Abstract: There is provided a system and method for grouping a plurality of individuals, each individual of the plurality of individuals having a corresponding transactional segment, the system comprising a memory storing a group identification application, a processor for executing the group identification application to identify an o-space center of a first group, wherein the o-space center is an intersection of a plurality of transactional segments, obtain a non-parametric lower-body orientation probability distribution for each of the plurality of individuals, based on the o-space center, and determine that a first plurality of individuals from the plurality of individuals belong to the first group based on the non-parametric lower-body orientation probability distribution of each individual of the plurality of individuals, wherein each of the first plurality of individuals has a corresponding one of the plurality of transactional segments that intersect with one another.

Abstract: There is provided a system and method for grouping a plurality of individuals, each individual of the plurality of individuals having a corresponding transactional segment, the system comprising a memory storing a group identification application, a processor for executing the group identification application to identify an o-space center of a first group, wherein the o-space center is an intersection of a plurality of transactional segments, obtain a non-parametric lower-body orientation probability distribution for each of the plurality of individuals, based on the o-space center, and determine that a first plurality of individuals from the plurality of individuals belong to the first group based on the non-parametric lower-body orientation probability distribution of each individual of the plurality of individuals, wherein each of the first plurality of individuals has a corresponding one of the plurality of transactional segments that intersect with one another.

Abstract: There is provided a system and method for grouping a plurality of individuals, each individual of the plurality of individuals having a corresponding transactional segment, the system comprising a memory storing a group identification application, a processor for executing the group identification application to identify an o-space center of a first group, wherein the o-space center is an intersection of a plurality of transactional segments, obtain a non-parametric lower-body orientation probability distribution for each of the plurality of individuals, based on the o-space center, and determine that a first plurality of individuals from the plurality of individuals belong to the first group based on the non-parametric lower-body orientation probability distribution of each individual of the plurality of individuals, wherein each of the first plurality of individuals has a corresponding one of the plurality of transactional segments that intersect with one another.

Abstract: There is provided a system and method for grouping a plurality of individuals, each individual of the plurality of individuals having a corresponding transactional segment, the system comprising a memory storing a group identification application, a processor for executing the group identification application to identify an o-space center of a first group, wherein the o-space center is an intersection of a plurality of transactional segments, obtain a non-parametric lower-body orientation probability distribution for each of the plurality of individuals, based on the o-space center, and determine that a first plurality of individuals from the plurality of individuals belong to the first group based on the non-parametric lower-body orientation probability distribution of each individual of the plurality of individuals, wherein each of the first plurality of individuals has a corresponding one of the plurality of transactional segments that intersect with one another.

Abstract: Systems, apparatuses, methods, and software for collecting and disseminating crowd-sourced information relating to one or more shared vehicles, such as buses, passenger trains, subway vehicles, streetcars, etc. The crowd-sourced information is collected via mobile client devices carried by users, such a riders of the shared vehicle at issue. Information collected includes tracing data for tracing the route and timing of each shared vehicles. The tracing data is used to update a computer model that helps predict arrival/departure times. The predicted arrival times can be conveyed to users and to allow people to arrange rendezvous events. Other information collected includes user-report information on items such as condition of the shared vehicle, fullness of the vehicle, and the user's experience with the vehicle and/or corresponding infrastructure. Collected user-report information can be shared with other users and/or a customer service system affiliated with the shared vehicle.