Abstract: Travel-demand forecasting methods are described for predicting traffic volume based, at least in part, on user-entered data in the form of anticipated traffic routes, demographic data and/or other types of socioeconomic data. This data can source a prediction algorithm or be used to forecast traffic patterns. Methods and systems are described for, among other things, optimizing traffic predictions, forecasting traffic patterns using user-assigned trip patterns, associating rich attribute information to navigation routes, exposing personal-logistic information to a group, communicating traffic-situation-generated alerts based on user information, optimizing a presentation of user-defined traffic routes, and presenting location indications based on proximity (temporal or geographical).

Abstract: Travel-demand forecasting methods are described for predicting traffic volume based, at least in part, on user-entered data in the form of anticipated traffic routes, demographic data and/or other types of socioeconomic data. This data can source a prediction algorithm or be used to forecast traffic patterns. Methods and systems are described for, among other things, optimizing traffic predictions, forecasting traffic patterns using user-assigned trip patterns, associating rich attribute information to navigation routes, exposing personal-logistic information to a group, communicating traffic-situation-generated alerts based on user information, optimizing a presentation of user-defined traffic routes, and presenting location indications based on proximity (temporal or geographical).

Abstract: Travel-demand forecasting methods are described for predicting traffic volume based, at least in part, on user-entered data in the form of anticipated traffic routes, demographic data and/or other types of socioeconomic data. This data can source a prediction algorithm or be used to forecast traffic patterns. Methods and systems are described for, among other things, optimizing traffic predictions, forecasting traffic patterns using user-assigned trip patterns, associating rich attribute information to navigation routes, exposing personal-logistic information to a group, communicating traffic-situation-generated alerts based on user information, optimizing a presentation of user-defined traffic routes, and presenting location indications based on proximity (temporal or geographical).

Abstract: A method and system for automatically loading and unloading a transport is disclosed. A first guidance system is used to travel near the transport and a second guidance system is used to travel on the transport.

Abstract: Travel-demand forecasting methods are described for predicting traffic volume based, at least in part, on user-entered data in the form of origin/destination data pairs, user preferences, demographic data and other types of socioeconomic data. This data can source a prediction algorithm or be used to calibrate or more make accurate a current algorithm. Methods and systems are described for, among other things, optimizing traffic predictions, forecasting traffic patterns using user-assigned trip patterns, associating rich attribute information to navigation routes, exposing personal-logistic information to a group, communicating traffic-situation-generated alerts based on user information, optimizing a presentation of user-defined traffic routes, and presenting location indications based on proximity (temporal or geographical).

Abstract: Presenting of real-world situational data on a dynamically updateable user interface is provided for by providing a dynamically updateable user interface that includes dynamic objects having variable characteristics and that correspond to real-world objects, receiving situational data that corresponds to a status of the one or more real-world objects, and conforming the one or more variable characteristics to be consistent with the situational data such that an observer of the one or more dynamic objects is informed of a current status of a corresponding real-world situation.

Abstract: Travel-demand forecasting methods are described for predicting traffic volume based, at least in part, on user-entered data in the form of origin/destination data pairs, user preferences, demographic data and other types of socioeconomic data. This data can source a prediction algorithm or be used to calibrate or more make accurate a current algorithm. Methods and systems are described for, among other things, optimizing traffic predictions, forecasting traffic patterns using user-assigned trip patterns, associating rich attribute information to navigation routes, exposing personal-logistic information to a group, communicating traffic-situation-generated alerts based on user information, optimizing a presentation of user-defined traffic routes, and presenting location indications based on proximity (temporal or geographical).

Abstract: A system, a method and computer-readable media for presenting dynamic traffic information. A user profile is stored, and advisory data based on the user profile is gathered. The advisory data may include traffic information associated with road segments identified by the user profile. Upon receiving a user input, the advisory data is presented to a user.

Abstract: Travel-demand forecasting methods are described for predicting traffic volume based, at least in part, on user-entered data in the form of origin/destination data pairs, user preferences, demographic data and other types of socioeconomic data. This data can source a prediction algorithm or be used to calibrate or more make accurate a current algorithm. Methods and systems are described for, among other things, optimizing traffic predictions, forecasting traffic patterns using user-assigned trip patterns, associating rich attribute information to navigation routes, exposing personal-logistic information to a group, communicating traffic-situation-generated alerts based on user information, optimizing a presentation of user-defined traffic routes, and presenting location indications based on proximity (temporal or geographical).

Abstract: Presenting of real-world situational data on a dynamically updateable user interface is provided for by providing a dynamically updateable user interface that includes dynamic objects having variable characteristics and that correspond to real-world objects, receiving situational data that corresponds to a status of the one or more real-world objects, and conforming the one or more variable characteristics to be consistent with the situational data such that an observer of the one or more dynamic objects is informed of a current status of a corresponding real-world situation.

Abstract: Presenting of real-world situational data on a dynamically updateable user interface is provided for by providing a dynamically updateable user interface that includes dynamic objects having variable characteristics and that correspond to real-world objects, receiving situational data that corresponds to a status of the one or more real-world objects, and conforming the one or more variable characteristics to be consistent with the situational data such that an observer of the one or more dynamic objects is informed of a current status of a corresponding real-world situation.

Abstract: A method and system for automatically loading and unloading a transport is disclosed. A first guidance system is used to travel near the transport and a second guidance system is used to travel on the transport.

Abstract: A system, a method and computer-readable media for presenting dynamic traffic information. A user profile is stored, and advisory data based on the user profile is gathered. The advisory data may include traffic information associated with road segments identified by the user profile. Upon receiving a user input, the advisory data is presented to a user.

Abstract: A system, a method and computer-readable media for presenting dynamic traffic information. A user profile is stored, and advisory data based on the user profile is gathered. The advisory data may include traffic information associated with road segments identified by the user profile. Upon receiving a user input, the advisory data is presented to a user.

Abstract: A method and system for automatically loading and unloading a transport is disclosed. A first guidance system is used to travel near the transport and a second guidance system is used to travel on the transport.