Semi-automated Generation of Road Transition Lines Using Mobile Laser Scanning Data

Recent advances in autonomous vehicles (AVs) are exponential. Prominent car manufacturers, academic institutions, and corresponding governmental departments around the world are taking active roles in the AV industry. Although the attempts to integrate AV technology into smart roads and smart cities have been in the works for more than half a century, the High Definition Road Maps (HDRMs) that assists full self-driving autonomous vehicles did not yet exist. Mobile Laser Scanning (MLS) has enormous potential in the construction of HDRMs due to its flexibility in collecting wide coverage of street scenes and 3D information on scanned targets. However, without proper and efficient execution, it is difficult to generate HDRMs from MLS point clouds. This study recognizes the research gaps and difficulties in generating transition lines (the paths that pass through a road intersection) in road intersections from MLS point clouds. The proposed method contains three modules: road surface detection, lane marking extraction, and transition line generation. Firstly, the points covering road surface are extracted using the voxel- based upward-growing and the improved region growing. Then, lane markings are extracted and identified according to the multi-thresholding and the geometric filtering. Finally, transition lines are generated through a combination of the lane node structure generation algorithm and the cubic Catmull-Rom spline algorithm. The experimental results demonstrate that transition lines can be successfully generated for both T- and cross-intersections with promising accuracy. In the validation of lane marking extraction using the manually interpreted lane marking points, the method can achieve 90.80% precision, 92.07% recall, and 91.43% F1-score, respectively. The success rate of transition line generation is 96.5%. Furthermore, the Buffer-overlay-statistics (BOS) method validates that the proposed method can generate lane centerlines and transition lines within 20 cm-level localization accuracy from MLS point clouds. In addition, a comparative study is conducted to indicate the better performance of the proposed road marking extraction method than that of three other existing methods. In conclusion, this study makes a considerable contribution to the research on generating transition lines for HDRMs, which further contributes to the research of AVs

Automatic Generation of Urban Road 3D Models for Pedestrian Studies From LiDAR Data

[Abstract] The point clouds acquired with a mobile LiDAR scanner (MLS) have high density and accuracy, which allows one to identify different elements of the road in them, as can be found in many scientific references, especially in the last decade. This study presents a methodology to characterize the urban space available for walking, by segmenting point clouds from data acquired with MLS and automatically generating impedance surfaces to be used in pedestrian accessibility studies. Common problems in the automatic segmentation of the LiDAR point cloud were corrected, achieving a very accurate segmentation of the points belonging to the ground. In addition, problems caused by occlusions caused mainly by parked vehicles and that prevent the availability of LiDAR points in spaces normally intended for pedestrian circulation, such as sidewalks, were solved in the proposed methodology. The innovation of this method lies, therefore, in the high definition of the generated 3D model of the pedestrian space to model pedestrian mobility, which allowed us to apply it in the search for shorter and safer pedestrian paths between the homes and schools of students in urban areas within the Big-Geomove project. Both the developed algorithms and the LiDAR data used are freely licensed for their use in further research.This research study was funded by the Directorate-General for Traffic of Spain, grant number SPIP2017-0234

Desenvolvemento de modelos de información de infraestructuras segundo estándares abertos e parametrización automática a partir de datos xeomáticos.

