REAL?TIME TRAFFIC MANAGEMENT STRATEGY GENERATION: FRAMEWORK, APPLICATION AND PERFORMANCE

Abstract

The importance of real-time traffic management strategies in modern transportation networks is well established especially when the network has evolved and become increasingly complicated. The advance of information and sensing technology has provided a large amount of traffic data containing speed, volume, density, etc. The usage of this rich source of data then gives rise to a challenging question of how to turn the data into a series of strategic actions in order to improve the traffic condition, save cost, enrich travelers’ experience and increase their level of satisfaction.

In this thesis, we focus on three perspectives of the aforementioned problem: framework, application and performance. With the studies in this thesis, we aim to fill in the gaps and solve the issues of existing traffic management strategy generation research and lay a foundation for future work in this area.