DOTs across the Country are mandated by the Federal Government to keep track of their roadway assets and to report against these assets to receive Federal funding for their maintenance and repair. Many DOTs conduct Roadway Characteristics Inventories (RCI) on an annual basis to update and maintain their data relative to these assets. Traditionally, this has been completed using a boots-on-the-ground approach which has been very effective at building these inventories. Many DOTs are experimenting with other technologies, namely mobile LiDAR, to conduct these inventories and to achieve many other benefits from the 3D data captured in the process.
The next graphic illustrates the typical technology solution utilized for these projects. It is composed of the Riegl VMX-450 LiDAR unit, coupled with High-definition Right-of-Way (ROW) imagery. This system can collect at rates up to 1.1 KHz (1,100,000 pts/sec) at a precision of 5mm. It collects points in a circular (360-degree) pattern along the right-of-way from 2 scanner heads facing forward and to the rear of the vehicle in a crossing pattern. The laser captures 3D points at a density of 0.3 foot at speeds up to 70mph. This scanner can be adjusted to scan at a rate that is applicable for the project specifications to limit the amount of data collected and to ensure that the resulting point cloud data is manageable.
Right-of-Way imagery is also co-collected along with this LiDAR point cloud data. These images are used to identify appropriate attribution for each feature type being extracted from the point cloud. In this example, the DOT has digitized Shoulder, Driveway Culvert Ends, and Drainage Features (Culverts, Ditches and Bottom of Swale). Additional Features such as Signs, Signals, Striping, and Markings will also be extracted and then reported to the Feds on an annual basis. The mobile LiDAR data provides a 3D surface from which to compile the data and then the ROW imagery can be used for contextual purposes to support attribution. This methodology provides an effective process that can be used to create 3D vector layers and accurate attribution used to build a robust Enterprise GIS.
Both the ROW imagery and the mobile LiDAR can be used to collect and extract the RCI data efficiently for the DOTs and provides the DOT with a robust data set that can be leveraged into the future. The ROW imagery is typically used to map features at a mapping-grade level while the LiDAR can vary a bit in accuracy. Since the relative accuracy inherent in the LiDAR is very precise, it is used to conduct dimensional measurements related to clearances, sign panel sizes, lane widths, and other measurements that require a higher precision.
The DOT utilizes the derivative products from this RCI exercise to report to the Feds in a way that is pretty basic, but effective to achieve their level of funding. For example, the data capture is very technical in nature and focuses on high precision and accuracy. Then, the RCI data is extracted from this source data, maintaining a level of precision that is dictated by the source data. Then, the DOT takes this precise data and aggregates it up to a higher level and reports the total number of Signs or the lineal feet of guardrail. Even though the reporting of this data is pretty basic in nature, the origins of the data can still have precision and accuracy and can be used for other purposes related to Engineering Design or Asset Management.
In conclusion, mobile LiDAR and Right-of-Way imagery are a safe and accurate way to collect and report against RCI variables for DOTs. This methodology promotes a safe working environment for both the DOT worker and the traveling public. It is also a cost-effective way to collect large amounts of 3D point cloud data which can be utilized for other purposes within the same Agency.