Oregon DOT and State Police Pave the Way for Innovative Collision Reconstruction Workflows
If there’s one thing that sets the Oregon State Police Collision Reconstruction Unit apart from most of its colleagues across the nation, it’s their working relationship with the Oregon Department of Transportation. “I’ve talked with a lot of colleagues around the country about their programs and where they’re going,” says District 1 Lead Collision Reconstructionist William Bush, of the Oregon State Police in St. Helens. “What’s really unique about Oregon is how closely and cooperatively we work with our DOT.” ODOT is ahead of the curve in the use and application of geospatial technology. Its Geometronics Unit develops and operates the Oregon Real-time GNSS Network, which enables GNSS users to achieve one centimeter accuracy in the field. The unit also owns and operates a Leica Pegasus: Two mobile-mapping solution to capture survey-grade data on its roadways. The vehicle-mounted laser scanner allows ODOT to measure and model existing roadway conditions without disrupting traffic. “Every foot of our entire highway system has been documented in three dimensions,” Bush says. “And they continue to map all the time.”
Two Departments Team Together to Accomplish a Common Goal
The highly accurate Pegasus point cloud data is utilized in a range of applications within ODOT, including project development, asset management, pavement evaluation, and slide monitoring. But when the Geometronics Unit recognized the data’s value in collision reconstruction and traffic safety, they reached out to the Oregon State Police Reconstruction Unit, which handles nearly 400 fatal collisions per year. ODOT secured a Federal Highway Administration (FHWA) grant for the proposed project and equipped the Collision Reconstruction Unit with 14 Leica TS12 robotic total measuring stations. “Inside that grant, all of which took place in 2016, they designated one nerd [from the unit] to figure out if their plan would work.” Bush says. “I just so happened to be the nerd.” Bush was paired with ODOT’s Lead Operations Surveyor, Kevin LaVerdure, PLS, to figure out how to expedite the reopening of roadways while still providing comprehensive documentation of the scene. “The original idea was that they were going to enable me to access and effectively handle the data, but I would capture the world in an arbitrary system with my robotic total station,” Bush explains. “After the fact, one of their survey crews would go out and flag [the scene], find the pins that I dropped, and get real-world coordinates to it. Then they’d merge the two systems on their software and cut the Pegasus cloud to the constraints that I had established.“ Bush would then import all the data into Map360 to create deliverables and finish the case.
A Real-World Test in Hazardous Winter Conditions
The proposed workflow was first executed in 2016 on an incident that took place in the Coast Range mountains toward the northwest corner of the state. “I knew that this would be a good use case to find out the viability of combining the two sets of data—the Pegasus cloud and our field data—to see if we could expedite opening roadways,” he says. When Bush arrived at the scene with the Leica robotic total measuring station, precipitation and overnight freezing temperatures had caused black ice on the four-lane mountain highway. Previously, a driver traveling downhill lost control of his vehicle, crossed lanes struck and spun a second vehicle before coming to rest in the travel lanes. “Everybody was none the worse for wear at this point,” Bush says, “except this occurs about a hundred feet below the crest of this rise.” However, as one of the drivers got out to examine the damage to his vehicle, a third vehicle rounded the crest and encountered black ice. “Once that driver recognized the hazard in front of him and engaged the brakes, there was nothing more that could be done,” Bush says. “Gravity and momentum took over.” The driver lost control and struck and killed the driver who was on foot. Bush’s two-part strategy was to establish points that could be shared between the site and the scene and then strictly focus on capturing scene-specific evidentiary items, including the positions of the vehicles and gouge, scrape and tire marks. With access to ODOT’s point cloud, he didn’t have to spend time documenting the four lanes of fixed features such as lane lines, shoulders and pavement edges. “I could forgo all that because I knew that those had already been documented with Leica-grade precision,” he says. In less than one hour, Bush had what he needed to restore the flow of traffic and reduce the possibility of additional incidents. “It was already hazardous enough with the weather—let alone with the additional blockage over the rise of the highway,” he says. “I shot those controls and then captured my evidence and was able to expedite opening up the roadway.” As planned, a survey crew later deployed to the scene with a Leica Viva GS14 GNSS receiver to capture real-world coordinates for the controls Bush had previously shot. “So the arbitrary data from my total station, by way of a correction to the real-world coordinates using the GS14, was reconciled with the Pegasus point cloud data,” he says.