It seeks to develop procedures that allow generating information models of these structures, created from the relevant information of the point clouds obtained with these systems. For this purpose, the BIM standards for civil engineering structures, both currently available and those that will be published for the duration of the thesis, will be exploited and adopted. Information modeling techniques will be used in these standards, with the aim of obtaining a system that allows modeling the structures automatically. The models will also be made compatible with other methodologies designed for BIM, whose purpose is to take full advantage of the information available for management and maintenance tasks. Meeting these objectives, an automatic modeling system will be developed according to the BIM standards for transport infrastructures, suitable for automatic feeding from geomatic data and remote sensing, which is in turn integrable into management and maintenance systems for these types of structures of civil engineering.Esta tesis busca el desarrollo de metodologías para la exportación de la información geomática de infraestructuras de transporte, particularmente estructuras ferroviarias y carreteras, obtenida mediante tecnologías de mapeado móvil. Se busca desarrollar procedimientos que permitan generar modelos de información de estas estructuras, creados a partir de la información relevante de las nubes de puntos obtenidas con estos sistemas. Con este propósito, se explotarán y adoptarán los estándares BIM para estructuras de ingeniería civil, tanto los actualmente disponibles como aquellos que serán publicados durante la duración de la tesis. Se utilizarán técnicas de modelado de información en estos estándares, con objetivo de obtener un sistema que permita realizar un modelado de las estructuras de manera automática. Se llevará a cabo también la compatibilización los modelos con otras metodologías diseñadas para BIM, cuyo propósito es el aprovechamiento total de la información disponible para tareas de gestión y mantenimiento. Cumpliendo estos objetivos se desarrollará un sistema automático de modelado según los estándares BIM para infraestructuras de transporte, apto para su alimentación automática a partir de datos geomáticos y teledetección, el cual es a su vez integrable en sistemas de gestión y mantenimiento para este tipo de estructuras de ingeniería civil.Esta tese busca o desenvolvemento de metodoloxías para a exportación da información xeomática de infraestruturas de transporte, particularmente estruturas ferroviarias e estradas, obtida mediante tecnoloxías de mapeado móbil. A tese busca o desenvolvemento de procedementos que permitan xerar modelos de información destas estruturas, creados a partir da información relevante das nubes de puntos obtidas con estes sistemas. Con este propósito, se explotarán e adoptarán os estándares BIM para estruturas de enxeñería civil, tanto os actualmente dispoñibles como aqueles que serán publicados durante a duración da tese. Utilizaranse técnicas de modelado de información nestes estándares, con obxectivo de obter un sistema que permita realizar un modelado das estruturas de maneira automática. Levarase a cabo tamén a compatibilización dos modelos con outras metodoloxías diseñadas para BIM, cuxo propósito é o aproveitamento total da información dispoñible para tarefas de xestión e mantemento. Cumplindo estes obxectivos se desenvolverá un sistema automático de modelado segundo os estándares BIM para infraestruturas de transporte, apto para a súa alimentación automática a partir de datos xeomáticos e teledetección, o cal é a súa vez integrable en sistemas de xestión e mantemento para este tipo de estruturas de enxeñería civil

Automated 3D model generation for urban environments [online]

Abstract In this thesis, we present a fast approach to automated generation of textured 3D city models with both high details at ground level and complete coverage for birds-eye view. A ground-based facade model is acquired by driving a vehicle equipped with two 2D laser scanners and a digital camera under normal traffic conditions on public roads. One scanner is mounted horizontally and is used to determine the approximate component of relative motion along the movement of the acquisition vehicle via scan matching; the obtained relative motion estimates are concatenated to form an initial path. Assuming that features such as buildings are visible from both ground-based and airborne view, this initial path is globally corrected by Monte-Carlo Localization techniques using an aerial photograph or a Digital Surface Model as a global map. The second scanner is mounted vertically and is used to capture the 3D shape of the building facades. Applying a series of automated processing steps, a texture-mapped 3D facade model is reconstructed from the vertical laser scans and the camera images. In order to obtain an airborne model containing the roof and terrain shape complementary to the facade model, a Digital Surface Model is created from airborne laser scans, then triangulated, and finally texturemapped with aerial imagery. Finally, the facade model and the airborne model are fused to one single model usable for both walk- and fly-thrus. The developed algorithms are evaluated on a large data set acquired in downtown Berkeley, and the results are shown and discussed

