Navigating the Complexities of Data Convergence
Anyone who regularly drives through Dallas, Texas, will generally do everything possible to avoid the IH 30/IH 35E interchange on the southwest edge of the city. Known locally as the Mixmaster, this tangled convergence of freeways has been ranked as one of the worst bottlenecks in the country and is the source of numerous traffic accidents and congestion delays. The freeway was constructed between 1958 and 1962 and has not undergone any significant improvements since then, despite a substantial increase in traffic volumes. In 1999, more than 280,000 vehicles per day traveled on IH 35E south of the Dallas North Tollway; portions of the freeway now carry more than 350,000 vehicles per day.
The Texas Department of Transportation (TxDOT) has been studying the problem for more than a decade. In 1999, the agency launched Project Pegasus, a plan to transform the IH 30 Canyon and IH 35E/IH 30 Mixmaster interchange near downtown Dallas and adjacent to the Trinity River Corridor through a comprehensive redesign. It was an ambitious project with a 25-year timeline. Some of the improvements have already been implemented. Others are still in the planning stages.
In 2011, TxDOT embarked on the Horseshoe Project, a pull-out from Project Pegasus that will be developed through an innovative design/build approach. Named for the U shape of the project area, the project involves upgrading the IH 30 bridge, part of the Mixmaster and the IH 35E bridges both northbound and southbound. Although design/build is not a new approach in construction, it is new for TxDOT. Successfully applying this streamlined, cost-effective construction method on a complex freeway interchange requires the use of cutting-edge technology and a substantial amount of data management expertise. Fortunately, TxDOT has access to both.
To manage the survey work, TxDOT’s Dallas District contracted Woolpert, a firm that has handled numerous other projects for TxDOT both under the Woolpert name and through the Dallas operations of Bohannan Huston, which Woolpert acquired in January 2011. The survey would involve collecting high-accuracy road surface data along 4-miles of interchange as well as side streets, underpasses and approximately 400 bridge columns. Adding to the project’s complexity was the region’s high traffic volumes; the interchange never sleeps. The speeds at which commuters and semi-trucks travel coupled with the freeway’s tight, elevated confines made the area an extremely dangerous place for surveyors. Ensuring worker safety would require minimizing the amount of time crews spent in the field.
Proper planning was essential. The team believed this project was the ideal application for Woolpert’s Optech Lynx Mobile Mapper M1, which collects up to 1 million points per second (1MHz) and has an integrated imaging system. However, mobile mapping at freeway speeds would not pick up the level of detail required on all the bridge columns. Additionally there were some areas the team either was not permitted to access or couldn’t access with the mobile mapping vehicle. The solution was to combine multiple technologies with existing datasets to obtain a single high-accuracy dataset with a minimum number of boots on the ground.
The team began by evaluating existing data. Previous contracts handled by Woolpert’s Dallas operations meant that a substantial amount of data was available in-house. Surveyors pulled up static laser scans of the bridges that were collected six years earlier. A 2-foot auto-correlated surface from a 17-county orthophotography project led by the Dallas team in 2007 filled in some of the open areas. Once this data was compiled, the team could easily see where mobile mapping should be used and where other methods--specifically, static scanning and traditional surveying--would be needed to complete the dataset for the current project.
The fieldwork began in September 2011. Working in the evening to avoid the highest traffic volumes, Woolpert’s mobile mapping crew made two passes in each direction on the interchange, one on the inside lane and one on the outside. A Woolpert survey truck followed about 60 yards behind the mobile mapping vehicle to prevent tailgaters. No lanes were closed for the project, and the mobile mapping vehicle traveled at posted speeds.
Several more crews began scanning the bridge columns with Leica ScanStation C10 laser scanners. To keep surveyors out of harm’s way, the static scanners were configured to work with Android-based tablets so they could be operated remotely, and all of the scanning took place at night. Three additional field crews set ground control for the mobile and static scans and filled in any remaining obscure areas.
Within two days, all the mobile LiDAR data had been collected. The bridge column scans and traditional surveys were completed in about a week. All that remained was the monumental task of combining, processing and registering the massive amounts of data.
Although commercial software packages have come a long way in the last several years, a number of gaps still exist, especially when merging datasets with different accuracies. To fill in these gaps, Woolpert relies on its Applied Research and Development (ARAD) group to write routines for macros that work within existing programs. Through these routines and the skill of Woolpert’s technicians, the team processed the different datasets from the Horseshoe, reconciled the surfaces, and converted them to MicroStation for the TxDOT deliverables--all within a four-month timeframe.
It should be noted that supplementing the LiDAR data with vehicle-captured imagery is not always an option for these types of projects. Safety; clean, unobstructed data; and the minimization of disruption to the general public can inhibit the ability to acquire data during daylight hours. For this reason, a system capable of capturing high-resolution LiDAR data without relying on imagery provides the best solution.
By using the design-build process, TxDOT expects the Horseshoe Project to get underway by spring 2013 and be completed by late 2016--at least two years sooner than what could have been achieved through traditional project development methods. The process will allow the agency to improve efficiency, reduce financial risk, optimize lifecycle costs and enhance quality. The wealth of data provided through mobile LiDAR is key to achieving these goals.
As the number of transportation projects incorporating mobile LiDAR continues to increase, so, too, will the complexity of those projects. Geospatial professionals will increasingly be expected to make use of existing data and merge different datasets to achieve the final deliverables. Although software and hardware will become easier to use, skilled professionals will be needed more than ever to make sense of the data. Preplanning and establishing the expectations at the start of a project will continue to be paramount.
Mobile LiDAR is no longer just a concept; it’s a reality. Professionals who understand how to use the technology and how to combine it with other tools and other datasets to achieve the best outcome will position themselves and their clients for success in this new paradigm.
Note: Additional details on this project will be presented at SPAR International 2012 at the Woodlands Marriott, Woodlands, Texas, April 15-18.