Abstract
This paper describes a framework used to develop and run automotive applications both on board of vehicles and in laboratory. It includes the recording system designed and implemented in the GOLD framework. The system can record data from different sensors, such as cameras, laserscanners, radars, GPS, IMU, IO boards. The system can easily be expanded adding new device drivers. An in-RAM prerecording functionality is available to let the user record events started in the past. An index file collects essential information on each recorded event, such as timestamp, source identifier, and other sourcespecific data. Different file formats can be used to store data on disks; standard file formats are available for images and audio, small data such as CAN messages or GPS data are recorded directly into the index file. In order to have a faster lookup of a particular scene, the system is also equipped with a user interface that allows to insert tags during the recording. This system has been under development and successfully employed in the last 15 years to acquiring data for several VisLab projects. The description of two case studies is included in this paper. BRAiVE is an advanced prototype used as mobile laboratory to acquire data for different purposes. VIAC is a trip from Parma, Italy, to Shanghai, China, performed to test the robustness of VisLab driving assistance systems; the autonomous driving sessions have been recorded generating a unique database suitable to study and possibly improve the algorithm performance.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
ARTOOLKIT (2002). http://www.washington.edu/artoolkit/.
AUTOSAR GbR (2006). Layered Software Architecture Version2.0.0 http://www.autosar.org/download/AUTOSAR_LayeredSoftwareArchitecture.pdf.
Bertozzi, M. and Broggi, A. (1998). GOLD: A parallel real-time stereo vision system for generic obstacle and lane detection. IEEE Trans. Image Processing 7,1, 62–81.
Bertozzi, M., Broggi, A. and Fascioli, A. (2006). VisLab and the evolution of vision-based UGVs. IEEE Computer 39,12, 31–38.
Bombini, L., Cattani, C. P., Fedriga, R. I., Felisa, M. and Porta, P. P. (2009). Test bed for unifed perception & decision architecture. Proc. 13th Int. Forum on Advanced Microsystems for Automotive Applications, Berlin, Germany.
Braid, D., Broggi, A. and Schmiedel, G. (2006). The TerraMax autonomous vehicle. J. Field Robotics 23,9, 693–708.
Broggi, A., Bertozzi, M., Fascioli, A. and Conte, G. (1999). Automatic Vehicle Guidance: The Experience of the ARGO Vehicle. World Scientific. Singapore.
Caraffi, C., Cardarelli, E., Medici, P., Porta, P. P. and Ghisio, G. (2008). Real time road signs classification. Proc. IEEE Int. Conf. Vehicular Electronics and Safety, Columbus, Ohio, USA, 253–258.
Cerri, P., Gatti, L., Mazzei, L., Pigoni, F. and Ho, G. (2010). Day and night pedestrian detection using cascade AdaBoost system. Proc. IEEE Intelligent Transportation Systems 2010, 1843–1848.
Chen, Y.-L., Sundareswaran, V., Anderson, C., Broggi, A., Grisleri, P., Porta, P. P., Zani, P. and Beck, J. (2008). TerraMax: Team oshkosh urban robot. J. Field Robotics 25,10, 841–860.
Chen, Y.-L., Sundareswaran, V., Anderson, C., Broggi, A., Grisleri, P., Porta, P. P., Zani, P. and Beck, J. (2009). TerraMax: Team Oshkosh Urban Robot. In Buehler, M., Iagnemma, K. and Singh, S. Editors. The DARPA Urban Challenge, Autonomous Vehicles in City Traffic, Springer Tracts in Advanced Robotics. Springer-Verlag Berlin Heidelberg. 595–622.
Geiger, A., Roser, M. and Urtasun, R. (2010). Efficient large-scale stereo matching. Asian Conf. Computer Vision ACCV, Queenstown, New Zealand.
Grisleri, P. and Fedriga, I. (2010). The BRAiVE Platform. Proc. 7th IFAC Symp. Intelligent Autonomous Vehicles, Lecce, Italy.
Hoeger, R., Amditis, A., Kunert, M., Hoess, A., Flemish, F., Krueger, H. P., Bartels, A., Beutner, A. and Pagle, K. (2009). Highly automated vehicles for intelligent transport: HAVEit approach. 15th ITS World Cong., New York.
MIDAS 4.0 Video and Data Capture, http://www.xcitex.com/html/midas_description.php.
Newman, P. M. (2006). MOOS — Mission Orientated Operating Suite. Massachusetts Institute of Technology, Dept. Ocean Engineering.
Reggente, M., Mondini, A., Ferri, G., Mazzolai, B., Manzi, A., Gabelletti, M., Dario, P. and Lilienthal, A. (2010). The dustbot system: Using mobile robots to monitor pollution in pedestrian area. Chemical Engineering Transactions, 23, 273–278.
Tokuyama, H. (1997). Asia-pacific projects status and plans. Proc. Int. AHS Workshop. U. S. Department of Transportation.
Van Dijke, J. P. (2009). CityMobil, advanced transport for the urban environment. 988th Annual Meeting of Transportation Research Board, Washington DC. TRB — Transportation Research Board.
Venturi. Venturi Global Challenges. Available at http://www.venturi.fr/Venturi-global-challenges2.
Zero-Emission Race Organizing Team. Zero-Emission Race. Available at http://www.zero-race.com/.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Broggi, A., Debattisti, S., Panciroli, M. et al. High performance multi-track recording system for automotive applications. Int.J Automot. Technol. 13, 123–132 (2012). https://doi.org/10.1007/s12239-012-0011-x
Received:
Revised:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12239-012-0011-x