초록

Traffic analyses have been performed by employing extensive data collected from Intelligent Transportation Systems (ITS). These so-called ITS big data are characterized by automated collection, standardized formats, and high precision. These data, if properly processed, have great potential to aid decision-making for transportation planning policy.

This study is intended to evaluate performance measures to monitor urban mobility. In this regard, ITS big data have advantages in comparison with the counterparts obtained from traditional traffic surveys. First of all, the former can be more flexibly processed than the latter with the use of suitable spatial or temporal units. In addition, ITS big data enable spatiotemporally continuous inspections on urban mobility. Such flexible and continuous analyses are particularly useful in designing or implementing traffic management strategies to solve traffic problems that evolve over time and space.

As an illustration, an empirical analysis was conducted on major roadways of the metropolitan city called Daejeon in Korea. For this analysis ITS big data were processed to quantify diverse performance measures to evaluate urban mobility. In this way, results from analyzing the mobility on individual links and, corridors as well as a road network as a whole, respectively, shed new insights on the traffic operations of the urban highway system.

The forthcoming contents are as follows. Chapter 1 furnishes the background and purpose of this study. Chapter 2 outlines key concepts concerning urban mobility. Chapter 3 explains the characteristics of ITS big data as well as their merits as inputs to evaluate urban mobility. Chapter 4 presents an empirical analysis to evaluate the mobility on the highway system under the jurisdiction of Daejeon. Finally, Chapter 5 presents conclusions and implications from this study.