Abstract: Techniques are described for automatically analyzing historical information about road traffic flow in order to generate representative information regarding current or future road traffic flow, and for using such generated representative traffic flow information. Representative traffic flow information may be generated for a variety of types of useful measures of traffic flow, such as for average speed at each of multiple road locations during each of multiple time periods. Generated representative traffic flow information may be used in various ways to assist in travel and for other purposes, such as to determine likely travel times and plan optimal routes. The historical traffic data used to generate the representative traffic flow information may include data readings from physical sensors that are near or embedded in the roads, and/or data samples from vehicles and other mobile data sources traveling on the roads.

Abstract: Techniques are described for generating predictions of traffic conditions at one or more indicated times, such as by using probabilistic techniques to assess various input data while producing predictions for each of one or more road segments (e.g., in a real-time manner based on changing current conditions for a network of roads in a given geographic area). In some situations, one or more predictive Bayesian models and corresponding decision trees are automatically created for use in generating the traffic condition predictions for each geographic area of interest, such as based on observed historical traffic conditions for those geographic areas. Predicted traffic condition information may then optionally be used in a variety of ways to assist in travel and for other purposes, such as to plan optimal routes through a network of roads based on predictions about traffic conditions for the roads at multiple times.

Abstract: Among other things, one or more techniques and/or systems are provided for authorizing an action using vehicle identification information (e.g., supplied by a vehicle) and user identification information (e.g., supplied by a mobile device associated with a user of the vehicle). Such an action may relate to, among other things, refueling the vehicle, parking the vehicle, using a fee-based road segment, and/or other vehicle-centric actions, for example. Moreover, in one embodiment, as part of the authorization, a payment transaction may be initiated by an authorization system configured to authorize the action.

Abstract: Techniques are described for assessing road traffic conditions in various ways based on obtained traffic-related data, such as data samples from vehicles and other mobile data sources traveling on the roads and/or from one or more other sources (such as physical sensors near to or embedded in the roads). The road traffic conditions assessment based on obtained data samples may include various filtering and/or conditioning of the data samples, and various inferences and probabilistic determinations of traffic-related characteristics of interest from the data samples. In some situations, the inferences include repeatedly determining current traffic flow characteristics and/or predicted future traffic flow characteristics for road segments of interest during time periods of interest, such as to determine average traffic speed, traffic volume and/or occupancy, and include weighting various data samples in various ways (e.g., based on a latency of the data samples and/or a source of the data samples).

Abstract: Among other things, one or more techniques and/or systems are provided for predicting a state of a parking location (e.g., occupied or vacant). A correlation between modeling variables (e.g., weather, proximity to a location, a calendar of events, sensor data, etc.) and a possible state of the parking location may be modeled. The state of a parking location may then be predicted using the model and current values for one or more variables (e.g., used to develop the model). In one embodiment, representations of one or more parking locations may be displayed on a map and may be marked with indicators (e.g., colors) that indicate a likelihood of the respective parking locations having parking availability, or the number of parking spots that are available (e.g., where a parking location may be a parking garage having multiple parking spots), (e.g., yellow indicating low parking availability, green indicating substantial parking availability).

Abstract: Techniques are described for displaying or otherwise providing information to users regarding various types of road traffic condition information in various ways. The information may be provided, for example, as part of a user interface (or “UI”), which may in some situations further include one or more types of user-selectable controls to allow a user to manipulate in various ways what road traffic condition information is displayed and/or how the information is displayed. A variety of types of road traffic condition information may be presented to users in various manners, including by presenting information on graphically displayed maps for geographic areas to indicate various information about road conditions in the geographic area. In addition, provided controls may allow users to select particular times, select particular routes, indicate to perform animation of various types of changing traffic conditions over a sequence of multiple successive times, etc.

Abstract: Among other things, one or more techniques and/or systems for parking based route navigation and/or parking resource management are disclosed to facilitate navigation to parking spots associated with a destination and/or management of respective parking spots. Navigation may be provided to a parking spot based upon parking criteria (e.g., such as distance to a destination and/or costs associated with the parking spot). Additionally, navigation (e.g., instructions, alternate transport, such as public transit) from the parking spot to the destination may be provided. Parking spots may be reserved by a parking management system based upon reservations received through a parking based route navigation system. Travelers may be re-routed based upon parking factors (e.g., traffic around a parking location, parking density, etc.). Accordingly, travelers may be routed to a destination in a more efficient manner and/or a management system may price and/or allocate parking spots in a desired manner.

