Computational intelligence and optimization for transportation big data: Challenges and opportunities

Abstract

With the overwhelming amount of transportation data being gathered worldwide, Intelligent Transportation Systems (ITS) are faced with several modeling challenges. New modeling paradigms based on Computational Intelligence (CI) that take advantage of the advent of big datasets have been systematically proposed in literature. Transportation optimization problems form a research field that has systematically benefited from CI. Nevertheless, when it comes to big data applications, research is still at an early stage. This work attempts to review the unique opportunities provided by ITS and big data and discuss the emerging approaches for transportation modeling. The literature dedicated to big data transportation applications related to CI and optimization is reviewed. Finally, the challenges and emerging opportunities for researchers working with such approaches are also acknowledged and discussed.