Knowl Inf Syst
Spatiotemporal trafﬁc network analysis: technology and
· Kotaro Hirasawa
Received: 13 September 2017 / Accepted: 22 May 2018
© Springer-Verlag London Ltd., part of Springer Nature 2018
Abstract The rapid development of intelligent transportation systems and the emergence of
the sharing economy have given rise to vast amounts of spatiotemporal data. Consequently,
spatiotemporal trafﬁc network analysis has become a crucial approach to trafﬁc managers
in trafﬁc control, route guidance, trafﬁc policy adjustment, and transportation network plan-
ning. This study provides a comprehensive survey of recent developments in spatiotemporal
trafﬁc network analysis and reviews the latest research ranging from 2000 to 2016. This paper
focuses on overall methods and general characteristics involved in trafﬁc network analysis.
First, we introduce some potential applications of spatiotemporal trafﬁc network analysis.
Second, we discuss data sources and corresponding pretreatment methods. Then, we investi-
gate various existing methodologies to examine the state of the art in trafﬁc network analysis.
At the end of this survey, we provide more detailed discussions on future research challenges
and new research points.
Keywords Spatiotemporal database · Trafﬁc network analysis · Spatiotemporal trafﬁc
pattern · Trafﬁc networks
Urban trafﬁc networks, which are typical of human-centered time-variant complex systems,
have experienced rapid development in recent decades, and the problem of creating highly
efﬁcient transportation systems has attracted signiﬁcant attention. Intelligent transport sys-
This work was supported by the National Natural Science Foundation of China [Grant No. 61602028].
Beijing philosophy and social science program [Grant No. 15JGC166], and the Fundamental Research
Funds for the Central Universities [Grant No. 2015jbwy007].
School of Economics and Management, Beijing Jiao Tong University, Beijing, China
IPS Research Center, Waseda University, Kitakyushu, Japan