OREGON STATE UNIVERSITY
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Purpose
As a state agency that relies on state and federal funding, the Oregon Department of Transportation (ODOT) is occasionally asked to quantify the economic efficiency of the improvement projects that it conducts. In this case, the state legislature asked ODOT to conduct an assessment of the efficiency (both economic and operational) of several advanced technologies that ODOT had deployed over the past few years. This research focuses on evaluating the economic efficiency of one of these technologies, mobile Light Detection and Ranging (LiDAR) technology (i.e. mobile mapping), which is used to scan the over 12,880 km of roadways that ODOT manages.
Goal
The Oregon Department of Transportation (ODOT) has been using survey-grade mobile Light Detection and Ranging (LiDAR) technology to scan and create three-dimensional (3D) representations of its more than 12,880 km of roadways and gradually replacing traditional surveying when possible since 2015. The application of such technology to create a repository of images of all roadways within a state is in the early adoption phase; the direct impact of such an endeavor on the public is minimal, as it mainly affects the state agency. This research presents a method to quantify the benefits and cost savings of this endeavor using a case study approach, a present value index, and a breakeven analysis.
Methodology
ODOT’s use of mobile mapping to scan and maintain the point cloud data of over 12,880 km of roadways is novel, and the benefits of such endeavors have not been studied. Given the vast usage of the point cloud data, a boundary of what usage to include in the analysis is needed. The case study approach for the current study was conducted in two parts:
1. Identifying the Usage of Mobile Mapping within and Outside of ODOT
2. Differentiate and Quantify the Benefits and Costs
The present value index showed over a $2 saving for every $1 invested over the technology’s 5-year useful life. The breakeven analysis showed that ODOT will breakeven with its annualized cost when mobile mapping is used to survey 79.2 km of roadways and 14 projects annually, regardless of the amount of funding received.
Research Papers
1. Jahanger, Q. K., Zimmerman, G., Hadziomerspahic, A., Martin, M. A., Sillars, D. N., Ng, E. H., & Calvo-Amodio, J. (2023). Economic and Operational Impacts of Three-Dimensional Engineered Models and Automated Machine Guidance on Statewide Roadway Projects. Practice Periodical on Structural Design and Construction, 28(3), 05023003.
2. Martin, M. A., Jahanger, Q. K., Zimmerman, G., Hadziomerspahic, A., Sillars, D. N., Ng, E. H., & Calvo-Amodio, J. (2020). Case study: Economic analysis of statewide Roadway 3D Mapping using mobile LIDAR. Journal of Transportation Engineering, Part A: Systems, 146(7). https://doi.org/10.1061/jtepbs.0000377
Image Source: https://odotopenhouse.org/files/unsorted/1589490973_flying-t-with-words.jpg