Investigating the potential of big data in the management of traffic in Malta

Abstract

Big Data is the latest revolution to take place – Google, Amazon, eBay, and Facebook, all successful mega-companies with one mutual practice – the utilisation of massive datasets from a multitude of sources, also known as Big Data. Could this success be replicated in other areas of importance such as Traffic Management? Malta has recently been experiencing heavy traffic congestion build-up on its roads, and the effects are getting worse with each passing year. The aim of this research was to investigate the potential benefits and applications of big data towards improving the management of traffic in Malta’s landscape. A variety of case studies showcasing the successful implementation of big traffic data using technologies, known as ITSs (Intelligent Transportation Systems), in the foreign scene were analysed. This study looked at Transport Malta in order to explore the authority’s goals, current data gathering practices and limitations with regards to big data utilisation. Furthermore, data mining techniques and other statistical analysis were implemented on a real traffic flow dataset comprising of a week-long data-collection exercise at 3 locations. This produced a list of promising correlations and prediction models that demonstrate the practical capacity of big data. Additionally, a performance assessment of two datasets using distinct data collection intervals was performed. This research concludes that there is great potential in utilising big data on a nation-wide scale for assisting in the traffic management of Malta’s roads. Furthermore, it suggests that transport authorities should decide on a clear data gathering criteria for optimum results.