Verification and Calibration of Microscopic Traffic Simulation Using NDS and Video Data for Alternative Intersections and Freeway Merge and Diverge Areas
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Summary
This study addresses the need for accurate traffic microsimulation calibration for alternative intersection designs and freeway merge/diverge areas in Alabama. As the Alabama Department of Transportation (ALDOT) increasingly adopts complex facilities like roundabouts, Diverging Diamond Interchanges (DDIs), and Restricted Crossing U-turns (RCUTs), default parameters in simulation software often fail to capture unique driver behaviors and geometric constraints. This discrepancy can lead to inaccurate operational assessments and poor design decisions. The research aimed to develop state-specific calibration and validation guidelines for PTV VISSIM models using empirical data to reflect local driving conditions. The methodology involved collecting data from 21 locations across Alabama, including 18 roundabouts, one DDI, one RCUT, one freeway work zone, and one freeway exit ramp. Researchers utilized drone video footage to capture vehicle trajectories and movement characteristics, processing this data with the Datafromsky tool to extract specific metrics. Additionally, the study incorporated Naturalistic Driving Study (NDS) data and roadway geometry information. Using the VISSIM COM interface, the team implemented an automated calibration workflow to determine key parameters, including priority rules at conflict points, car-following behavior, speed distributions, and lane-changing urgency. Model performance was validated by comparing simulated outputs against field data, such as travel times, speed distributions, and traffic volumes. The findings resulted in specific calibration guidelines for each facility type. For roundabouts, the study defined parameters for speed distributions, priority rules, and car-following models, accounting for variations in non-circular geometries. For DDIs, guidelines were established for speed distribution, car-following, lane-change behavior, and priority rules, addressing the unique signal timing and geometric features. RCUT calibration focused on lane utilization, stopping behavior, and acceleration/deceleration functions for weaving movements. For freeway merge and diverge areas, the study provided parameters for merging urgency, deceleration profiles, and speed distributions for both passenger cars and trucks. The calibrated models demonstrated improved alignment with observed field data compared to default settings. The significance of this work lies in providing ALDOT with a standardized, high-fidelity framework for traffic simulation. By translating observed driver behavior into recommended VISSIM parameters, the guidelines enhance the accuracy of operational assessments for alternative intersections and freeway facilities. This supports more informed investment and design decisions, ensuring that future projects are neither under- nor over-designed. The study contributes to the broader field by demonstrating the effectiveness of integrating drone-based trajectory data and NDS databases into microsimulation calibration workflows for complex traffic environments.
Key finding
The study developed and validated Alabama-specific calibration guidelines for PTV VISSIM microsimulation models of roundabouts, diverging diamond interchanges, restricted crossing U-turns, and freeway merge/diverge areas using drone-derived trajectory data.
Methodology
field_study
Sample size: 21
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. Discovered via bulk_ingest_rosap on 2026-05-23 (5 acquisition events logged).
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | rosap | — | — | 2 | 2026-05-23 |
| archive | success | — | — | — | 1 | 2026-05-23 |
| extract | success | cached | — | — | 2 | 2026-06-10 |
| clean | success | — | — | — | 1 | 2026-06-01 |
| chunk | success | — | — | — | 1 | 2026-06-01 |
| embed | success | — | — | — | 1 | 2026-06-02 |
| enrich | success | — | — | — | 1 | 2026-05-23 |
| promote | success | — | — | — | 1 | 2026-05-23 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 3 | 2026-06-10 |
| tag | success | vector_similarity | — | — | 18 | 2026-06-11 |
| verify | success | — | — | — | 2 | 2026-06-10 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.
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- Methodological Resource: dataset resource, validation psychometrics, tool software