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ICTD 2025

Street & Highway Operations

POSTER RECEPTION (View list of posters here)

Discretionary Lane Changing Stimuli Using Mixed Methodological Approach

Tuesday, June 10, 2025
4:45 PM – 6:00 PM MT
Abstract: This paper seeks to capture the factors that influence discretionary lane changing execution and categorize these factors into different clusters. The researchers use a mixed methodological approach including qualitative and quantitative analysis to organize these stimuli into clusters and calculate the correlation of each factor with the overall cluster; the mixed methods approach also provides the framework for determining the importance of each factor. This study uses three focus groups whose participants have driving experience in the United States to obtain possible lane changing reasons and factors. The focus groups identify forty discretionary lane changing reasons, which appear to cluster into safety, environmental, emotional and temporal categories. The study uses a stated preference survey of 220 respondents to determine the importance of the discretionary lane change stimuli. Exploratory Factor Analysis (EFA) as a data driven approach is conducted to cluster lane changing factors into different categories. The importance of each factor within each cluster is investigated in this study as well.
This study provides a path and understanding of lane changing reasons as preliminary effort for developing a scale for “lane changing propensity”. Also The outcomes of this study appear helpful for transportation modelers to understand the decision-making process of drivers from a different perspective.

Learning Objectives:

Attendees can expect to learn the following from this session:
  • To have better understanding of the reasons behind lane changing behavior. Moreover, participants understand lane changing reasons as preliminary effort for developing a scale for “lane changing propensity”.
  • have a better vision about the decision-making process of drivers from a different perspective. That would be beneficial for specifically transportation modelers.
  • Gain analysis knowledge of mixed methodological (qualitative and quantitative analysis) approach for research projects.