Spatio-Temporal Analysis of Traffic Congestion Based on Data Obtained From Modern Technologies

Analysing traffic conditions and presenting appropriate methods for traffic flow management play a critical role in evaluating the performance of transportation systems. Among different methods of collecting traffic data, approaches based on new technologies that enable the collection of large volumes of dynamic spatio-temporal data and facilitate the extraction of trends and patterns have attracted more attention. .In this study, Tehran as the capital of Iran with its special socio-economic characteristics and the variety of trips that lead to variable traffic situation, has been studied. Using analysis and traffic image data processing relating to Tehran network, the trend of average changes in traffic congestion within Congestion Charging Zone (CCZ) Air Pollution Control Zone (APCZ) and out of these areas on working and non-working days have been investigated. The Moran’s I spatial autocorrelation index, indicates the congested regions in the study area. Also, Havmoler diagrams showed the trend of spatio-temporal changes of traffic congestion on weekdays and weekends.