avaliação de medidas de desempenho para rodovias de pista simples obtidas a partir de relações fluxo-velocidade
Clicks: 15
ID: 142822
2016
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Steady Performance
4.2
/100
15 views
4 readers
AI Quality Assessment
Not analyzed
Readership in this journal
SteadyRanked #25 of 33 articles by views in nature machine intelligence
Most read
Least read
Bar heights use a square-root scale.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
The Highway Capacity Manual 2010 uses Percent-Time-Spent Following (PTSF) and Average Travel Speed to estimate level of service on two-lane rural highways. As it is almost impossible to observe PTSF directly in the field, many researchers have been searching for alternative measures of effectiveness (MDs) that can be obtained from traffic stream parameters. Moreover, speed-flow relationships have a fundamental role in LOS estimation in the HCM2010 and in the German HBS2001. The objective of this paper was to assess MDs derived from speed-flow relationships that could ade-quately describe quality of service on two-lane rural highways in Brazil. Speed-flow models were fitted for different condi-tions (geometry, percentages of heavy vehicles and free-flow speeds), using synthetic traffic data produced by a recalibrated version of CORSIM. Comparisons between the values obtained using these models and field data indicated that average travel speed of cars and density for cars could replace the current HCM criteria for the estimation of LOS on two-lane rural highways in Brazil.
| Reference Key |
junior2016transportesavaliao
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | ;Jose Elievam Bessa Junior;Jose Reynaldo Setti |
| Journal | nature machine intelligence |
| Year | 2016 |
| DOI |
10.14295/transportes.v24i3.1145
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.