Abstract
We put forward architecture of a framework for integration of data from moving objects related to urban transportation network. Most of this research refers to the GPS outdoor geolocation technology and uses distributed cloud infrastructure with big data NoSQL database. A network of intelligent mobile sensors, distributed on urban network, produces congestion traffic patterns. Congestion predictions are based on extended simulation model. This model provides traffic indicators calculations, which fuse with the GPS data for allowing estimation of traffic states across the whole network. The discovery process of congestion patterns uses semantic trajectories metamodel given in our previous works. The challenge of the proposed solution is to store patterns of traffic, which aims to ensure the surveillance and intelligent real-time control network to reduce congestion and avoid its consequences. The fusion of real-time data from GPS-enabled smartphones integrated with those provided by existing traffic systems improves traffic congestion knowledge, as well as generating new information for a soft operational control and providing intelligent added value for transportation systems deployment.
Highlights
Knowledge data discovery and big data are concepts that revolutionize the modern information technology
In the field of urban transportation, road traffic state can be represented at any time through the analysis of information collected on all vehicles, which contributes to the development of descriptive models in the form of formulas and rules to reproduce the complex dynamics of traffic
We present the traffic flow modeling approaches according to fundamental diagram
Summary
Knowledge data discovery and big data are concepts that revolutionize the modern information technology. Urban transport as part of “Urban Computing” is considered one of the most striking big data and knowledge discovery applications These range from urban traffic management activities with computerized processing of massive amounts of traffic data and geographic data to complex signaling and traffic assignment or control systems, to communications, vehicles tracking, and traveler information operations using increasingly common modern technologies like GPS [2], Wi-Fi, and cellular phone systems. In order to quantify the severity of congestion, Global Positioning System (GPS) applications have been utilized to collect travel time per period and delay data for many of transportation networks. (i) the first point concerning the modeling of congestion and allowing developing a measurement process based on GPS technology,.
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