Abstract: Among other things, one or more techniques and/or systems for parking based route navigation and/or parking resource management are disclosed to facilitate navigation to parking spots associated with a destination and/or management of respective parking spots. Navigation may be provided to a parking spot based upon parking criteria (e.g., such as distance to a destination and/or costs associated with the parking spot). Additionally, navigation (e.g., instructions, alternate transport, such as public transit) from the parking spot to the destination may be provided. Parking spots may be reserved by a parking management system based upon reservations received through a parking based route navigation system. Travelers may be re-routed based upon parking factors (e.g., traffic around a parking location, parking density, etc.). Accordingly, travelers may be routed to a destination in a more efficient manner and/or a management system may price and/or allocate parking spots in a desired manner.

Abstract: Among other things, one or more techniques and/or systems for parking based route navigation and/or parking resource management are disclosed to facilitate navigation to parking spots associated with a destination and/or management of respective parking spots. Navigation may be provided to a parking spot based upon parking criteria (e.g., such as distance to a destination and/or costs associated with the parking spot). Additionally, navigation (e.g., instructions, alternate transport, such as public transit) from the parking spot to the destination may be provided. Parking spots may be reserved by a parking management system based upon reservations received through a parking based route navigation system. Travelers may be re-routed based upon parking factors (e.g., traffic around a parking location, parking density, etc.). Accordingly, travelers may be routed to a destination in a more efficient manner and/or a management system may price and/or allocate parking spots in a desired manner.

Abstract: One or more techniques and/or systems are provided for providing search results for presentation as a function of the availability of respective providers comprised in the search results. For example, a user may perform a search for local groceries stores and stores within a 5 miles geographic radius of the user may be identified and filtered/distinguished as a function of the availability of respective stores. Such availability may be a function of whether respective stores are open or closed at the time of the search, whether respective stores are expected to be open or closed at an estimated time of arrival (e.g., based upon travel time from the user's location at the time of the search to respective stores), and/or parking considerations (e.g., parking availability, type of parking, and/or parking cost) at respective stores.

Abstract: One or more techniques and/or systems are provided for determining whether a vehicle comprises a sufficient amount of fuel to reach a destination. Making such a determination may comprise, among other things, estimating an amount of fuel required to reach the destination and/or estimating a rate of consumption along a travel route. Such estimates may be based upon factors external to the vehicle, including, among other things, topology of the travel route, current and/or predicted traffic patterns along the travel route, and/or driving habits of a user or others whom have navigated a similar route (or at least a portion of the route). When it is determined that the vehicle comprises an insufficient amount of fuel, a refueling notice indicative of the determination may be provided. In one embodiment, such a refueling may also suggest possible refueling stations along the travel route.

Abstract: Techniques are described for assessing road traffic conditions in various ways based on obtained traffic-related data, such as data samples from vehicles and other mobile data sources traveling on the roads and/or from one or more other sources (such as physical sensors near to or embedded in the roads). The road traffic conditions assessment based on obtained data samples may include various filtering and/or conditioning of the data samples, and various inferences and probabilistic determinations of traffic-related characteristics of interest from the data samples. In some situations, the inferences include repeatedly determining current traffic flow characteristics and/or predicted future traffic flow characteristics for road segments of interest during time periods of interest, such as to determine average traffic speed, traffic volume and/or occupancy, and include weighting various data samples in various ways (e.g., based on a latency of the data samples and/or a source of the data samples).

Abstract: Location-based devices (e.g., GPS receivers) may be used to identify and track traffic conditions. However, such scenarios are difficult to extend to the identification of relevant facts other than traffic, such as road or weather conditions (e.g., debris, animals, or ice). Presented herein are techniques for receiving and aggregating reports of location-based conditions received from users, either spontaneously (“I just witnessed an accident”) or in response to a query (e.g., “did you encounter road ice one kilometer ago?”) From such reports, location conditions of respective locations may be automatically extracted (e.g., using natural-language parsing techniques), and users in the vicinity of or routing through a particular location may be automatically notified of location conditions (e.g., “ice reported one kilometer ahead”).

