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Bus travel time reliability incorporating stop waiting time and in-vehicle travel time with AVL data

  • Zixu Zhuang
  • , Zhanhong Cheng
  • , Jia Yao*
  • , Jian Wang
  • , Shi An
  • *Corresponding author for this work
  • School of Transportation Science and Engineering, Harbin Institute of Technology
  • Dalian University of Technology

Research output: Contribution to journalArticlepeer-review

Abstract

Improving bus travel time reliability can attract more commuters to use bus transit, and therefore reduces the share of cars and alleviates traffic congestion. This paper formulates a new bus travel time reliability metric that jointly considers two stochastic processes: the in-stop waiting process and in-vehicle travel time process, and the bus travel time reliability function is calculated by the convolution of independent events’ probabilities. The new reliability metric is defined as the probability when bus travel time is less than a certain threshold and can be used in both conditions with and without bus transfer. Next, Automatic Vehicle Location (AVL) data of the city of Harbin is used to demonstrate the applicability of the proposed method. Results show that factors such as weather, day of the week, departure time, travel distance, and the distance from the boarding stop to the bus departure station can significantly affect the travel time reliability. Then, a case with low bus departure frequency is analyzed to show the impact of travelers’ arrival distribution on their bus travel time reliability. Further, it is demonstrated that the travel time reliabilities of two bus transfer schemes of the same Origin–Destination (O–D) pair can have significantly different patterns. Understanding the bus travel time reliability pattern of the alternative bus routes can help passengers to choose a more reliable bus route under different conditions. The proposed bus travel time reliability metric is tested to be sensitive to the effect of different factors and can be applied in bus route recommendation, bus service evaluation, and optimization.

Original languageEnglish
Article number71
JournalInternational Journal of Coal Science and Technology
Volume9
Issue number1
DOIs
StatePublished - Dec 2022
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure
  2. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

Keywords

  • Automatic vehicle location
  • Bus departure frequency
  • Bus travel time
  • Reliability

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