Abstract: One or more techniques and/or systems are provided for developing and facilitating the development of a vehicle profile for a vehicle. An application developer may experience difficulty when developing applications that are to interact with a vehicle computing device of a vehicle due to proprietary software, communication protocols, data formats, etc. Accordingly, a vehicle profile may be developed to act as an intermediary abstraction layer between the application and the vehicle computing device. A profile developer can define how to process certain types of input from the application, what vehicle signal information can be accessed by the application, how information such as a user interface of the application is to be displayed such as through a vehicle navigation unit, what vehicle parameters can be modified by the application, etc. In this way, the application can interact with the vehicle computing device through the vehicle profile.

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 from the data samples. In some situations, the filtering of the data samples includes identifying data samples that are inaccurate or otherwise unrepresentative of actual traffic condition characteristics, such as data samples that are not of interest based at least in part on roads with which the data samples are associated and/or that otherwise reflect vehicle locations or activities that are not of interest.

Abstract: One or more techniques and/or systems are provided for estimating parking occupancy. For a paid parking period, parking meter transaction data may be acquired for a parking meter encompassed by a zone of one or more parking spaces. The parking meter transaction data may be evaluated to determine status data, such as an estimation of whether one or more parking spaces are available, occupied, and/or will become available. A parking occupancy, indicative of a likelihood of available parking spaces, may be estimated based upon the status data. For a free parking period, the parking occupancy may be estimated based upon vehicle flow data that is indicative of vehicles entering, parking, and/or leaving the one or more parking spaces. In this way, the parking occupancy may be provided to a driver to mitigate wasted time and/or gas otherwise spent searching for an available parking space.

Abstract: Users within transit in a vehicle may initiate location queries to fulfill a set of interests, such as stops for food, fuel, and lodging. A device may fulfill the queries according to various factors, such as the distance of nearby locations to the user or to another location specified by the user, and the popularity of various locations. However, the user may not have specified or even chosen a route, and may wish to have interests fulfilled at a later time (e.g., stopping for food in 30 minutes), and a presentation of search results near the user's current location may be unhelpful. Presented herein are techniques for fulfilling location queries that involve predicting a route of the user, and identifying a timing window for the query results (e.g., locations that are likely to be near the user's projected location when the wishes to stop for food in 30 minutes).

Abstract: One or more techniques and/or systems are provided for determining a scaled flow rate of traffic for a road segment. For example, probe flow rate information is determined based upon locational information from one or more probe vehicles on a road segment (e.g., a flow rate of probe vehicles corresponding to a sum of probe vehicles identified from time stamped global positioning system coordinates provided by the probe vehicles). Satellite imagery of the road segment is analyzed to identify a count of vehicles on the road segment. Scale factor and offset information is estimated based upon the probe flow rate information and the count of vehicles. The scale factor and offset information is used to scale the probe flow rate information to determine a scaled flow rate that may be a relatively accurate flow rate of traffic, which may correspond to an inferred traffic volume along the road segment.

Abstract: A method and system for modeling and processing vehicular traffic data and information, comprising: (a) transforming a spatial representation of a road network into a network of spatially interdependent and interrelated oriented road sections, for forming an oriented road section network; (b) acquiring a variety of the vehicular traffic data and information associated with the oriented road section network, from a variety of sources; (c) prioritizing, filtering, and controlling, the vehicular traffic data and information acquired from each of the variety of sources; (d) calculating a mean normalized travel time (NTT) value for each oriented road section of said oriented road section network using the prioritized, filtered, and controlled, vehicular traffic data and information associated with each source, for forming a partial current vehicular traffic situation picture associated with each source; (e) fusing the partial current traffic situation picture associated with each source, for generating a single co

Abstract: One or more techniques and/or systems are provided for providing a traffic news interface. For example, a traffic news provider component may query traffic camera data and/or traffic incident data to identify traffic cameras and/or traffic incidents along a route of a driver. The traffic cameras and/or the traffic incidents may be ranked based upon a safety metric, a travel time sensitivity metric, an alternative route selection metric, a driving behavior pattern, a driver mood, a distance of a traffic camera or traffic incident from a current user location, and/or other information used to determine how relevant information from the traffic camera and/or a traffic incident is to this particular driver. A subset of traffic cameras and/or traffic incidents may be selected for inclusion within a traffic news interface based upon camera relevancy rankings and/or incident relevancy rankings.