Trajectory generation for lane-change maneuver of autonomous vehicles

Lane-change maneuver is one of the most thoroughly investigated automatic driving operations that can be used by an autonomous self-driving vehicle as a primitive for performing more complex operations like merging, entering/exiting highways or overtaking another vehicle. This thesis focuses on two coherent problems that are associated with the trajectory generation for lane-change maneuvers of autonomous vehicles in a highway scenario: (i) an effective velocity estimation of neighboring vehicles under different road scenarios involving linear and curvilinear motion of the vehicles, and (ii) trajectory generation based on the estimated velocities of neighboring vehicles for safe operation of self-driving cars during lane-change maneuvers. ^ We first propose a two-stage, interactive-multiple-model-based estimator to perform multi-target tracking of neighboring vehicles in a lane-changing scenario. The first stage deals with an adaptive window based turn-rate estimation for tracking maneuvering target vehicles using Kalman filter. In the second stage, variable-structure models with updated estimated turn-rate are utilized to perform data association followed by velocity estimation. Based on the estimated velocities of neighboring vehicles, piecewise Bezier-curve-based methods that minimize the safety/collision risk involved and maximize the comfort ride have been developed for the generation of desired trajectory for lane-change maneuvers. The proposed velocity-estimation and trajectory-generation algorithms have been validated experimentally using Pioneer3- DX mobile robots in a simulated lane-change environment as well as validated by computer simulations

Road safety evaluation through automatic extraction of road horizontal alignments from Mobile LiDAR System and inductive reasoning based on a decision tree

13 p.Safe roads are a necessity for any society because of the high social costs of traffic accidents. This challenge is addressed by a novel methodology that allows us to evaluate road safety from Mobile LiDAR System data, taking advantage of the road alignment due to its influence on the accident rate. Automation is obtained through an inductive reasoning process based on a decision tree that provides a potential risk assessment. To achieve this, a 3D point cloud is classified by an iterative and incremental algorithm based on a 2.5D and 3D Delaunay triangulation, which apply different algorithms sequentially. Next, an automatic extraction process of road horizontal alignment parameters is developed to obtain geometric consistency indexes, based on a joint triple stability criterion. Likewise, this work aims to provide a powerful and effective preventive and/or predictive tool for road safety inspections. The proposed methodology was implemented on three stretches of Spanish roads, each with different traffic conditions that represent the most common road types. The developed methodology was successfully validated through as-built road projects, which were considered as “ground truth.”S

Visual computing techniques for automated LIDAR annotation with application to intelligent transport systems

106 p.The concept of Intelligent Transport Systems (ITS) refers to the application of communication and information technologies to transport with the aim of making it more efficient, sustainable, and safer. Computer vision is increasingly being used for ITS applications, such as infrastructure management or advanced driver-assistance systems. The latest progress in computer vision, thanks to the Deep Learning techniques, and the race for autonomous vehicle, have created a growing requirement for annotated data in the automotive industry. The data to be annotated is composed by images captured by the cameras of the vehicles and LIDAR data in the form of point clouds. LIDAR sensors are used for tasks such as object detection and localization. The capacity of LIDAR sensors to identify objects at long distances and to provide estimations of their distance make them very appealing sensors for autonomous driving.This thesis presents a method to automate the annotation of lane markings with LIDAR data. The state of the art of lane markings detection based on LIDAR data is reviewed and a novel method is presented. The precision of the method is evaluated against manually annotated data. Its usefulness is also evaluated, measuring the reduction of the required time to annotate new data thanks to the automatically generated pre-annotations. Finally, the conclusions of this thesis and possible future research lines are presented

Small business innovation research. Abstracts of completed 1987 phase 1 projects

Non-proprietary summaries of Phase 1 Small Business Innovation Research (SBIR) projects supported by NASA in the 1987 program year are given. Work in the areas of aeronautical propulsion, aerodynamics, acoustics, aircraft systems, materials and structures, teleoperators and robotics, computer sciences, information systems, spacecraft systems, spacecraft power supplies, spacecraft propulsion, bioastronautics, satellite communication, and space processing are covered