A method of communicating with traffic participants according to an example of this disclosure includes storing data of traffic participant tendencies at an intersection. The method further includes sensing real-time movement characteristics of all traffic participants in the proximity of the intersection. The method further includes determining that it is impracticable to communicate all movement data with all traffic participants in the proximity of the intersection and then calculating a criticality level of one or more traffic participants in the proximity of the intersection based on their movement characteristics and the traffic participant tendencies at the intersection. The method further includes developing a limited communication strategy for the one or more traffic participants based on their criticality level; and then communicating accident prevention information to one or more of the traffic participants according to the limited communication strategy through a communication means.

Among other things, one or more techniques and/or systems are provided for personalized vehicle management. A current location of a vehicle may be received. A route of the vehicle may be determined based upon a trip library and/or the current location. The trip library may correspond to routes travelled by the user above a travel frequency threshold. A route segment (e.g., a portion of the route that the vehicle will travel within a threshold duration) may be identified. A route segment characteristic (e.g., a weather characteristic, a physical characteristic, a traffic characteristic, etc.) of the route segment may be determined. The route segment characteristic may be provided to a driver assistance component of the vehicle. The driver assistance component may be instructed to alter functionality of the vehicle using a vehicle operational parameter derived from the route segment characteristic.

An information processing device includes a processor including hardware. The processor is configured to: communicate with an information communication device associated with a mobile object on which a user rides and configured to output user skill information related to driving skill of the user and a sensor configured to sense other mobile objects inside and around an intersection and output sensing information; derive entering timing at which the mobile object enters the intersection based on the sensing information acquired from the sensor and the user skill information acquired from the information communication device; and output timing information including the entering timing of the mobile object to the information communication device before the mobile object enters the intersection.

Methods and systems for generating a trained destination prediction model are provided. The method may include obtaining a plurality of historical orders corresponding to a plurality of users and determining a plurality of first features and a plurality of second features associated with the plurality of historical orders. The method may further include determining a plurality of transformed features based on the plurality of first features and a plurality of sets of cross features by correlating the plurality of second features. The method may further include obtaining a preliminary destination prediction model and training the preliminary destination prediction model to obtain a trained destination prediction model based on the plurality of transformed features and the plurality of sets of cross features.

In some implementations, a mobile device transmits traffic information to a server for analysis. The traffic information includes movement information including detected stops and durations of detected stops. The traffic information is analyzed to detect traffic patterns that indicate locations of stop signs and/or stop lights. The traffic information is analyzed to determine durations of stops at stop signs and/or stop lights. The durations of stops are associated with a time of day and/or day of the week. In some implementations, navigational routes are determined based stop sign and/or stop light information, including the delays attributable to detected stop signs and/or stop lights.

Provided is a technology for improving accuracy in determining the next action. Travel history generator generates, for each driver, a travel history associating an environmental parameter indicating a travel environment through which a vehicle has previously traveled with an action selected by the driver in response to the environmental parameter. Acquisition unit acquires a travel history similar to a travel history of a current driver from among travel histories generated by travel history generator. Driver model generator generates a driver model based on the travel history acquired by acquisition unit. Determination unit determines the next action based on the driver model generated by driver model generator) and an environmental parameter indicating a current travel environment of the vehicle.

Methods and systems for generating a trained destination prediction model are provided. The method may include obtaining a plurality of historical orders corresponding to a plurality of users and determining a plurality of first features and a plurality of second features associated with the plurality of historical orders. The method may further include determining a plurality of transformed features based on the plurality of first features and a plurality of sets of cross features by correlating the plurality of second features. The method may further include obtaining a preliminary destination prediction model and training the preliminary destination prediction model to obtain a trained destination prediction model based on the plurality of transformed features and the plurality of sets of cross features.

Among other things, one or more techniques and/or systems are provided for personalized vehicle management. A current location of a vehicle may be received. A route of the vehicle may be determined based upon a trip library and/or the current location. The trip library may correspond to routes traveled by the user above a travel frequency threshold. A route segment (e.g., a portion of the route that the vehicle will travel within a threshold duration) may be identified. A route segment characteristic (e.g., a weather characteristic, a physical characteristic, a traffic characteristic, etc.) of the route segment may be determined. The route segment characteristic may be provided to a driver assistance component of the vehicle. The driver assistance component may be instructed to alter functionality of the vehicle using a vehicle operational parameter derived from the route segment characteristic.

An online system provides navigation information customized using travel preferences of users. The online system receives actions performed by users that may indicate their geographical locations of interest. The online system may use a model to predict a user's level of interest in destination geographical locations. The online system generates navigation information or travel information that describes routes from origin geographical locations of users to destination geographical locations to which the users are likely to travel. The online system transmits the navigation information to client devices for presentation as personalized or dynamically-created content items to users. The online system may generate navigation information using catalogs describing routes between geographical locations. For instance, the catalog indicates a vehicle for navigation along a route, as well as origin and destination geographical locations.

An online system provides navigation information customized using travel preferences of users. The online system receives actions performed by users that may indicate their geographical locations of interest. The online system may use a model to predict a user's level of interest in destination geographical locations. The online system generates navigation information or travel information that describes routes from origin geographical locations of users to destination geographical locations to which the users are likely to travel. The online system transmits the navigation information to client devices for presentation as personalized or dynamically-created content items to users. The online system may generate navigation information using catalogs describing routes between geographical locations. For instance, the catalog indicates a vehicle for navigation along a route, as well as origin and destination geographical locations.