Current state and future outlook of traffic data fusion in London

Abstract

Metropolitan areas today have become more than ever saturated with various types and sources of real-time data. Yet, the unsolved practical challenge how to most effectively combine data sources currently prevents the wide use of this data as a powerful tool to both improve the quality of the transport supply and to influence travel demand. Focusing on London, this paper investigates the current state and attempts to give an outlook into the future of traffic data fusion in dense urban network environments. Successes and gaps in the current state are identified, and extensions are proposed, along with respective deployment scenarios and impacts assessment.

Simon Hu

Assistant Professor