Since passage of the Moving Ahead for Progress in the 21st Century (MAP-21), transportation agencies have become increasingly reliant on data for planning and programming, asset management, and performance tracking. An efficient asset inventory database with accurate data is critical for states to comply with MAP-21 (and now FAST Act) requirements.
The Kentucky Transportation Cabinet’s (KYTC) Division of Planning maintains the Highway Information System (HIS), which is a primary source of this information for transportation professionals at the Cabinet (KYTC). Because highway system is continually changing, it is a challenging task to keep the information in the HIS up to date. Further, the level of accuracy and precision of the initial data collection activities vary among the agencies tasked with data collection.
This study developed a quality check program of the HIS to ensure key items in the database are accurate. KYTC identified a list of priority data items to include in this assessment. They were: (1) Number and width of through lanes; (2) Type and width of medians; (3) Presence and width of auxiliary lanes (e.g., truck climbing, turning, two-way left turn); and (4) Type and width of shoulders.
For this study, Kentucky Transportation Center (KTC) researchers developed a process to systematically sample highway segments and generate data collection points. These points were located on Google Earth and Google Street View so that those programs ’ native tools could be used to measure the relevant attributes.Researchers then compared the HI S records and observed data to identify possible errors. This study’s analysis verified that the vast majority of the sampled segments have accurate entries in the HIS database. For Through Lane and Shoulder asset types, inconsistencies between the observed and archived data were mostly on roads in small urban areas and rural minor arterials or lower functional groups.Since they account for about 86% of the total mileages in Kentucky, additional sampling of roads in these groups is recommended. Median width was identified as another item that warrants further review. The Auxiliary Lane asset type appears to have the least inconsistency between the observed and archived data, according to random samples.
Digital Object Identifier
Chen, Mei; Kazi, Obaidur Rahman; and Fields, Tony, "Develop a Highway Inventory Data Quality Control Scheme (PL-26)" (2017). Kentucky Transportation Center Research Report. 1561.