Abstract: One or more techniques and/or systems are provided for estimating parking occupancy. For a paid parking period, parking meter transaction data may be acquired for a parking meter encompassed by a zone of one or more parking spaces. The parking meter transaction data may be evaluated to determine status data, such as an estimation of whether one or more parking spaces are available, occupied, and/or will become available. A parking occupancy, indicative of a likelihood of available parking spaces, may be estimated based upon the status data. For a free parking period, the parking occupancy may be estimated based upon vehicle flow data that is indicative of vehicles entering, parking, and/or leaving the one or more parking spaces. In this way, the parking occupancy may be provided to a driver to mitigate wasted time and/or gas otherwise spent searching for an available parking space.

Abstract: One or more techniques and/or systems are provided for routing a user between events using an itinerary. An event source (e.g., electronic calendar) may be assessed to identify event information (e.g., event locations) for events (e.g., meetings). The event information may be evaluated to determine a schedule of events. Routes between events within the schedule may be identified to determine route information (e.g., predicted travel times) for the routes. The event information and the route information may be evaluated to generate an itinerary of events. In an example, a constraint may be identified (e.g., a traffic accident along a route). The constraint may be evaluated to determine an impact (e.g., a user arriving to the meeting event late) of the constraint on the itinerary. Responsive to the impact exceeding an adjustment threshold, the itinerary may be adjusted (e.g., modifying a route between one or more events to avoid the accident).

Abstract: Techniques are described for using information regarding road traffic and other types of transportation-related information to determine and/or assess alternative inter-modal passenger travel options in a geographic area that supports multiple modes of transportation. For example, a particular user may have multiple alternatives for travel from a starting location to a destination location in the geographic area, including to use alternative modes of transportation (e.g., private vehicle, bus, train, walking, etc.) for some or all of the travel, and these alternatives may have different travel-related characteristics in different situations (e.g., depending on current road traffic; mass transit schedules and current actual deviations; travel-related fees for gas, parking, mass transit, etc; parking availability; etc.).

Abstract: Transit through an area by a population of travelers may be evaluated by a number of techniques, and may be useful for routing, transit time estimation, and transit control. Some techniques involve the use of probes, such as individuals or vehicles that are tagged and trackable through the area. However, estimating properties such as transit queue volume through probe counts may be difficult, as the ratio of probes to the overall population may vary. Presented herein are techniques for estimating transit properties by evaluating transit queues to estimate the probe ratio for an area. Such techniques involve counting and tracking the probes in a transit queue to estimate a queue length change of the transit queue, and a probe rate change of probes entering and exiting the transit queue. This information may inform estimates of the probe ratio, and in turn regional transit estimates, such as transit queue volumes.

Abstract: 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.

Abstract: Among other things, one or more client devices, techniques, and/or systems are provided for providing linear route conditions. A linear route condition interface, presented to a user, may comprise a linear route representation (e.g., represented by a horizontal or vertical bar) of a route from a starting location to a destination location. The linear route representation depicts a first road segment, populated with a traffic flow indicator, a second road segment, populated with a second traffic flow indicator, and/or any other number of road segments between the starting location and the destination location. Responsive to identifying user indication of interest for the first road segment, supplementary information about traffic conditions on the first road segment are presented to the user. Responsive to identifying user indication of interest for the second road segment, supplementary information about traffic conditions on the second road segment are presented to the user.

Abstract: One or more techniques and/or systems are provided for determining a scaled flow rate of traffic for a road segment. For example, probe flow rate information is determined based upon locational information from one or more probe vehicles on a road segment (e.g., a flow rate of probe vehicles corresponding to a sum of probe vehicles identified from time stamped global positioning system coordinates provided by the probe vehicles). Satellite imagery of the road segment is analyzed to identify a count of vehicles on the road segment. Scale factor and offset information is estimated based upon the probe flow rate information and the count of vehicles. The scale factor and offset information is used to scale the probe flow rate information to determine a scaled flow rate that may be a relatively accurate flow rate of traffic, which may correspond to an inferred traffic volume along the road segment.

