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

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, MIMS 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, clouds with different amount of points 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. (C) 2018 The Authors. Published by Elsevier Ltd.