Abstract: Among other things, one or more techniques and/or systems for forecasting traffic and concurrently presenting images of forecasted traffic are disclosed to facilitate more efficient departure and/or navigation by providing an outlook of anticipated traffic flow for an area and/or a route (e.g., associated with an origin and destination), for example. A predicted traffic pattern and/or associated navigation may be provided and/or generated based upon traffic data (e.g., historical traffic data, current traffic data, and/or predicted traffic data). Additionally, a suggested departure time may be provided to mitigate travel time to and/or from a destination, for example. Accepted suggestions may be associated with predicted traffic data to update predicted traffic patterns (e.g., predicted traffic data) thereafter. Accordingly, travelers may be provided with traffic forecasting to enable more desirable travel experiences (e.g., shorter travel times).

Abstract: Techniques are described for generating predictions of future traffic conditions at multiple future times, such as by using probabilistic techniques to assess various input data while repeatedly producing future time series predictions for each of numerous road segments (e.g., in a real-time manner based on changing current conditions for a network of roads in a given geographic area). In some situations, one or more predictive Bayesian models and corresponding decision trees are automatically created for use in generating the future traffic condition predictions for each geographic area of interest, such as based on observed historical traffic conditions for those geographic areas. Predicted future traffic condition information may then be used in a variety of ways to assist in travel and for other purposes, such as to plan optimal routes through a network of roads based on predictions about traffic conditions for the roads at multiple future times.

Abstract: Techniques are described for assessing road traffic conditions in various ways based on obtained traffic-related data, such as data samples from vehicles and other mobile data sources traveling on the roads and/or from one or more other sources (such as physical sensors near to or embedded in the roads). The road traffic conditions assessment based on obtained data samples may include various filtering and/or conditioning of the data samples, and various inferences and probabilistic determinations of traffic-related characteristics of interest from the data samples. In some situations, the inferences include repeatedly determining current traffic flow characteristics and/or predicted future traffic flow characteristics for road segments of interest during time periods of interest, such as to determine average traffic speed, traffic volume and/or occupancy, and include weighting various data samples in various ways (e.g., based on a latency of the data samples and/or a source of the data samples).

Abstract: Techniques are described for generating predictions of future traffic conditions at multiple future times, such as by using probabilistic techniques to assess various input data while repeatedly producing future time series predictions for each of numerous road segments (e.g., in a real-time manner based on changing current conditions for a network of roads in a given geographic area). In some situations, one or more predictive Bayesian models and corresponding decision trees are automatically created for use in generating the future traffic condition predictions for each geographic area of interest, such as based on observed historical traffic conditions for those geographic areas. Predicted future traffic condition information may then be used in a variety of ways to assist in travel and for other purposes, such as to plan optimal routes through a network of roads based on predictions about traffic conditions for the roads at multiple future times.

Abstract: Techniques are described for displaying or otherwise providing information to users regarding various types of road traffic condition information in various ways. The information may be provided, for example, as part of a user interface (or “UI”), which may in some situations further include one or more types of user-selectable controls to allow a user to manipulate in various ways what road traffic condition information is displayed and/or how the information is displayed. A variety of types of road traffic condition information may be presented to users in various manners, including by presenting information on graphically displayed maps for geographic areas to indicate various information about road conditions in the geographic area. In addition, provided controls may allow users to select particular times, select particular routes, indicate to perform animation of various types of changing traffic conditions over a sequence of multiple successive times, etc.

Abstract: Techniques are described for assessing road traffic conditions in various ways based on obtained traffic-related data, such as data samples from vehicles and other mobile data sources traveling on the roads, as well as in some situations data from one or more other sources (such as physical sensors near to or embedded in the roads). The assessment of road traffic conditions based on obtained data samples may include various filtering and/or conditioning of the data samples, and various inferences and probabilistic determinations of traffic-related characteristics of interest from the data samples. In some situations, at least some of the mobile data sources are configured to frequently acquire and store data samples, and to occasionally make multiple such data samples available together for use in the road traffic condition assessment (e.g., by acquiring a data sample every minute and by transmitting a group of stored data samples every 15 minutes).

Abstract: Techniques are described for assessing road traffic conditions in various ways based on obtained traffic-related data, such as data samples from vehicles and other mobile data sources traveling on the roads and/or from one or more other sources (such as physical sensors near to or embedded in the roads). The road traffic conditions assessment based on obtained data samples may include various filtering and/or conditioning of the data samples, and various inferences and probabilistic determinations of traffic-related characteristics of interest from the data samples. In some situations, the inferences include repeatedly determining current traffic flow characteristics and/or predicted future traffic flow characteristics for road segments of interest during time periods of interest, such as to determine average traffic speed, traffic volume and/or occupancy, and include weighting various data samples in various ways (e.g., based on a latency of the data samples and/or a source of the data samples).