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.

Filtering road traffic condition data obtained from mobile data sources

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, the inferences include repeatedly determining 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).

Assessing road traffic conditions using data from mobile data sources.

The invention provides a quality control method of road continuous traffic flow data, and the method comprises the following steps: firstly recognizing a fault stationary traffic data acquiring device by using a pattern recognition algorithm which seals cross sectional flow conservatism and a suspicious stationary traffic data acquiring device; then recognizing road real-time traffic flow data byusing a road traffic flow judgment rule; and finally, completing invalid and missing data by using a distribution value in the same period in the history and the adjacent coil data. The quality control method has the advantages that mass data stored in the existing database can be fully utilized to recognize and repair the fault device and effectiveness of the quality of the real-time data by virtue of a statistic method and a traffic flow theory by using space relation among traffic data, therefore, the effectiveness and integrality of the real-time data can be guaranteed, and a data supportcan be provided for various off-line and real-time applications such as the maintenance of the acquiring device, the traffic monitoring and guidance.

Quality control method of road continuous traffic flow data

The invention discloses a traffic road condition information filling method and a system, which relate to the field of traffic information treatment and can improve the accuracy of filling road condition information. The traffic road condition information filling method comprises the following steps: completing vacant data in traffic road condition data according to the historical road condition data; carrying out clustering treatment on all the road condition data of a same road in the same time period for obtaining the road condition change trend, and establishing a road traffic road condition trend mode library; matching the road condition trend of the road in the time period containing the time point t with the road condition change trend of the road in the traffic road condition trend mode library, and calculating the driving speed of the road at the time point t for filling the road condition. The method and the system are applied in the treatment of traffic accident information of an intelligent traffic system.

Traffic road condition information filling method and system

The invention provides a website index data prediction method and system and an alarming method and system. The data prediction method comprises the following steps: collecting the historical data of an index in a preset area, classifying the historical data according to time periods, and classifying the historical data in each time period according to a sequence of date; dividing the historical data in each time period into standard data and data to be corrected, correcting the data to be corrected according to the standard data, and forming historical optimization data by the corrected data and the standard data; and according to the historical optimization data, calculating the prediction data of the index at a first prediction date through an ARIMAX model. The prediction data of a certain index at a certain date can be accurately predicted, prediction accuracy is obviously improved, an alarm is given when a plurality of indexes used for measuring the operation situation of a website meet certain conditions at the same time, and therefore, users can timely know the operation situation of the website.

Data prediction method and system and alarming method and system

A control method of data quality includes carrying out data classification division based on judgement rules designed upon total comparison method, threshold theory and traffic flow theory; then utilizing figure calculation theory to revise the data. The designed device for the method consists of fetching device, identifying device, revising device, storing device and outputting device for data.

Lei Yu

Papers

Road traffic flow data quality controlling method and apparatus