Exploring traffic dynamics on motorways: A spatiotemporal analysis of speed patterns on the Attica Tollway

Advances in technology have introduced remarkable capabilities, particularly in the realm of gathering and accessing vast amounts of data, leading to the emergence of the "Big Data" era and presenting exciting opportunities to harness the wealth of generated information. Traffic management centres are stakeholders that can exploit such data towards improving road network operation. This research explores the utilization of real traffic data, collected from distinct sources on an interurban motorway: static location-based on aggregate traffic data and probe vehicle data. The first type is collected by traffic detectors, while the second involves GNSS data from patrol vehicles. The analysed traffic quantity is vehicle speed, wtih specific on the visualisation through the creation of heatmaps to represent daily traffic patterns and the application of k-means clustering. The performed analysis demonstrates the importance of considering spatiotemporal variables as a unified entity when analysing speed in transportation networks. The limitations of using patrol vehicles as estimators of ambient speed, especially under low and heavy traffic conditions, are delineated, while the dual purpose of data gathered from these vehicles towards enhancing driving performance and enabling detector maintenance is elaborated. Valuable traffic insights are offered through comprehensive spatiotemporal speed behavior analysis and data combination. The integration of these techniques enhances decision-making for a streamlined and secure transportation system.