Comparison between Physical Parameters and Sensory Parameters Regarding Travel Behavior Based on Sensitivity Analysis
Bibliographic record
Abstract
An effective way to optimize decision-making regarding the transport mode choice in the transportation system is improving or changing the travel cost, the travel time, or some other travel characteristics by using sensitivity analysis. This method encourages travelers to switch from private transportation to public transport, thus reducing pollution and emission. Furthermore, by searching for the most sensitive factors in travel behavior, the sensitivity analysis might highlight the directions of the improvement. However, according to previous studies, travelers will transfer from one transport mode to another only if the utility of the new choice is higher than the original transport mode. In the current paper, sensitivity analysis is applied to provide a comparison between the impacts of the physical and sensory parameters on the travel behavior and transport mode choice based on a utility function. The multinomial logit (MNL) model is used to estimate and perform the sensitivity analysis of the main variables. The sensitivity analysis demonstrates the degree of the travelers’ sensitivity to changes in the travel characteristics including both physical and sensory parameters. The models are calibrated with the NLOGIT software and validated through statistical indicators; thus, the essential factors influencing the choices are obtained. The input variables selected for the models are based on the data collected in Budapest, Hungary. The sensitivity analysis is determined by the outputs of the variables based on the changes of the input variables. As the results show, the travelers have more sensitivity to the changes in the physical parameters. Furthermore, the outcomes indicate that the travel cost is an essential variable, which greatly affects the decisions related to the transport mode choice. From the sensory parameters, the comfort factor has more influence than other factors. The results of the analysis present that the travelers’ sensitivity to changes in the travel utilities of the travel characteristics impacts the decisions regarding the mode choice behavior significantly.
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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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".