Index - Using Data Analytics for Cost-Effective Prediction of Road Conditions: Case of The Pavement Condition Index , November 2018

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Transportation Innovations</span></p> </div> </div> <div style="background-color:#FFF; text-align:left; margin:0 auto;"> <table align="center" border="0" cellpadding="1" cellspacing="0" width="100%"> <tr bgcolor="black"> <td width="70%"> </td> <td align="left"><form accept-charset="UTF-8" action="//web.archive.org/web/20190202153647/https://search.usa.gov/search" class="has-query-term" id="search-bar" method="get"> <table border="1" cellpadding="0" cellspacing="0" align="left"> <tr> <td><input type="text" class="srchbox" name="query" maxlength="256" style="width:200px;" value="Search Research & Technology" onblur="if(this.value == '') {this.value = 'Search Research & Technology';}" onfocus="if(this.value == 'Search Research & Technology'){this.value = '';}" id="sterms"/></td> <td><input type="image" class="srchbtn" src="/web/20190202153647im_/https://www.fhwa.dot.gov/images/fhwa2/bg/imgbgsrchbtn.png" name="btnG" value="Search" title="Submit Search"/></td> </tr> </table> <input id="sitelimit" name="sitelimit" type="hidden" value="fhwa.dot.gov/publications"/> <input name="utf8" type="hidden" value="✓"/> <input id="affiliate" name="affiliate" type="hidden" value="dot-fhwa"/> </form></td> </tr> </table> <table align="center" border="0" cellpadding="5" cellspacing="0" width="100%"> <tr> <td bgcolor="#6699FF" align="center"><strong style=" color:white; text-transform:uppercase; font-size:52px">SUMMARY REPORT</strong></td> </tr> <tr> <td bgcolor="#6699FF" align="center"><span><strong>This summary report is an archived publication and may contain dated technical, contact, and link information</strong></span></td> </tr> </table> <table align="center" border="0" cellpadding="5" cellspacing="0" width="90%"> <tr> <td align="left" valign="top"><ul class="b2c"> <li class="b2c"> <a href="https://web.archive.org/web/20190202153647/https://www.fhwa.dot.gov/">Federal Highway Administration</a> > </li> <li class="b2c"> <a href="/web/20190202153647/https://www.fhwa.dot.gov/publications/">Publications</a> > </li> <li class="b2c"> <a href="/web/20190202153647/https://www.fhwa.dot.gov/publications/lists/021.cfm">Research Publications</a> > </li> <li class="b2c"> <a href="/web/20190202153647/https://www.fhwa.dot.gov/publications/lists/technical/infrastructure/pavements/ltpp/">LTPP Publications</a> > </li> <li class="b2c"> <a href="index.cfm">18065</a> > </li> <li class="b2c"> Index </li> </ul></td> </tr> </table> <table align="center" border="0" cellpadding="4" cellspacing="0" width="100%"> <tr> <td width="100%" align="right"><a href="https://web.archive.org/web/20190202153647/https://highways.dot.gov/research-resources"><img src="https://web.archive.org/web/20190202153647im_/https://www.fhwa.dot.gov/publications/images/btpl_button.png" width="146" height="24" alt="Back to Publication List" title="Back to Publication List"/></a></td><td>        </td> </tr> </table> <div class="printonly"> <table width="90%" align="center"> <tr><td align="right">Publication Number:  FHWA-HRT-18-065    Date:  November 2018</td></tr> </table> </div> <table align="center" border="0" cellpadding="5" cellspacing="0" width="90%"> <tr> <td align="right"><div align="right"><strong>Publication Number:</strong> FHWA-HRT-18-065<br/> <strong>Date:</strong> November 2018<br/> </div></td> </tr> </table> <div class="center90table"> <a name="content" id="content"></a> <p> </p> <h1 align="center"><span class="center style3"> Using Data Analytics for Cost-Effective Prediction of Road Conditions: Case of The Pavement Condition Index </span></h1> <p align="center"><a href="18065.pdf"><strong>PDF Version</strong></a> (998 KB)</p> <p align="center"><a href="errata.cfm"><strong style="color:#FF0000;">HTML Version of Errata for FHWA-HRT-18-065</strong></a></p> <p align="center"><a href="18065_errata.pdf"><strong style="color:#FF0000;">PDF version of Errata</strong></a></p> <div align="center"><p class="pdfview">PDF files can be viewed with the <a href="/web/20190202153647/https://www.fhwa.dot.gov/exit.cfm?link=http://get.adobe.com/reader/">Acrobat® Reader®</a></p> </div> <p> </p> <h2 align="center">ABSTRACT</h2> <p>Municipalities and transportation departments devote considerable effort to collecting data—particularly in relation to road conditions. Many small municipalities do not have sufficient resources to collect data regularly. In larger municipalities, on the other hand, collecting field-based data may have negative impacts in terms of crew safety and traffic interruptions; data analytics could help reduce these negative impacts. In this study, data analytics is used to test if affordable and easy-to-collect data can be used to predict future values of the Pavement Condition Index (PCI). North American transportation departments frequently use the PCI to assess road conditions. To calculate the PCI, transportation departments and municipalities must collect distress data and their severity levels.