vehicle. The GPS signals associated with the multiple vehicles can be fused, and a prediction made about the travel time of the target vehicle based on the GPS signals associated with multiple vehicles and the GPS signals associated with the target vehicle. The GPS data provides a redundancy that increases the accuracy and robustness of the prediction.

Abstract: The disclosed embodiments illustrate method and system for managing a dispatch of vehicles based on generation of a dispatch schedule. The method includes generating a dispatch schedule for one or more vehicles at one or more time instants based on a first demand for the one or more vehicles along a route. For a current time instant, the method includes predicting a second demand for the one or more vehicles at each of the one or more stations, at time instants subsequent to the current time instant, based on a current demand. The method further includes updating the dispatch schedule by varying the count of vehicles to be dispatched from the first station based at least on the second demand. Further, the method includes transmitting a notification to a computing device installed in each of the one or more vehicles.

Abstract: The disclosed embodiments illustrate a method for real time management of transportation services. The method includes determining a discrete control process with respect to a plurality of states of a vehicle. Each state in the plurality of states corresponds to a station and a count of vacant seats in the vehicle at the station. A set of rules is generated to maximize a key performance parameter of the vehicle, based on at least the determined discrete control process. A valuation parameter is determined, in real time, for one or more vacant seats in the vehicle at each of one or more subsequent stations based on the generated set of rules. The determined valuation parameter for the one or more vacant seats corresponding to each of the one or more subsequent stations is transmitted to a plurality of mobile computing devices associated with a plurality of commuters.

Abstract: The disclosed embodiments illustrate methods and systems for recommending one or more vehicles, commuting on a predefined route, for one or more requestors. The method includes determining a first additional distance traversable by each vehicle apart from the predefined route to accommodate each requestor. Further, a graph comprising a first set of nodes representing the one or more requestors, and a second set of nodes representing the one or more vehicles, is generated. Thereafter, a mapping between the first set of nodes and the second set of nodes is determined based on the first additional distance. The mapping corresponds to an allocation of a requestor to a vehicle such that an additional distance traversable by the vehicle is less than an additional distance traversable by remaining vehicles apart from the predefined route. Thereafter, the one or more vehicles are recommended for the one or more requestors based on the mapping.

Abstract: The disclosed embodiments illustrate methods of data processing for real-time prediction of crowdedness in vehicles in transit. The method includes receiving a current location of a vehicle, a real-time traffic information along a route of transit, and a current passenger demand at a first subsequent station and a second subsequent station. The method includes predicting a dwell time for the vehicle corresponding to the first subsequent station. The method includes predicting an arrival time instant of the vehicle at the second subsequent station based on a predicted first travel time of the vehicle, a predicted second travel time of the vehicle, and the predicted dwell time. The method includes predicting a passenger occupancy of the vehicle at the predicted arrival time instant at the second subsequent station based on at least a first passenger demand, a second passenger demand associated with the second subsequent station, and a passenger alighting pattern.

Abstract: The disclosed embodiments illustrate method and system for managing a dispatch of vehicles based on generation of a dispatch schedule. The method includes generating a dispatch schedule for one or more vehicles at one or more time instants based on a first demand for the one or more vehicles along a route. For a current time instant, the method includes predicting a second demand for the one or more vehicles at each of the one or more stations, at time instants subsequent to the current time instant, based on a current demand. The method further includes updating the dispatch schedule by varying the count of vehicles to be dispatched from the first station based at least on the second demand. Further, the method includes transmitting a notification to a computing device installed in each of the one or more vehicles.

Abstract: The disclosed embodiments illustrate methods and systems for prediction of a communication channel for communication with customer service. The method includes monitoring, by one or more sensors in a server, a communication involving at least a first user for a pre-defined time period. The one or more types of communication channels being used by at least the first user over the pre-defined time period and/or the one or more types of problems reported by at least the first user, is monitored. The method further includes generating, by one or more processors of the server, a temporal data based on the monitoring. The classifier is trained by the one or more processors, based on the generated temporal data. The classifier predicts a likelihood of selection of a type of communication channels from the one or more types of communication channels, for communication between the first user and the server.

Abstract: A method and a system are provided to derive one or more observations between a plurality of parameters in customer care data. The method includes receiving customer care data from a plurality of data sources. Thereafter the customer care data is transformed to create a plurality of data structures utilizing one or more semantic web protocols. The plurality of data structures represents a relationship between one or more parameters in the customer care data. Thereafter a subset of data structures is extracted from the plurality of data structures based on a query received via a query interface. One or more graph analytics techniques are applied on the subset of data structures to determine one or more observations associated with the subset of data structures. Thereafter the one or more observations pertaining to the subset of data structures are displayed on a display screen.

Abstract: The disclosed embodiments illustrate methods and systems for scheduling one or more first vehicles along a route in a transportation system. The method includes determining one or more demands pertaining to a commutation along a route, where the route comprises at least one pair of stations such that there is a unique path between the pair of stations. The method further includes determining a set of constraints associated with the transportation system. The set of constraints are based on at least a count of second vehicles plying on one or more routes in the transportation system at a time instance, a capacity of a first vehicle, and a performance metric of the transportation system. Further, the method includes determining a count of first vehicles, for plying along the route at the time instance, based on at least the set of constraints.

Abstract: Methods and systems for collaborative location tracking. Commuters can be organized into a group according to commuter client devices (e.g., smartphones, tablet computing devices, etc.) respectively associated with the commuters. The commuter client devices are tracked as a group rather than individually and based on power efficient context-aware location data derived from the commuter client devices and a generated trip plan in association with data indicative of real-time dynamics so that power usage of individual commuter client devices is rationally minimized.

Abstract: The disclosed embodiments illustrate methods and systems for scheduling one or more first vehicles along a route in a transportation system. The method includes determining one or more demands pertaining to a commutation along a route, where the route comprises at least one pair of stations such that there is a unique path between the pair of stations. The method further includes determining a set of constraints associated with the transportation system. The set of constraints are based on at least a count of second vehicles plying on one or more routes in the transportation system at a time instance, a capacity of a first vehicle, and a performance metric of the transportation system. Further, the method includes determining a count of first vehicles, for plying along the route at the time instance, based on at least the set of constraints.

Abstract: The disclosed embodiments illustrate methods and systems for recommending one or more vehicles, commuting on a predefined route, for one or more requestors. The method includes determining a first additional distance traversable by each vehicle apart from the predefined route to accommodate each requestor. Further, a graph comprising a first set of nodes representing the one or more requestors, and a second set of nodes representing the one or more vehicles, is generated. Thereafter, a mapping between the first set of nodes and the second set of nodes is determined based on the first additional distance. The mapping corresponds to an allocation of a requestor to a vehicle such that an additional distance traversable by the vehicle is less than an additional distance traversable by remaining vehicles apart from the predefined route. Thereafter, the one or more vehicles are recommended for the one or more requestors based on the mapping.

Abstract: The disclosed embodiments illustrate methods and systems for determining an effect of a weather condition on a transportation network. The method includes receiving one or more parameters of the weather condition in a geographical area for a predetermined time-period. The method further includes determining a delay from a scheduled time of arrival of one or more vehicles, associated with the transportation network, at a location from one or more locations, in the transportation network, in the geographical area for the predetermined time-period. Thereafter, a sensitivity of the one or more locations to the weather condition of the geographical area is determined by correlating the delay with the one or more parameters of the weather condition. Further, the sensitivity of the one or more locations is displayed, through a user interface, as a first layer overlaid on a map of the geographical area.