Suitability Testing of LiDAR Processing Software Aimed at 3-D Sight Distance Estimations

Abstract

Sight distance estimations are significant components of road safety analyses. Drivers ought
to have enough available sight distance (ASD) in order to safely perform basic driving
maneuvers. When not performed in situ, estimating ASD on existing roads normally requires
up-to-date representations of the roads’ geometric properties as well as the execution of
roadway design related tasks and geospatial analysis operations; hence, several software
products are needed to carry out these calculations throughout their entire workflow.
Nowadays, LiDAR based Mobile Mapping Systems (MMS) have been intensively put into
use to gather data needed to accomplish many transportation applications. In spite of their
many benefits, MMS produce fair volumes of point cloud data which add some complexity
to the processing stage in terms of software, computational requirements and
interoperability. This paper analyses software capabilities, in terms of suitability and
performance, of computer programs capable of LiDAR data processing tasks. The main goal
of this evaluation is to gauge their aptness to deliver data needed to perform ASD
estimations. To accomplish this, a thorough review of available literature on sight distance
analyses was conducted to get a depiction of frequently demanded software tasks and
deliverables and based on that, different volumes of point cloud were processed with a
variety of software solutions in order to test their appropriateness for the purpose from early
stages of the workflow to final calculations. This research highlights how the truly potential
of LiDAR data for performing highway safety related analyses relies heavily upon the usage
of efficient and powerful software tools.