</p> <p>In this study, the Long-Term Pavement Performance (LTPP) database was used as the source of data.<sup>(</sup><sup>1</sup><sup>)</sup> Because the LTPP database does not include the PCI values of its road sections, the first step in the study was to develop a program to calculate the PCI from the distress values in the LTPP database. Next, a set of pavement attributes was selected—mainly based on the ease of collection and cost effectiveness. The researchers tested the potential importance of these attributes in predicting PCI using seven ranking algorithms and a heuristic feature-selection algorithm. </p> <p>Two types of decision trees were trained based on 942 examples of asphalt roads. Using combinations of 14 attributes, a set of decision trees was developed to predict the level of PCI deterioration with an accuracy of more than 70 percent. Finally, the accuracy and confusion matrices of different decision trees were compared to test the impact of each attribute on prediction accuracy. This method can help municipalities and transportation departments identify the most significant attributes to accurately predict road performance indicators (PIs).</p> <p align="center"><img src="/web/20190202153647im_/https://www.fhwa.dot.gov/publications/research/infrastructure/pavements/ltpp/18065/images/FHWA_HRT_18_065_pdf_coverimage.jpg" width="300" height="388" alt="FHWA-HRT-18-065 PDF Cover Image" title="FHWA-HRT-18-065 PDF Cover Image"/></p> <p> </p> </div> <p> </p> <div id="footer" style="border-top:#999 3px solid;"> <div style=" margin-left:10%;"> <table id="footermain" align="left" border="0" cellpadding="2" cellspacing="5"> <tr> <td class="left" style="line-height:1.5em"><div class="zeromarginblue"> Page Owner: Office of Research, Development, and Technology, Office of Infrastructure, RDT <br/> </div> <div class="zeromargin"> Topics: research, infrastructure, pavements and materials, ltpp<br/> Keywords: research, infrastructure, pavements and materials, Machine learning, data analytics, Pavement Condition Index, data collection, asset management, deterioration modeling. <br/> TRT Terms: research, facilities, transportation, highway facilities, roads, parts of roads, pavements, ltpp<br/> Scheduled Update: Archive - No Update needed <br/> </div> <div id="moddate">This page last modified on 01/03/2019 </div></td> </tr> </table> </div> </div> <div class="clearall"></div> </div> <table><tr><td><p class="txtright txtsmall noprint returntoplink">Return to top</p></td></tr></table> <p align="left">  <div id="fhwafooter"> <div class="fhwacontainer"> <div class="fhwasign" title="U.S. Department of Transportation/Federal Highway Administration"></div> <div class="noprint"><a href="/web/20190202153647/https://www.fhwa.dot.gov/privacy.cfm">Privacy Policy</a> | <a href="/web/20190202153647/https://www.fhwa.dot.gov/foia/">Freedom of Information Act (FOIA)</a> | <a href="/web/20190202153647/https://www.fhwa.dot.gov/accessibility/">Accessibility</a> | <a href="/web/20190202153647/https://www.fhwa.dot.gov/webpolicies/publishschedule.cfm">Web Policies & Notices</a> | <a href="https://web.archive.org/web/20190202153647/https://www.transportation.gov/civil-rights/civil-rights-awareness-enforcement/no-fear-act">No Fear Act</a> | <a href="https://web.archive.org/web/20190202153647/https://www.oig.dot.gov/Hotline">Report Waste, Fraud and Abuse</a> | <a href="https://web.archive.org/web/20190202153647/https://www.transportation.gov/">U.S. DOT Home</a> | <a href="https://web.archive.org/web/20190202153647/https://www.usa.gov/">USA.gov</a> | <a href="https://web.archive.org/web/20190202153647/https://www.whitehouse.gov/">WhiteHouse.gov</a><br/><br/></div> <div> <a href="/web/20190202153647/https://www.fhwa.dot.gov/">Federal Highway Administration</a> | 1200 New Jersey Avenue, SE | Washington, DC 20590 | 202-366-4000 <br/><a href="/web/20190202153647/https://www.fhwa.dot.gov/research/">Turner-Fairbank Highway Research Center</a> | 6300 Georgetown Pike | McLean, VA | 22101 </div> </div> </div>  </p> </body> </html>

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Index - Using Data Analytics for Cost-Effective Prediction of Road Conditions: Case of The Pavement Condition Index , November 2018 - FHWA-HRT-18-065