Modeling traffic flow using simulation and Big Data analytics

Abstract

Improving the efficiency, safety, and cost of road systems is an essential social problem that must be solved as the number of drivers, and the size of mass transit systems increase. Methodologies used for the construction of traffic simulations need to be examined in the context of real world big traffic data. This data can be used to create models for vehicle arrivals, turning behavior, and traffic flow. Our work focuses mainly on generating models for these concepts and using them to drive microscopic traffic simulations built upon real world data. Strengths and weaknesses of various simulation optimization techniques are also considered as a methodology issue, since the nature of traffic systems weakens the effectiveness of some optimization techniques.