Determinants Behind the Taste Variation in Discretionary Lane Changing Behavior of Drivers Facing Downstream Queues

Matin, Seyed Hamed Seyed; Kordani, Ali Abdi · 2025 · DOAJ

DOI: 10.5507/tots.2025.001

archive: archived pipeline: cataloged verified

Get this paper ↗ (DOI — opens at the source; we link to it, we don't host it)

Summary

This study investigates the determinants of discretionary lane-changing behavior among drivers encountering downstream traffic queues, addressing a gap in literature that often treats drivers as homogeneous entities. The research aims to quantify how socioeconomic factors, driving styles, attitudinal traits, and road environment characteristics influence lane-changing decisions. By focusing on discretionary changes—where drivers switch lanes to increase speed rather than to exit—the paper seeks to improve traffic flow models by accounting for unobserved heterogeneity and taste variation among drivers. The study is situated in Tehran, Iran, providing insights into driving behaviors in a developing country with distinct cultural and infrastructural norms. The methodology combines video-recording data from the Niayesh Highway in Tehran with a behavioral survey administered to drivers. Video footage captured vehicle trajectories, speeds, and lateral positions in a congested, four-lane urban environment, while the survey collected data on 124 valid respondents regarding their demographics, driving history, and attitudes. The researchers employed discrete choice modeling, specifically comparing standard binary logit and mixed logit models (MLM). The MLM was selected for its ability to account for random parameter variations, thereby capturing individual differences in how drivers value specific attributes, such as lateral distance or speed differentials. Results indicate that the mixed logit model provided a superior fit compared to the standard logit model, confirming the presence of significant taste variation. Key findings reveal that higher target vehicle speed, greater lateral distance from left-side obstacles, and a propensity for law evasion (e.g., running yellow lights) positively correlate with the likelihood of lane changing. Conversely, drivers aged 41–50 and those who maintain safe following distances were less likely to change lanes. Interestingly, drivers who had experienced at least two accidents in the past year showed a higher likelihood of lane changing, suggesting that accident history does not necessarily deter risky maneuvers. Additionally, the speed of the preceding vehicle and lateral distance from right-side obstacles significantly influenced the decision to remain in the current lane. The significance of this research lies in its demonstration that driver heterogeneity is a critical factor in traffic dynamics. By integrating attitudinal and socioeconomic variables with traffic data, the study offers a more nuanced understanding of discretionary lane-changing behavior than traditional macroscopic or microscopic models. These findings can enhance the accuracy of traffic flow simulations and safety assessments, particularly in congested urban environments. The study underscores the need for future models to incorporate individual taste variations and attitudinal traits to better replicate and predict real-world traffic behaviors.

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed.

Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• lane changing
• traffic density
• work zones
• speed choice

Information type

What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).

• Empirical Findings: behavioral performance data