Abstract: One or more techniques and/or systems are provided for estimating parking occupancy. For a paid parking period, parking meter transaction data may be acquired for a parking meter encompassed by a zone of one or more parking spaces. The parking meter transaction data may be evaluated to determine status data, such as an estimation of whether one or more parking spaces are available, occupied, and/or will become available. A parking occupancy, indicative of a likelihood of available parking spaces, may be estimated based upon the status data. For a free parking period, the parking occupancy may be estimated based upon vehicle flow data that is indicative of vehicles entering, parking, and/or leaving the one or more parking spaces. In this way, the parking occupancy may be provided to a driver to mitigate wasted time and/or gas otherwise spent searching for an available parking space.

Abstract: One or more techniques and/or systems for providing congestion information for a road segment presently experiencing traffic congestion and/or likely to experience traffic congestion in the future are provided. In some embodiments, traffic models are configured to determine road segments where traffic congestion is likely to occur, to determine a cause of traffic congestion, and/or to determine the effect of such traffic congestion (e.g., the duration of such traffic congestion, the expected time delays due to such traffic congestion, etc.). Congestion information indicative of the cause of congestion and/or the effect(s) of such traffic congestion, for example, may be provided to a user to explain to the user why the congestion is occurring, to describe one or more road segments to avoid, and/or to explain why a particular route was selected as a preferred route to a destination, for example.

Abstract: One or more techniques and/or systems are provided for selectively collecting vehicle telemetry data from one or more vehicles. For example, a communication data budget for a vehicle may be identified (e.g., a 5 GB per month data connection plan). A determination may be made as to whether the vehicle can provide vehicle telemetry data used to model a travel condition (e.g., road imagery, temperature, a windshield wiper state, and/or other vehicle telemetry data used to model a road safety condition). If the vehicle has remaining communication data budget available for transmission of the vehicle telemetry data without the vehicle exceeding the communication data budget for a billing cycle, then a data request for the vehicle telemetry data may be sent to the vehicle. Responsive to receiving the vehicle telemetry data from the vehicle, the travel condition may be modeled (e.g., the road condition may be determined as icy).

Abstract: Vehicles feature various forms of automated driving control, such as speed control and braking distance monitoring. However, the parameters of automated control may conflict with the user driving behaviors of the user; e.g., braking distance maintained with respect to a leading vehicle may seem overcautious to users who prefer shorter braking distances, and unsafe to users who prefer longer braking distances. Presented herein are techniques for controlling vehicles according to the user driving behaviors of users. While a user operates a vehicle in a driving context, a device monitors various driving features (e.g., acceleration or braking) to determine various user driving behaviors. When requested to control a driving feature of the vehicle, a controller may identify the user driving behaviors of the user in the driving context, and control the driving features according to the user driving behaviors, thus personalizing automated driving to the preferences of the user.

Abstract: One or more techniques and/or systems are provided for providing linear route progress. For example, a linear route progress interface, comprising a linear route representation of a route from a starting location to a destination location, may be displayed. The linear route representation may linearly represent a progress of the user along the route (e.g., as opposed to directions on a map that may otherwise visually overwhelm a user merely interested in traffic flow and/or incident information that may affect an arrival time of the user). The linear route progress interface may be populated with traffic flow indicators (e.g., traffic flow speed) and/or incident indictors (e.g., indicating accidents, construction, etc.). A user indicator, corresponding to a current position of the user, may be populated within the linear route progress interface. The user indicator and/or the linear route representation may be modified to illustrate user progress along the 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, 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 from the data samples. In some situations, the filtering of the data samples includes identifying data samples that are inaccurate or otherwise unrepresentative of actual traffic condition characteristics, such as data samples that are not of interest based at least in part on roads with which the data samples are associated and/or that otherwise reflect vehicle locations or activities that are not of interest.