Initial Results From European Road Safety Inspection (eursi) Mobile Mapping Project

Mobile mapping systems are becoming a popular method for collecting high quality near 3D information of terrestrial scenes. Modern mobile mapping systems can produce millions of georeferenced points per minute. These can be used to gather quantitative information about surfaces and objects. With this geospatial data it is becoming possible to segment and extract the road surface. In this paper, we will detail a novel LIDAR based road edge extraction algorithm which is applicable to both urban and rural road sections

Challenges in Partially-Automated Roadway Feature Mapping Using Mobile Laser Scanning and Vehicle Trajectory Data

Connected vehicle and driver's assistance applications are greatly facilitated by Enhanced Digital Maps (EDMs) that represent roadway features (e.g., lane edges or centerlines, stop bars). Due to the large number of signalized intersections and miles of roadway, manual development of EDMs on a global basis is not feasible. Mobile Terrestrial Laser Scanning (MTLS) is the preferred data acquisition method to provide data for automated EDM development. Such systems provide an MTLS trajectory and a point cloud for the roadway environment. The challenge is to automatically convert these data into an EDM. This article presents a new processing and feature extraction method, experimental demonstration providing SAE-J2735 map messages for eleven example intersections, and a discussion of the results that points out remaining challenges and suggests directions for future research.Comment: 6 pages, 5 figure

Automated road extraction from terrestrial based mobile laser scanning system using the GVF snake model

Accurate extraction and reconstruction of route corridor features from geospatial data is a prerequisite to effective management of road networks for engineering, safety and environmental applications. High quality road geometry and road side features can now be extracted from dense point cloud LiDAR data, recorded by modern day Mobile Mapping Systems. This valuable route network information is gaining the attention of road safety and maintenance engineers. Road points are needed to be correctly identified, classified and extracted from LiDAR data before reconstructing intrinsic road geometry and road-side infrastructure. In this paper, we present a method to automatically extract the road from terrestrial based mobile laser scanning system using the GVF (Gradient Vector Flow) snake model. A snake is an energy minimizing spline that moves towards the desired feature or object boundary under the influence of internal forces within the curve itself and external GVF forces derived typically from 2D imaging data by minimizing certain energy such as edges or high frequency information. In our novel method, we initialise the snake contours over point cloud data based on the trajectory information produced by the MMS navigation sub-system. The internal energy term provided to the snake contour is based on adjusting the intrinsic properties of the curve, such as elasticity and bending, whilst the GVF energy and constraint energy terms are derived from the LiDAR point cloud attributes. Our method primarily differs from the traditional snake models in initialisation and in deriving the energy terms from the 3D LiDAR data

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

Indicador Integrado Multiparamétrico (IIM) para la caracterización de espacios peatonales en áreas urbanas a partir de la integración de datos LiDAR procedente de Mobile Mapping System con otras fuentes de información

Trabajo de Fin de Máster del Máster en Geotecnologías cartográficas en ingeniería y arquitectura, curso...En este estudio se propone una metodología de investigación que permite identificar los caminos escolares peatonales más adecuados en áreas urbanas. En base a ciertas variables de seguridad vial, a la distancia de desplazamiento y al estado de los viales, entre otros parámetros de interés, se generará un indicador de movilidad que permitirá visualizar de manera sencilla los trayectos domicilio-colegio más adecuados. El trabajo se divide en dos partes bien diferenciadas, la primera de ellas se focaliza en segmentar y clasificar nubes de puntos LiDAR para reconocer diferentes elementos viarios que condicionan la movilidad del peatón urbano. En la segunda parte se analiza la accesibilidad peatonal a un centro educativo aplicando técnicas de costes acumulados de desplazamiento, para identificar los caminos peatonales más apropiados en función de los elementos identificados en la fase previa

A Design Framework for Off-road Equipment Automation

Design frameworks can be helpful in the development of complex systems needed to automate machines. Designing autonomous off-road machinery requires having the means for managing the complexity of multiple interacting systems. A design framework, consisting of four technical layers, is presented. These layers are (1) machine architecture, (2) machine awareness, (3) machine control, and (4) machine behavior. Examples of technology advanced in development efforts of autonomous, robotic platforms for agricultural applications are provided. Linkages were made to applications in the construction machinery sector. Similarities between agricultural and construction automation exist in each of the technical layers

Context classification for service robots

This dissertation presents a solution for environment sensing using sensor fusion techniques and a context/environment classification of the surroundings in a service robot, so it could change his behavior according to the different rea-soning outputs. As an example, if a robot knows he is outdoors, in a field environment, there can be a sandy ground, in which it should slow down. Contrariwise in indoor environments, that situation is statistically unlikely to happen (sandy ground). This simple assumption denotes the importance of context-aware in automated guided vehicles

A systematic review of perception system and simulators for autonomous vehicles research

This paper presents a systematic review of the perception systems and simulators for autonomous vehicles (AV). This work has been divided into three parts. In the first part, perception systems are categorized as environment perception systems and positioning estimation systems. The paper presents the physical fundamentals, principle functioning, and electromagnetic spectrum used to operate the most common sensors used in perception systems (ultrasonic, RADAR, LiDAR, cameras, IMU, GNSS, RTK, etc.). Furthermore, their strengths and weaknesses are shown, and the quantification of their features using spider charts will allow proper selection of different sensors depending on 11 features. In the second part, the main elements to be taken into account in the simulation of a perception system of an AV are presented. For this purpose, the paper describes simulators for model-based development, the main game engines that can be used for simulation, simulators from the robotics field, and lastly simulators used specifically for AV. Finally, the current state of regulations that are being applied in different countries around the world on issues concerning the implementation of autonomous vehicles is presented.This work was partially supported by DGT (ref. SPIP2017-02286) and GenoVision (ref. BFU2017-88300-C2-2-R) Spanish Government projects, and the “Research Programme for Groups of Scientific Excellence in the Region of Murcia" of the Seneca Foundation (Agency for Science and Technology in the Region of Murcia – 19895/GERM/15)