The development of road database requires the management of continuously growing road databases. Mobile mapping systems can acquire this information, while offering an unbeatable productivity with the combination of navigation and videogrammetry tools. However, the complexity of data georeferencing and the fusion of the results with video sequences require numerous hours of repetitive labor. We propose to introduce the concept of “real time” in the field of mobile mapping. The deterministic exploitation of the data captured during a kinematic survey aims at restricting human intervention in the sophisticated georeferencing process, while authorizing the dissemination of this technique outside well-informed communities. What are the tools and algorithms robust enough to ensure the quality control of the georeferencing of the road objects? We intend to provide these concerns a pertinent answer, while demonstrating the validity of the concept via the automatic acquisition and interpretation of the road geometry.
Incursion Into Real-Time Mapping
The author’s vision of real-time mapping systems encompasses a mobile acquisition platform dedicated for a well-defined task. To sustain the high optimization requirements of such a data-critical application, the use of custom-made software based on open source libraries is a privileged approach of implementation. Road-geometry extraction from painted marks is an appropriate subject for a proof-of-concept demonstration. In this context, the Geodetic Engineering Laboratory investigates the suitability of using a vertical camera to automatically extract the road geometry (Figure 1).
Our concept of real-time mapping
To georeference road data with the shortest delay, a real-time OS powers the computer hosting the mapping software (Abbott, 2003). Despite this precaution, an inter-thread latency exceeding 5 ms may arise, which proves that the host computer should be relieved from non-time-critical tasks. We chose the methodology of distributed computing to deal with the navigation- and image-preprocessing steps for georeferencing.Top
Distributed Computing Serving Real-Time Mapping
A first subsystem applies the concept of the moving base station to determine the position and heading of the video unit (Cannon et al., 2003). The proposed implementation relies on a dual-antenna RTK GPS receiver outputting navigation data to the host computer. The primary chip of this receiver permanently broadcasts 5 Hz corrections to the secondary one. Degree-level accuracy for the heading is thus obtained. A custom Internet-based regional DGPS server contributes to the 5 Hz centimeter-level position of the primary GPS receiver antenna via a GPRS connection. This server behaves as a transparent relay that forwards RTK corrections from a cellular-enabled GPS reference to any authenticated rover in the close vicinity. This approach offers:
Independence from the cellular provider who can grant routable but highly expensive SIM cards,
Free choice of format and throughput,
Multicasting of the reference corrections to groups of rovers,
User-friendly development of add-in software for the server.
Key Terms in this Chapter
GPRS: General Packet Radio Service (GPRS) is a mobile data service available to users of wireless mobile phones. It provides moderate speed data transfer, by using unused radio channels in the cellular network.
Distributed Computing: This computing methodology is based on the fact that the process of solving a problem can be divided into smaller tasks, which may be carried out simultaneously with some coordination.
RTK GPS Receiver: This class of GPS receiver exploits relative positioning based on the interferometric principle of exploiting precise carrier-phase measurements in real-time. The attainable accuracy is at the centimeter level provided that the reference station measurements are transmitted timely and reliably to the rovers and the integer ambiguities can be resolved correctly.
CMOS: The Complementary Metal-Oxide Semiconductor is a major class of integrated circuits whose chips include a microprocessor, microcontroller, static RAM, and other digital logic circuits. CMOS devices use little power and allow a high density of on-chip logic functions.
CCD: A Charge-Coupled Device is a sensor for recording images, consisting of an integrated circuit containing an array of linked, or coupled, capacitors. Under the control of an external circuit, each capacitor can transfer its electric charge to one or another of its neighbors.
GDF: Geographic Data File stands for a European standard file format for geographic files. It also gives rules about capturing, describing and linking data. Although its primary use is for automotive navigation systems, GDF is widely used in transport and traffic applications.
FGDC: The Federal Geographic Data Committee is an interagency committee that promotes the coordinated development, use, sharing, and dissemination of geospatial data. The FGDC develops geospatial data standards for implementing the American spatial data infrastructure.
Real-Time Mapping: This expression refers to a process of map making for a level of computer responsiveness that a user senses as sufficiently immediate or that enables the computer to keep up with the georeferencing process.
Xenomai: This technology aims at helping application designers relying on traditional RTOS to move as smoothly as possible to a GNU/Linux-based execution environment, without having to rewrite their application entirely.
NTRIP: Networked Transport of RTCM via Internet Protocol is an open, non-proprietary method that encodes the RTK corrections for highly-efficient transmission over the Internet. It calls upon a substantial array of servers that allows the simultaneous connection of thousands of users.
Real-Time OS: Dedicated to real-time applications, this class of operating system uses specialized scheduling algorithms in order to provide the developer with the tools necessary to produce deterministic behavior in the final system.
Complete Chapter List
Jose E. Córcoles, Pascual González
Jose E. Córcoles, Pascual González
Michael Vassilakopoulos, Antonio Corral, Boris Rachev, Irena Valova, Mariana Stoeva
Carlos Granell, Michael Gould, Miguel Ángel Manso, Miguel Ángel Bernabé
Trias Aditya, Menno-Jan Kraak
Maikel Garma de la Osa, Yissell Arias Sánchez
Mahbubur R. Meenar, John A. Sorrentino
Eric Delmelle, Raymond Dezzani
José Poveda, Michael Gould
Alina Lazar, Bradley A. Shellito
Kevin M. Curtin
Bo Huang, Magesh Chandramouli
Iftikhar U. Sikder
Matthew Perry, Amit Sheth, Ismailcem Budak Arpinar, Farshad Hakimpour
Yuqi Bai, Liping Di, Aijun Chen, Yang Liu, Yaxing Wei
Peisheng Zhao, Liping Di, Wenli Yang, Genong Yu, Peng Yue
Carlos Granell, Michael Gould, Miguel Ángel Esbrí
Genong Yu, Liping Di, Wenli Yang, Peisheng Zhao, Peng Yue
Peng Yue, Liping Di, Wenli Yang, Genong Yu, Peisheng Zhao
Aijun Chen, Liping Di, Yuqi Bai, Yaxing Wei
Yaxing Wei, Liping Di, Guangxuan Liao, Baohua Zhao, Aijun Chen, Yuqi Bai
Alexander Klippel, Kai-Florian Richter, Stefan Hansen
Péter Hegedüs, Mihály Orosz, Gábor Hosszú, Ferenc Kovács
Kevin M. Curtin
Vladimir I. Zadorozhny
Henrik Hanke, Alf Neumann
Mahbubur R. Meenar, John A. Sorrentino, Sharmin Yesmin
Wei-Shinn Ku, Haojun Wang, Roger Zimmermann
Muhammad Usman Iqbal, Samsung Lim
Mohammed A. Quddus
Andrés Pazos, José Poveda, Michael Gould
Magesh Chandramouli, Bo Huang
Iftikhar U. Sikder
Arianna D’Ulizia, Fernando Ferri, Patrizia Grifoni
Lionel Savary, Georges Gardarin, Karine Zeitouni
Edward Mac Gillavry
Iftikhar U. Sikder, Santosh K. Misra
George Kakaletris, Dimitris Varoutas, Dimitris Katsianis, Thomas Sphicopoulos
Stelios C.A. Thomopoulos, Nikolaos Argyreas