Application of Big Data Analytics to Determine Traffic Congestion

Abstract

This study focused on the application of big data analytics to estimate roadway congestion. The implementation of big data allows a convenient approach of data collection without any field or observer biasness. It also relieves the restriction of a limited sample. Highway Capacity Manual 2000 suggested considering travel speed as the most appropriate parameter for describing traffic congestion. Therefore, this research employs a speed performance index with the concept of big data analytics to describe traffic congestion of road. This research estimates speed performance index for different sections of road. The data was gathered for three main roads of Karachi i.e. Rashid Minhas Road, Shahra e Faisal Road and Main Korangi Road. The major achievement of this study project is to propose a novel approach to calculate the speed of a vehicle without field measurements. The data is collected through Smartphone with the aid of an application available online namely My Track. The data that was utilized for this project mainly comprises of GPS Exchange Format (GPX) routes that are converted into Extensible Markup Language (XML) to run the developed script. The script was able to determine the status of congestion on a variety of highways with the help of speed performance index. The same script can be used by administrators and other transportation service providers for estimating the congestion on a real-time basis. The methods and procedures from this study would aid in the transportation planning process, especially for route selection of individuals as well as services.