Development of Efficient Methods Preprocessing Large Lidar Data Sets for Application to Road Design and Optimization

Technological improvements, competition in the survey services industry and the increased use of UAV’s (drone) has driven down the cost of LiDAR acquisition. As a result, LiDAR is rapidly gaining popularity in application in road planning and design. LiDAR data sets typically contain tens of millions of points. Efficiently processing this data efficiently presents challenges for software.

The proposed research seeks to investigate methods for preprocessing LiDAR data sets for road design and optimization. Included in this are algorithms and data structures for rapid conversion between TINs (Triangulated Irregular Networks), raster grids, and cross section models. The application of these methods would be tailored to civil engineering calculations such as contour generation earthwork calculations and alignment optimization.

Faculty Supervisor:

Jiannan Wang

Student:

Partner:

Softree Technical Systems

Discipline:

Computer science

Sector:

Transportation (excluding aerospace); Technology; Forestry

University:

Simon Fraser University

Program: