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Record W3214287578 · doi:10.22060/ajce.2020.17644.5638

The Assessment of the Change in the Share of Public Transportation by Applying Demand Management Policies: Evidence from Extending Traffic Restriction to the Air Pollution Control Area in Tehran

2021· article· en· W3214287578 on OpenAlexaff
Amir Tayarani Yousefabadi, Alireza Mahpour, Iman Farzin, Amir Mohammadian Amiri

Bibliographic record

VenueAUT Journal of Civil Engineering · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicTransportation Planning and Optimization
Canadian institutionsMcMaster University
Fundersnot available
KeywordsTollPublic transportTransport engineeringTraffic congestionPaymentToll roadControl (management)BusinessPlan (archaeology)Environmental economicsEngineeringGeographyEconomicsFinance

Abstract

fetched live from OpenAlex

The growing car ownership has caused a lot of problems such as increased travel time and environmental pollution. In recent years, different policies have been proposed for travel demand management. Among these plans conducted in Tehran, the Odd-Even day plan starting from the door of each house or the extension of traffic congestion zone to the Odd-Even plan zone can be mentioned. In the present study, to determine the change in the behavior of the people traveling in the air pollution control area in Tehran in return for the payment of a various toll and exploring their pro-environmental beliefs and attitudes which supports the Value-Belief-Norm (VBN) theory, a stated preference questionnaire has been designed, and 500 of it were distributed among the individuals in this area and then collected. The results show that 51% of people have used their private cars to travel within the area. 24% of people have used semipublic transportation, and 25% have used public transportation (bus and subway) for their traveling. Based on the tolling design scenario, which was with an increase of 15 to 18% of the base traffic congestion zone prices of 2016, the relative frequency of using four types of non-public transportation (which is the sum of private vehicles and semipublic transportation) decreased 20 and 21% for different types of tolls throughout the day.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.946
Threshold uncertainty score0.475

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.030
GPT teacher head0.292
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2021
Admission routes1
Has abstractyes

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