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Record W4376276211 · doi:10.4337/9781800375550.00032

Road pricing applications in North America

2023· book-chapter· en· W4376276211 on OpenAlexaboutno aff
Mark Burris, John F. Brady, Sruthi Ashraf

Bibliographic record

VenueEdward Elgar Publishing eBooks · 2023
Typebook-chapter
Languageen
FieldSocial Sciences
TopicTransportation Planning and Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsRevenueMetropolitan areaRoad pricingFinanceBusinessPricing strategiesTransport engineeringMarketingEngineeringGeographyTraffic congestion

Abstract

fetched live from OpenAlex

This chapter discusses transport pricing and funding in the United States and Canada, with a focus on road pricing in the United States. The chapter begins with a brief history of road pricing in the United States from the earliest days of priced travel until 1995 when the first innovative, priced managed lane projects opened. Now a common part of highway networks in major metropolitan regions, these projects have been extensively studied. This chapter briefly discusses the growth in innovative funding and financing through those priced facilities before focusing on more recent insights into these innovative projects. We review three key issues with initiating pricing projects: (1) the ability of the priced facility to garner support and meet traveler expectations, (2) the industry’s ability to predict travel on, and revenue from, potential priced facilities, and (3) the choice of a dynamic or variable pricing mechanism. These three issues have gained increased importance as priced facilities have moved from infancy to a high growth stage. This chapter discusses transport pricing and funding in the United States and Canada, with a focus on road pricing in the United States. The chapter begins with a brief history of road pricing in the United States from the earliest days of priced travel until 1995 when the first innovative, priced managed lane projects opened. Now a common part of highway networks in major metropolitan regions, these projects have been extensively studied. This chapter briefly discusses the growth in innovative funding and financing through those priced facilities before focusing on more recent insights into these innovative projects. We review three key issues with initiating pricing projects: (1) the ability of the priced facility to garner support and meet traveler expectations, (2) the industry’s ability to predict travel on, and revenue from, potential priced facilities, and (3) the choice of a dynamic or variable pricing mechanism. These three issues have gained increased importance as priced facilities have moved from infancy to a high growth stage. This chapter discusses transport pricing and funding in the United States and Canada, with a focus on road pricing in the United States. The chapter begins with a brief history of road pricing in the United States from the earliest days of priced travel until 1995 when the first innovative, priced managed lane projects opened. Now a common part of highway networks in major metropolitan regions, these projects have been extensively studied. This chapter briefly discusses the growth in innovative funding and financing through those priced facilities before focusing on more recent insights into these innovative projects. We review three key issues with initiating pricing projects: (1) the ability of the priced facility to garner support and meet traveler expectations, (2) the industry’s ability to predict travel on, and revenue from, potential priced facilities, and (3) the choice of a dynamic or variable pricing mechanism. These three issues have gained increased importance as priced facilities have moved from infancy to a high growth stage.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.952
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.026
GPT teacher head0.261
Teacher spread0.235 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2023
Admission routes1
Has abstractyes

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