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 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:
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:
Estimates may be compiled of a volume of travelers in an area, such as vehicles, pedestrians, and migratory wildlife. Such estimates are often compiled through human observation and/or the deployment of regional monitoring equipment, such as roadside cameras and road-embedded sensors; however, such techniques may entail significant costs in equipment purchase, deployment, monitoring, and maintenance, and may exhibit inadequate accuracy and/or rapidity of data collection. Presented herein are techniques for estimating a traveler volume in an area by using an aerial device, such as a drone, to capture an aerial image of the area from an aerial perspective, and applying object recognition machine vision techniques to recognize and count the travelers depicted in the aerial image. Such data may be used to estimate traveler volume; to evaluate transit patterns of the travelers throughout a region; and/or to control transit patterns of the travelers using transit control devices.
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.
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 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:
Vehicles operation is often regulated by vehicle operation policies, such as operator and vehicle licensing, safe operation rules, and emissions testing, as well as advisory policies (e.g., safety tips) and infrastructure policies (e.g., traffic congestion reduction). However, enforcement of vehicle operation policies may be infrequent, costly, inaccurate, and/or ineffective for particular types of problems. Presented herein are techniques for enforcing vehicle operation policies using vehicle telemetrics detected by a vehicle telemetry sensor and reported to telemetric monitoring components during operation of the vehicles. For example, in-car emissions sensors may regularly report emissions data to roadside monitors, enabling continuous monitoring, early detection of emissions problems, and accurate measurements during road travel. Additional telemetric exchange may promote the persuasion of advisory vehicle operation policies, such as safety tips, and the transmission of travel information of interest to other vehicles and individuals, such as road hazards, traffic congestion, and available parking spots.
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).