Application of Big Data Technologies for Quantifying the Key Factors Impacting Passenger Journey in a Multi-Modal Transportation Environment

Abstract

Transportation systems are designed to run in normal conditions. The occurrence of planned works, unscheduled major events or disturbances can affect the transportation services that intended to provide and as a result, the disruptive nature may have a significant impact on the operation of the transport modes. This chapter focuses on the impact of disruptions in the multimodal transportation using the available open data. The enablers (key variables) of the datasets are taken into account to evaluate the service performance of each transport mode and its influence on other transport modes in case of disturbances. The high-volume, streaming data collected for a long time is a good potential use case for applying text mining techniques on big data. This chapter provides an insight into research being carried out for developing capabilities to store and analyze multi-modal data feeds for predictive analysis.