Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Traffic calming (TC) has been applied widely for several decades, although approaches to evaluating its effects on speeds have been inconsistent. This resulted in limited comparable and robust evidence to support practitioner guidance for TC design. To fill this gap and suggest best practices for the evaluation of TC effects on speeds, we performed a systematic review of 158 publications. We distilled information related to five research questions: Which measurement sensor was used? How was speed measured? Was free-flow speed considered? What was the sampling density? How were sample considerations reported? In addition to coding the studies based on these research questions, we rated them based on scientific robustness. The review confirmed the inconsistent state of evaluation practice. Most common evaluation approaches employed static detectors, low levels of control for bias (simple before-after), and unknown survey periods. The review found that the most robust evaluation practices involved multivariate before-after or cross-sectional study designs, used dynamic measurement of speeds (e.g., probe vehicles, simulations), large samples of vehicles, and more precise evaluation of speed changes using speed-distance graphs. These findings could guide more consistent and robust evaluation practice, and thus help to improve evidence-based TC guidance for creating safer and more sustainable neighborhoods.
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Source |
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http://dx.doi.org/10.1016/j.aap.2023.107073 | DOI Listing |
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