Using a Neural Network to Analyze the Impact of Passenger Activity on Bus Dwell Time and Travel Time

Authors

  • Mei Chen
  • Xiaobo Liu

DOI:

https://doi.org/10.5399/osu/jtrf.44.3.581

Abstract

This paper applies neural network modeling approach to analyze the impact of passenger activities on bus dwell time and station-to-station travel time. Data used to develop the model was collected by onboard AVL/APC devices. Sensitivity analyses based on a trained neural network were performed to evaluate the relative significance of each passenger activity variable to variation of dwell time and/or station-to-station travel time. Transit providers can use these methods to identify the causes of schedule deviation and to develop improvement measures that are most effective to transit service.

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Published

2010-10-11

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Section

Articles