February 25th, 2013
Utah DOT Leveraging LiDAR for Asset Management LeapPreserve Infrastructure, by Guest Post.
This guest post was written by Philip Ellsworth for industry magazine LiDAR News. Philip is a consultant working with UDOT’s Consultant Services Division.
In a world where LiDAR has revolutionized movie making, the Utah Department of Transportation is employing this impressive technology on a groundbreaking data collection project that will set the stage for vastly improved asset management — not just at UDOT, but across the country. After advertising a one-of-a-kind Request for Proposals (RFP) in the fall of 2011, UDOT has recently entered into a contract with Mandli Communications to gather, identify, and process a wide variety of roadway assets along its entire 6,000+ center lane miles of State Routes and Interstates. With the winning bidder (Mandli) proposing to use mobile LiDAR as its primary technology on the project (along with an array of other sensors), this UDOT contract may very well be the first of its kind in technological magnitude and scope.
In the beginning, the project was a simple effort to update an ongoing program where a contractor had been hired to gather roadway distress data for the Department. It was not long before the initially small UDOT team began to see that there was more potential to their efforts than just pavement distress data. With the leadership of Stan Burns, Director of UDOT Asset Management, they expanded their efforts to pull in other groups, asking everyone along the way, “What data can your division use to enhance your asset management decisions through a simplified collection effort?” It was soon discovered that some divisions had been duplicating efforts, potentially costing the Department precious resources; quickly a dynamic and diverse team began to form.
A goal, established to “deploy state of the art collection methods to improve and develop rigorous safety, maintenance and preservation programs” became a key motivator to UDOT embarking on this project. Beyond this goal, it is clear that UDOT believes that the ability to make efficient asset management decisions is entirely dependent upon the accuracy and credibility of the available data. Confidently knowing the full details of UDOT’s multi-billion dollar infrastructure makes a better decision-making environment for leaders. And with safety at the forefront of UDOT’s and the public’s mind, it is critical to have the most dependable data possible in order to make potentially lifesaving decisions.
Mandli has completed the first phase of the project – data gathering – and is in the process of the second phase of the project – post processing and data delivery. Mandli proposed to gather both the positive and negative directions of data on Utah roads in 2012 and then come back in 2014 and update the data sets. The UDOT Roadway Imaging and Inventory program requires the vendor to gather no less than a dozen different roadway assets including roadway distress data, surface areas, lane miles, number of signs, ROW images, vertical clearances, and more with each of those categories broken down even further into subcategories ranging from condition data to GPS data, etc.
Sensors on the UDOT Mandli flagship vehicle include a Velodyne LiDAR sensor, a laser road imaging system, a laser rut measurement system, a laser crack measurement system, a road surface profiler, a position orientation system, and more – certainly making it one of Mandli’s most advanced asset gathering vehicles in their fleet.
While UDOT acknowledges a few hiccups along the way, the Department is excited to see the final results, expecting that the scope of the data being collected in and of itself will be better than what is available today. However, expectations of better data simply due to the size of the project hasn’t stopped UDOT from getting heavily involved in the Quality Assurance (QA) aspects of the project; aggressively pursuing the accuracy side of the project as well, even requiring a weekly QC/QA update meeting between UDOT, Mandli and their QA partner Stanley Consultants. This QA effort, combined with tight data tolerances, is expected to net UDOT a data set that meets one of their top original goals to “Gather the most data pertaining to roadway condition, location and roadway assets in an economical way, while maintaining a high level of accuracy and quality.”
While this project’s level of data collection is certainly possible using more traditional, ’boots on the ground‘ methods, UDOT believes that adding the use of LiDAR is actually providing more return on their investment. In the beginning, there was some hesitancy on the part of some involved, with some even expressing doubt that an endeavor of this magnitude could ever achieve its goals, or at least not without a technology such as LiDAR to complete it. The team moved forward anyway, knowing that an effort
was needed to gather the most data they could in the most cost-effective way possible – in order to increase their ability to make asset and safety management decisions with more confidence. They were truly convinced from the beginning that the effort to cobble together a diverse team would benefit each division through an “economies of scale” approach to procurement. When it was found that LiDAR was within reach, and had even been proposed by the winning team, the excitement level for the project increased exponentially. This alone, UDOT team members believe, has kept team members vigorously involved, creating a collaborative effort that even some naysayers now applaud.
UDOT team members have learned that collaboration is important because of its affect on the DOT’s ability to integrate their asset data in a meaningful way. Having multiple sets of similar data dispersed in disparate ways leads to duplication of efforts, an increase in the loss of data integrity, and an increased risk for data to become obsolete more quickly than if the data can be integrated and accessed through a collaborative effort. This project is proving to UDOT that integration is not only necessary in today’s asset management world, but that it is indeed possible.
One tool in UDOT’s bag of integration innovation is their UPLAN planning network platform, which has found itself in a symbiotic relationship with the UDOT Roadway Imaging and Inventory program. UPLAN is distributed on an ArcGIS platform, in conjunction with UDOT’s existing Oracle-based systems. Frank Pisani, UDOT’s GIS Manager says that it was initially developed as an internal planning tool but has quickly become UDOT’s enterprise-wide attempt to disseminate its vast database of information in a user-friendly environment, accessible online at http://uplan.maps.arcgis.com. The Roadway Imaging and Inventory project will help UPLAN by supplying it with a large amount of accurate information, while UPLAN will help the Roadway Imaging and Inventory project by becoming another portal by which the data can be distributed. This creates a scenario where not only will UDOT managers and staff be anticipating the project data, but the public can now anticipate the opportunity to experience the data as well.
No fewer than eight managers from various divisions, both inside and outside UDOT (including asset management, structures, traffic & safety, GIS, technology services, motor carriers, and more) have been collaborating on this UDOT project for well over a year. And now, with the project in full swing, these eight divisions are continuing to work together, while bringing others into the project along the way.
One group of experts that has been increasingly interested in the project are UDOT preconstruction engineering teams – those who spend a majority of their time designing UDOT roads, bridges, and other infrastructure. The mobile LiDAR point cloud has proven extremely intriguing to these preconstruction groups and as a result there is a clear desire within UDOT to discover its untapped potential. Preconstruction engineering teams are even investigating the possibility of getting high enough accuracy out of the LiDAR point cloud to be used in some preliminary design scenarios. For this endeavor, they’ve turned again to the LiDAR industry of professionals and are working with consultants, including Virtual Geomatics, to develop methods to enhance the accuracy of the LiDAR point cloud through a calibration process. Early efforts appear promising, with indications of getting to an average accuracy level of +/- 3 cm when using control points contained in the point cloud data.
Another group within UDOT that has increasingly expressed interest and favor for this project are members of the Department leadership and management, not only from those close to the project but others as well. UDOT indicates that a paradigm shift may be occurring within the DOT where employees in leadership and beyond are more commonly asking spatially-oriented questions, which fosters an environment where the value of data integration and data accuracy is not just recognized but demanded.
Even with the long awaited MAP-21 legislation driving DOT’s across the nation to re-think their asset management programs, through its requirement that each state develop a risk-based asset management plan for the National Highway System, UDOT has found a way to stay at the leading edge of another transportation industry leap. And they’re clearly showing that system-wide mobile LiDAR is within reach for DOT’s across the nation.