Alternative Definitions of Passing Critical Gaps
DOI: 10.3141/2260-09
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Summary
This study addresses the lack of detailed modeling for passing behavior on two-lane highways, which constitute a significant portion of global road networks and are associated with high crash rates. While passing opportunities are critical for traffic flow, safety, and emissions, existing microscopic simulation tools often rely on simplified models based on outdated data. The authors specifically investigate how different definitions of "passing gaps" impact the accuracy of passing gap acceptance models. They argue that previous studies often ignored the driver’s motivation to pass and relied on a single, common gap definition, potentially limiting model explanatory power. To evaluate alternative gap definitions, the researchers developed a two-stage model structure: first, a binary choice representing the driver’s desire to pass, and second, a gap acceptance decision where the driver compares an available gap against a critical gap. Three specific definitions for the available passing gap were tested: (1) the time gap (TG) between consecutive opposing vehicles when the subject passes the lead vehicle; (2) the time for maneuver completion (TFMC), defined as the time gap between the opposing vehicle and the vehicle ahead of the subject; and (3) the time to collision (TTC) between the opposing vehicle and the subject vehicle at the moment the subject passes the lead vehicle. Data were collected using a fixed-base driving simulator (STISIM) with 100 participants. The experimental design employed a full factorial approach with 16 scenarios varying road geometry (curve radius), traffic conditions (speeds and gaps of lead and opposing vehicles), and vehicle types. This generated 14,654 passing gap observations, of which 696 resulted in completed passing maneuvers. The results indicate that the TTC-based model provided the best statistical fit to the data, outperforming the TG and TFMC models in maximum log-likelihood values and non-nested hypothesis tests. Across all models, the desire-to-pass component made a statistically significant contribution to explaining behavior, confirming that modeling driver motivation alongside gap acceptance is superior to single-step models. Key findings show that the desire to pass increases with the speed difference between the driver’s desired speed and the lead vehicle’s speed, and decreases as the following distance increases. For gap acceptance, critical gaps decreased with higher subject vehicle speeds and increased with higher lead vehicle speeds, reflecting the influence of relative speed. Critical gaps were also larger for trucks than passenger cars due to visibility and safety concerns, and smaller for younger drivers compared to older drivers. Road curvature significantly influenced acceptance, with higher acceptance probabilities on roads with larger curve radii. The study concludes that the definition of passing gaps significantly affects model performance, with the TTC definition proving most effective. It demonstrates that incorporating a driver’s desire to pass, along with variables capturing traffic, geometric, and driver characteristics, provides a more comprehensive explanation of passing behavior. These findings suggest that improved passing models, particularly those utilizing the TTC definition and two-stage decision structures, should be integrated into microscopic traffic simulation tools to better evaluate two-lane highway performance and safety.
Key finding
The passing gap acceptance model using the time-to-collision definition between the subject and opposing vehicles provided the best fit to the data, and modeling the driver's desire to pass significantly improved the explanation of passing behavior.
Methodology
simulator
Sample size: 100
Provenance
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-06-05 |
| archive | success | canonical_url | — | — | 1 | 2026-06-06 |
| extract | success | cached | — | — | 3 | 2026-06-10 |
| clean | success | clean | — | — | 1 | 2026-06-07 |
| chunk | success | chunk | — | — | 1 | 2026-06-07 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-07 |
| promote | success | — | — | — | 1 | 2026-06-05 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 2 | 2026-06-10 |
| tag | success | vector_similarity | — | — | 15 | 2026-06-11 |
| verify | partial | — | — | — | 2 | 2026-06-10 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified_with_issues.
Topics
Ranked by relevance to this paper. Hover a topic for its definition.
- gap acceptance
- following distance
- rail grade crossings
- lane changing
- pedestrian behavior perception
- mental model of traffic
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, crash risk outcomes
- Theoretical Contribution: computational model