Conference Proceedings 26 - Transportation Research Board

TRANSPORTATION DATA AND PERFORMANCE MEASUREMENT 83widths for doing capacity analysis. Therefore, collectingbasic inventory data for new constructionmight be the highest priority. Collecting new constructiondata could be more important than collectingpavement roughness data, which changes slowlyenough that delaying collection for several monthswould not affect system-level analysis.FIGURE 3Location of ramp along mainline.data. A follow-up to the audit will occur soon withall data collectors to review what was learned and toincorporate the findings into a revised data-collectionmanual.Data LifeData collection is usually expensive. Therefore, it isimportant to understand the useful life of data so thatit can be leveraged as much as possible before anupdate is necessary. To determine the data’s usefullife, the data’s accuracy necessary to address businessrequirements must be determined.The useful life of data can be derived from the responsibleuse of the data. For example, highly detailedpavement condition ratings can be used to predictpavement condition for 5 to 6 years from thedate of inspection. This means that one can confidently,or responsibly, generate a 5- to 6-year improvementprogram based on the data. It is temptingto generate long-term [or out-year (6 years)] improvementprograms because pavement deteriorationcurves can forecast conditions for up to 40 years.Although this forecast is possible mathematically, aresponsible user will seek to understand the variablesaffecting data quality over time; this understandingshould be used as the basis for determining the frequencywith which to update and use data.In contrast, some data have a long, useful life.Pavement width, shoulder width, pavement type, intersectionlocation, and median location and type remainthe same from the time they are built until reconstruction,so it is not necessary to plan a cyclicalcollection of such data. It also may not be necessaryto collect the data in the field but to use its built plansor a photolog in the office to collect the data.It is also wise to prioritize the importance of eachdata item. Although pavement and shoulder widthremains static between construction times, it is importantto have the current pavement and shoulderAutomatic or Manual CollectionAutomation of data collection usually enables datato be collected quickly and efficiently. If the automationequipment is cost-effective and the data canbe processed efficiently, then automation is likely tobe a viable alternative to manual data collection.However, automated collection methods are not alwaysthe best way to collect data. Automation canwork well if a large volume of data is collected daily(e.g., automatic traffic count and classification stations)or thousands of miles of road per year arerated (e.g., collecting pavement roughness). However,for data that is stagnant, such as political boundaries,manual collection may be more economical.Automated data collection usually implies speedand efficiency, but the real value of automation isrealized when speed is coupled with increased accuracy,precision, and repeatability of the data. Thedrawbacks of automated data collection typically relateto significant up-front capital costs and ongoingmaintenance costs for equipment.Defining the benefits of accuracy and precision fordata items is a good starting point for the evaluationof automation benefits. Some data items do not lendthemselves to accurate, precise, and efficient manualmeasurement; for example, it is almost impossible toobtain pavement roughness data and standardized,repeatable manual determinations of pavementroughness. Thus, automation is clearly a superior alternative.But for many data items, automation is notso easily distinguished as a superior data-collectionmethod; in fact, automation might not be the bestapproach. The cost of equipment must be weighedagainst the benefits of enhanced accuracy, speed, andrepeatability when an automated data-collection solutionis considered (Figures 4 and 5).Data may be collected through a combination ofboth manual and automated processes. Handhelddevices that allow collectors to input and store dataand then easily upload into a larger inventory systemcan contribute significantly to consistency andrepeatability (Figure 6). Laptops and data boardsprovide much of the same functionality in otherapplications.