High-resolution simulation-based analysis of leading vehicle acceleration profiles at signalized intersections for emission modeling

Sicong Zhu, Inhi Kim, Keechoo Choi

Research output: Contribution to journalArticleResearchpeer-review

Abstract

The acceleration profile of leading vehicles at intersections is critical for emission estimation and microlevel queue simulation. Data obtained from experiments using a high-resolution driving simulator can deliver useful insights into microscale acceleration behaviors at signalized intersections. Acceleration data of the leading vehicles in queues are collected by the simulator. The observed accelerations are found to be stochastic. The acceleration characteristics are also significantly diversified among participants. Hence, a Markov chain is implemented to simulate the acceleration behaviors. The acceleration data are classified into varied operation states. And the Markov chain reconstructs the acceleration profiles of leading vehicles and reproduces the randomness of acceleration behaviors. Among numerous candidate profiles, a speed profile is selected by a proposed criterion that represents the typical acceleration behaviors at signalized intersections.

Original languageEnglish
Pages (from-to)375-385
Number of pages11
JournalInternational Journal of Sustainable Transportation
Volume15
Issue number5
DOIs
Publication statusPublished - 2021

Keywords

  • Driving behaviors
  • Markov chain
  • simulator
  • speed profile

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