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Simulating two-phase taxi service process by random walk theory.

Wei-Peng Nie1, Zhi-Dan Zhao2, Shi-Min Cai1

  • 1CompleX Lab, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China.

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This study analyzes taxi service data, revealing distinct temporal and spatial features for passenger pick-up and drop-off phases. Two independent random walk models explain these mechanisms, improving understanding of taxi service dynamics.

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Area of Science:

  • Complex Systems Science
  • Transportation Science
  • Data-Driven Modeling

Background:

  • Existing data-driven methods for city taxi services lack comprehensive models.
  • Current mathematical models fail to capture the full taxi service process, including distinct pick-up and drop-off phases.

Purpose of the Study:

  • To analyze taxi service data to understand distinct temporal and spatial features of pick-up and drop-off phases.
  • To develop independent mathematical models for simulating taxi service mechanisms.
  • To provide a framework for better understanding taxi service dynamics.

Main Methods:

  • Analysis of large-scale taxi service data from a major Chinese city.
  • Correlation analysis to determine interdependencies between service phases.
  • Development of two independent random walk models based on the Langevin equation.

Main Results:

  • Taxi service processes exhibit different temporal and spatial characteristics during the on-load (pick-up) and off-load (drop-off) phases.
  • A lack of significant correlation was found between the on-load and off-load phases.
  • The proposed models successfully describe the observed temporal and spatial features.

Conclusions:

  • The on-load and off-load phases of taxi services operate independently with distinct characteristics.
  • Random walk models based on the Langevin equation provide a robust framework for simulating and understanding taxi service mechanisms.
  • This research offers a novel mathematical approach to urban transportation system analysis.