an approach to an intersection traffic delay study based on shift-share analysis
Clicks: 179
ID: 224792
2015
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
30.0
/100
179 views
30 readers
AI Quality Assessment
Not analyzed
Readership in this journal
SteadyRanked #35 of 52 articles by views in psychoanalytic review
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
Intersection traffic delay research has traditionally placed greater emphasis on the study of through and left-turning vehicles than right-turning ones, which often renders existing methods or models inapplicable to intersections with heavy pedestrian and non-motorized traffic. In the meantime, there is also a need for understanding the relations between different types of delay and how they each contribute to the total delay of the entire intersection. In order to address these issues, this paper first examines models that focus on through and left-turn traffic delays, taking into account the presence of heavy mixed traffic flows that are prevalent in developing countries, then establishes a model for calculating right-turn traffic delay and, last, proposes an approach to analyzing how much each of the three types of traffic delay contributes to the total delay of the intersection, based on the application of shift-share analysis (SSA), which has been applied extensively in the field of economics.
| Reference Key |
xi2015informationan
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | ;Jianfeng Xi;Wei Li;Shengli Wang;Chuanjiu Wang |
| Journal | psychoanalytic review |
| Year | 2015 |
| DOI |
10.3390/info6020246
|
| 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.