Document Type

Pre-Print

Publication Date

4-2019

Subjects

Bus lines -- Data processing, Bus lines -- Performance, Bus lines -- Management, Travel time (Traffic engineering), Local transit -- Oregon -- Portland -- Management, Linear regression

Abstract

Understanding the key factors that contribute to transit travel times and travel time variability is an essential part of transit planning and research. Delay that occurs when buses service bus stops, dwell time, is one of the main sources of travel time variability and has therefore been the subject of ongoing research to identify and quantify its determinants. Previous research has focused on testing new variables using linear regressions that may be added to models to improve predictions. An important assumption of linear regression models used in past research efforts is homoscedasticity or the equal distribution of the residuals across all values of the predicted dwell times. The homoscedasticity assumption is usually violated in linear regressions models of dwell time and this can lead to inconsistent and inefficient estimations of the independent variable coefficients. Log-linear models can sometimes correct for the lack of homoscedasticity, i.e. for heteroscedasticity in the residual distribution. Quantile regressions, which predict the conditional quantiles, rather than the conditional mean, are non-parametric and therefore more robust estimators in the presence of heteroscedasticity. This research furthers the understanding of established dwell determinants using these novel approaches to estimate dwell and provides a relatively simple approach to improve existing models at bus stops with low average dwell times.

Description

This is the author’s version of a work that was accepted for publication in the Transportation Research Record. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document.

The copyright holder for this preprint is the author/funder. All rights reserved. No reuse allowed without permission.

Persistent Identifier

https://archives.pdx.edu/ds/psu/28444

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