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Logic-Driven Traffic Big Data Analytics: An Introduction

In: Logic-Driven Traffic Big Data Analytics

Author

Listed:
  • Shaopeng Zhong

    (Dalian University of Technology
    Southwest Jiaotong University)

  • Daniel (Jian) Sun

    (Chang’an University
    Shanghai Jiao Tong University)

Abstract

With the acceleration of urbanization, transportation problems have become the main bottleneck limiting the development of modern cities. Traffic congestion, traffic safety, environmental pollution, and other phenomena arise one after another, which have sharply affected the economic construction and operation efficiency of the city. The fundamental way to resolve the urban transportation problem is to integrate urban transportation and land use at the same time, feedback to each other, and achieve mutual coordination. Given this, this chapter firstly analyzes the interaction mechanism between land use and transportation from both macro and micro aspects and proposes the goal of integrated land use and transportation development. Secondly, four classic urban development cases, namely Stockholm, Copenhagen, New York, and Dalian, are selected to compare the process, causes, and social impact of their coordinated development model of transportation and land use. Finally, this chapter summarizes the transportation big data methods for investigating the relationship between transportation and land use. This chapter can not only provide a theoretical basis and technical groundwork for the research of subsequent chapters but also promote readers to have a more comprehensive understanding of the integration of transportation and land use.

Suggested Citation

  • Shaopeng Zhong & Daniel (Jian) Sun, 2022. "Logic-Driven Traffic Big Data Analytics: An Introduction," Springer Books, in: Logic-Driven Traffic Big Data Analytics, chapter 0, pages 1-32, Springer.
    • Handle: RePEc:spr:sprchp:978-981-16-8016-8_1
    DOI: 10.1007/978-981-16-8016-8_1
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    Cited by:

    1. HUO, Zhengqi & YANG, Xiaobao & LIU, Xiaobing & YAN, Xuedong, 2024. "Spatio-temporal analysis on online designated driving based on empirical data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 183(C).

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