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When water hits pavement, how effectively it moves off of and away from the surface impacts performance from both a distress and a safety perspective. A third factor also impacts pavement durability: how well the roadside keeps water moving off of and away from the road.

Pavement is maintained over the years, but roadsides often remain untouched after initial construction. In the ensuing decades, weather and traffic change roadside topography – usually not for the better. Locations that begin holding water because the ditch has flattened or eroded let water seep into the substructure and subgrade, causing visible damage and setting the stage for future pavement failure.

Identifying and monitoring these problem areas would be extremely helpful in optimizing pavement maintenance as well as designing roadsides that provide adequate drainage. The Texas DOT (TxDOT) and Texas A&M Transportation Institute (TTI) are exploring how mobile light detection and ranging (LiDAR) technology can help transportation departments cost-effectively do that.

Over the last three years to four years, the two have evaluated LiDAR’s potential as a tool for collecting surface geometric data at highway speeds. The information can be analyzed for compliance with design standards and its impact on surface drainage, and to pinpoint exact locations where maintenance on the roadside must occur due to poor drainage.

“Mobile LiDAR techniques are rapidly penetrating industry,” says TTI Associate Research Engineer Charles Gurganus. “But processing and making sense of the vast amounts of data they capture creates challenges that have made their use almost nonexistent among state DOTs.”

Gurganus and his TTI research team are attempting to push past those barriers by developing a network-level tool and surface drainage rating method DOTs can add to their asset management systems at a project level to fix specific problems.

Created through a TxDOT- and Federal Highway Administration-funded research project, the surface drainage rating includes paved surface attributes and roadside attributes measured exclusively with a mobile LiDAR device and processed in bulk with limited manual intervention.

The rating specifically applies to rural roadway sections with an unconfined edge and uses data on the following elements:

• Traveled way width

• Data collection lane cross-slope

• Hydroplaning speed

• Roadside front slope

• Roadside ditch depth

• Roadside flowline slope

The first three elements impact surface rating; the last three impact roadside rating. The network-level information enables agencies to evaluate both roadway and roadside surfaces for needs.

For example, if a data collection section falls within a geometric curve, a cross-slope rating of less than 1.0 indicates the radius of that curve is shorter than ideal given the current superelevation. As the cross-slope rating decreases, the difference in speed at which a motorist can safely navigate the curve at the posted speed limit increases. The low rating provides the local decision maker with a location to ensure mitigating measures are in place. The LiDAR data is accompanied by video, so the local manager is able to check the video and determine that the proper advisory sign(s) and/or chevrons are in place. Other investigative techniques provide an understanding of not only an element within the rating, but also if improvements can be made to that particular geometric element of the road.

TTI is also exploring the use of mobile LiDAR to map drainage basins on a pavement surface. The ability to grid mobile LiDAR data allows maintenance engineers to evaluate the existing drainage basins for a surface, whether it be a paved roadway or the roadside.

“This means we can analyze hydroplaning potential for paved roads,” says Gurganus. “Knowing how much water is flowing to a particular point and using existing hydroplaning speed calculations, we can predict the potential hydroplaning speed of the as-is condition. That’s a major advantage of mobile LiDAR: We can analyze ‘as-is’ condition rather than theoretical condition.”

The initial research project produced a rating for 73.5 miles in four TxDOT districts and performed a project-level analysis on four projects. Detailed design for proposed work on US 75 in the Paris district and RM 652 in the El Paso district was provided. Project-level analyses were also performed on IH 30 in the Atlanta district and US 77 in the Austin district. The primary output were rut maps for maintenance decision making, with a roadside grading plan for the US 77 work.

TTI is working on further implementation in two other districts.

“In the Brownwood district on SH67, we are working with personnel to produce an entire plan on ditch maintenance and drainage – all the way through the detail process,” says Gurganus. “They can fix the problems with special ditch grading and a thin overlay instead of doing full-depth reclamation. This is a huge cost savings.”

According to Gurganus, the team has much success in isolated areas designing special ditches for roadsides. “We can draw the exact data needed to get the ditch design accurate,” he says. “The design is a balance between ditch depth, flowline slope, and continuing to provide a safe roadside that can also be easily maintained.”

The TxDOT report currently waiting on publication has a more network-level slant, allowing agencies that already store information regarding pavement performance (particularly historical distress information) to use mobile LiDAR for gathering and storing other geometric attributes, such as existing pavement cross slope, roadside front slope, ditch depth, and ditch slope. These attributes give the managing agency a more robust dataset and allow engineers to analyze not only distress history, but also how the sections comply with design standards for geometric elements.

For instance, in the Atlanta district on SH43, the road is over 70 years old and needs to be rehabilitated. To develop the new shape and superelevation, the road must be raised 6 inches, and roadside front slope from the edge of the pavement to the bottom of the ditch must stay within design constraints. Using the mobile LiDAR and rating system, TTI researchers are creating an entire terrain model on the existing condition to see if it’s in compliance with design standards. This will help determine trouble spots within the future design.

An upcoming Transportation Research Board presentation covers a case study on the use of mobile LiDAR to assess hydroplaning potential and verifying its accuracy on a location with an above-average number of wet weather crashes. TTI has also explored using distance and reflectivity measurements to distinguish pavement surface changes. This helps managers better understand the extent of patching and limits of particular pavement types; using reflectivity changes across a pavement, they’d have more ability to make construction changes on surface treatments.