Application of System Dynamics in Car-Following Models
Why this work is in the frame
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Bibliographic record
Abstract
Over the past 50 years, many different “car-following” models have been proposed to describe driver behavior in a traffic stream. A number of inherent assumptions about human constraints and preferences in existing car-following models have hampered their relevance for use in the design and evaluation of different Intelligent Transportation Systems technologies and/or controls such as Advanced Vehicle Control and Safety Systems. In this paper we introduce a new Systems Dynamic (SD) car-following model that addresses many of the shortcomings of existing car-following models and provides a more relevant platform for simulating driver behavior in all types of car-following situations. The proposed SD model was developed and validated based on observed vehicle tracking data. Preliminary results suggest that the proposed model yields speed and spacing profiles for vehicles in “real time” that compare well with those observed empirically.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it