Powerful Software Transforms Data to Deliverables
To complete the workflow, Bush needed to combine the data from the three different sensors—the shared controls collected with the GS14 GNSS rover, the scene-specific evidence documented with the Leica TS12 robotic total measuring station, and the mobile mapping scan data captured with the Leica Pegasus. “I brought all three datasets together to make one coordinate-correct final diagram in Map360,” Bush says. Map360, which is part of Leica Geosystems Incident Mapping Suite (IMS), provided the advanced software technology critical to the successful execution of the workflow. “Map360 is at its core,” Bush says. The desktop software’s multisensor support, powerful IntelliCAD engine and easy-to-use interface enabled Bush to easily import, process, analyze and visualize his data to create clear, concise 2D deliverables. “It doesn’t matter what technology I use because it all comes together in Map360,” Bush says. “It serves as the collection point for all things moving forward, and it hasn’t rejected any dataset that I’ve pushed into it to-date.” In this incident, determining the innocence or culpability of the driver who struck the victim depended on a clear understanding of not only what took place but also where it took place. “I wanted to make sure that the final deliverables that we provided to the district attorney’s office for evaluation really drew the whole picture,” he says. “It would be very easy for me to give them a simple two-dimensional, top-down view of exactly what happened. But in a case like that, if we look at the world in strictly two dimensions, we would have thought, ‘Well, there would’ve been plenty of time for that driver to stop. He must’ve been inattentive, or he failed to take an alternate route around where things were, or he must’ve been going far too fast.’” In less than one hour, Bush not only completed the standard overhead diagram, which goes into each case file, but also a series of side views that clearly conveyed the geography and geometry of the scene. “We can see how much higher things are on the left versus how much lower they are on the right to really visualized the grade of the roadway and how complicated it would be to actually stop on a hill that steep,” he says. “It also included the rise of the road so that we know that his line of sight would have been greatly limited just by the geometry of where he was.” The quick data collection and delivery of work products enabled the district attorney’s office to determine in a very short time frame—less than a month from call to closure—whether there was any culpability on the surviving operator’s part. “The three-dimensional aspect was incredibly important to helping the DA’s office in their charging decision,” he says. “The incident was deemed noncriminal.”
After interdepartmental teamwork and the decision to transfer the GS14 operation and workload from ODOT to the law enforcement side, LaVerdure and Bush presented a reliable and reasonable workflow. “From delivery of the initial devices and the inception of research to where we finally had the absolute plan on how we’re going to move forward effectively—both effectiveness on scene and effectiveness with regard to a return on investment—probably took us two years,” Bush says. Today, Bush clears scenes in minutes rather than hours. “I very seldom require any more than 60 minutes to complete my work on scene,” Bush says. “[The workflow has] proven itself over and over and over again to the point where it’s inspired our state government to continue spending funding to advance the mission further,” Bush says. “The only hurdle left to overcome is having an entire unit that’s capable of adopting the new workflow,” he says. Up until recently, Bush has been the only one equipped and trained to execute the workflow. “[As of August,] we now have four additional personnel—each one of our district leads—who are equipped to do the same thing.” he says. Powerful data combined with extraordinary vision and interdepartmental teamwork has not only enabled the Oregon State Police Collision Reconstruction Unit to begin clearing scenes at record speeds but has also driven the Oregon Department of Transportation closer to achieving its traffic safety and incident management goals. “I could never overstate what they’ve done to help us realize a whole new way of evaluating our data and its relation to all the other datasets that we wouldn’t, I don’t think, have come to as public safety,” Bush says. “We look at a scene as a snapshot of time in which we have only one opportunity to gather all this. But when we try to broaden our gaze—and with them, we’ve been able to do that—and understand how we can work towards interoperability between systems and about what the data really means, it’s there, the foundation that we’ve built, everything that I operate under.” Watch the video below to see how ODOT used mobile mapping to quickly evaluate and prepare its roadways for a 2015 speed-limit increase. You can learn more about the ODOT mobile LiDAR approach here.
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