Heterogeneous Data Aggregation Schemes to Determine Traffic Flow Parameters in Regional Intelligent Transportation Systems

Abstract

For optimal solution of intelligent transportation centers goals it’s necessary to collect and process information from a variety of sources to ensure a full understanding of the situation on roads in real-time. It is possible to improve traffic control and transportation corridor management tasks via analysis of heterogeneous sources such as GPS, metadata regarding device identity, status and location used by mobile devices to stay connected to various networks, data received from vehicles and road infrastructure devices, transport cards and terminals information in the public transport; e-mail messages, SMS, posts in messengers or social networks, metadata of phone calls of road users (drivers, pedestrians and passengers); video streams from surveillance cameras and drones, cameras to record violations; data from accelerometers, compasses, temperature sensors, infrared radiation, electromagnetic field, atmospheric pressure, etc.; data from radars, devices analyzing RFID-tags. In the paper the possibility of using heterogeneous sources to calculate the necessary characteristics of the traffic flow is discussed, the existing approaches to aggregate information obtained from heterogeneous sources are described, a conceptual scheme of the module to aggregate heterogeneous data based on BigData and Data Mining methods is suggested.