Impact of Carpooling on Trip-Chaining Behavior and Emission Reductions
Bibliographic record
Abstract
Within an activity-based framework, the hypothesis that carpooling imposes a constraint on the way individuals organize their activities was tested, with resulting impacts on traffic peak congestion and trip-chaining behavior. The hypothesis was tested by estimating the joint probability density functions (PDFs) of subsistence, maintenance, and discretionary trips made by carpool and single-occupancy vehicle (SOV) users. Results show that whereas SOV maintenance and discretionary activities are linked to subsistence trips in a joint undertaking, carpool activities suggest discontinuity in the formation of trip chains. A comparison of the joint PDF of subsistence and discretionary activities reveals that trips are conducted either before or after the commute schedule; this results in a temporal shift that reduces peak-period traffic congestion and emission pollution. Marked differences are found to exist between SOV and carpool trip-chaining behavior. Carpoolers are more likely to engage in a greater number of cold-start trip chains; this behavior uncovers a potential negative impact on emission pollution. These findings suggest that a comprehensive approach to the evaluation of carpool programs must take into account the benefits as well as any ensuing negative externalities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".