Abstract: Techniques and systems are disclosed for receiving user input related to three co-optimized objectives, factors, or parameters, and translating the user input into weight factors for a tri-variable weighting function. In various embodiments, a triangular user interface element is displayed that allows a user to assign importance weights to three interrelated decision optimization objectives using a single user input selection gesture. Each side of the triangular user interface element presents a factor of the weight function. When the user selects a single position on the perimeter or within the field of the triangular figure in the user interface, weight factors for each of the three interrelated optimization objectives are determined that can be used as weight factors in the tri-variable weighting function.

Abstract: Systems and techniques are described to enable the dynamic selection of a transit route through the stop zones of a transit line. Techniques are disclosed for receiving a current location of a transit vehicle on a transit line and determining a transit route through one or more of the vehicle's remaining stop zones by choosing an optimized combination of stop options and route segment options for that specific transit vehicle. Techniques may be performed in some cases by accessing a real-time traffic information service to obtain one or more traffic condition factors on a route segment, determining a dynamic route segment option weight, calculating a dynamic cost function with respect to the weights, and determining an optimized set of the route segments with respect to the cost functions.

Abstract: Techniques and systems are described that enable the intelligent recommendation and presentation of demand-responsive transit services. Implementations can analyze current user activities with respect to historically-based user transit behaviors in order to determine the user's imminent transit demands. Prior-scheduled transit options meeting the imminent demand are searched, and filtering parameters including user preferences and demand-responsive transit provider constraints are retrieved. Embodiments further retrieve possible demand-responsive transit options for meeting the demand from a demand-responsive transit system scheduling/information service. Embodiments consolidate and analyze these diverse sources to identify a set of preferred transit alternatives for available transit options that meet the filtering parameters. Implementations are described that integrate with an existing transit application present on a user device (e.g., a mobile device).

Abstract: Techniques and systems are disclosed for receiving user input related to three co-optimized objectives, factors, or parameters, and translating the user input into weight factors for a tri-variable weighting function. In various embodiments, a triangular user interface element is displayed that allows a user to assign importance weights to three interrelated decision optimization objectives using a single user input selection gesture. Each side of the triangular user interface element presents a factor of the weight function. When the user selects a single position on the perimeter or within the field of the triangular figure in the user interface, weight factors for each of the three interrelated optimization objectives are determined that can be used as weight factors in the tri-variable weighting function.

Abstract: Systems and techniques are described to enable the dynamic selection of a transit route through the stop zones of a transit line. Techniques are disclosed for receiving a current location of a transit vehicle on a transit line and determining a transit route through one or more of the vehicle's remaining stop zones by choosing an optimized combination of stop options and route segment options for that specific transit vehicle. Techniques may be performed in some cases by accessing a real-time traffic information service to obtain one or more traffic condition factors on a route segment, determining a dynamic route segment option weight, calculating a dynamic cost function with respect to the weights, and determining an optimized set of the route segments with respect to the cost functions.