Abstract: Traffic congestion detection, classification and identification includes analysis of link-speed data representative of vehicular speed and capacity on one or more roadway segments to determine non-linear, multi-segment traffic bottlenecks in a transportation network graph. Link-speed data is processed to detect bottleneck conditions, classify bottlenecks and bottleneck-like traffic features according to their complexity, and identify sustained or recurring bottlenecks. Such a system and method of traffic congestion detection, classification and identification provides a framework for using this link-speed data to detect the head and queue of bottlenecks on a directed graph representing the transportation network, classify the resulting bottlenecks and bottleneck-like traffic features according to the shape of their queue, and identify and measure sustained or recurrent bottlenecks even when the location, or head, of the bottleneck varies slightly across multiple time periods or across multiple days.

Abstract: Quality assessment of probe data collected from GPS systems is performed by a system and method of determining a value of data points provided by different vendors of such data. Incoming raw probe data is initially analyzed for removal of extraneous data points, and is then mapped to roadway links and smoothed out. The resulting output is processed to determine the coverage value of data provided by a given vendor and enable a comparison between different vendors. Such a model of probe data processing also enables an evaluation of a contribution of further vendors of raw probe data to an existing dataset. Additionally, a real-time performance evaluation of continually-ingested probe data includes building historical and data count profiles, and generating output data represented by a number of data points for a specific distance within a geo-box representing a geographical area, to project a value of raw probe data for a next incremental time period.

Abstract: Estimation of traffic speed includes applying data processing functions to determine missing speed information by smoothing spatial and temporal GPS data to achieve an accurate estimation of link speed over all links of a transportation network at all time periods. This estimation of traffic speed uses one link's observed speed information to estimate neighboring links without observed speed information and therefore provides a system and method of processing collected GPS data to obtain a thorough understanding of traffic flow conditions for all represented links without further collection of GPS data. The present invention also provides a framework for analyzing and improving real-time collection of GPS speed data.

Abstract: Traffic congestion detection, classification and identification includes analysis of link-speed data representative of vehicular speed and capacity on one or more roadway segments to determine non-linear, multi-segment traffic bottlenecks in a transportation network graph. Link-speed data is processed to detect bottleneck conditions, classify bottlenecks and bottleneck-like traffic features according to their complexity, and identify sustained or recurring bottlenecks. Such a system and method of traffic congestion detection, classification and identification provides a framework for using this link-speed data to detect the head and queue of bottlenecks on a directed graph representing the transportation network, classify the resulting bottlenecks and bottleneck-like traffic features according to the shape of their queue, and identify and measure sustained or recurrent bottlenecks even when the location, or head, of the bottleneck varies slightly across multiple time periods or across multiple days.

Abstract: Quality assessment of probe data collected from GPS systems is performed by a system and method of determining a value of data points provided by different vendors of such data. Incoming raw probe data is initially analyzed for removal of extraneous data points, and is then mapped to roadway links and smoothed out. The resulting output is processed to determine the coverage value of data provided by a given vendor and enable a comparison between different vendors. Such a model of probe data processing also enables an evaluation of a contribution of further vendors of raw probe data to an existing dataset. Additionally, a real-time performance evaluation of continually-ingested probe data includes building historical and data count profiles, and generating output data represented by a number of data points for a specific distance within a geo-box representing a geographical area, to project a value of raw probe data for a next incremental time period.

Abstract: Estimation of traffic speed includes applying data processing functions to determine missing speed information by smoothing spatial and temporal GPS data to achieve an accurate estimation of link speed over all links of a transportation network at all time periods. This estimation of traffic speed uses one link's observed speed information to estimate neighboring links without observed speed information and therefore provides a system and method of processing collected GPS data to obtain a thorough understanding of traffic flow conditions for all represented links without further collection of GPS data. The present invention also provides a framework for analyzing and improving real-time collection of GPS speed data.

Abstract: An integrated traffic state estimation framework ingests information from multiple input data sources having an impact on traffic flow and correlated to specific road links in a segmented roadway network, and generates output data representative of predictive traffic states. The predictive traffic states are then modeled to generate routing information for traffic on a particular section of roadway. These multiple input data sources include general traffic data collected from one or more sensors or third parties, weather data, incident data, pavement condition data, and roadway operations data, each of which includes data relevant to traffic congestion. The input data is weighted and modeled with data processing modules configured to integrate known and predicted information to produce accurate routing information for particular roadway segments for media, telematics, and consumer uses.