ADAS Device Operated on CAN Bus Using PiCAN Module for Raspberry Pi

  • Marek Drewniak
  • Krzysztof Tokarz
  • Michał Rędziński
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10449)

Abstract

In the era of the development of Cyber-Physical Systems, solutions that are based on the transparent and universal possibility to monitor and analyse signals from the measurement devices have become more popular. This is especially crucial in the case of safe and real-time systems, e.g. in the CAN networks that are used in the automotive and manufacturing. During the research, the authors focused on preparing a solution that is based on the Raspberry Pi computer. When used as an independent and non-interfering CAN node, it is capable of monitoring, analysing and controlling Advanced Driving Assistance Systems. The solution can be used as both a gateway between a hermetic, safe system and the external world and also as an onboard element that performs auxiliary data analyses that do not load the main processing unit.

Keywords

ADAS CAN bus CANoe Ethernet LIDAR Raspberry Pi 

Notes

Acknowledgements

This work was supported by the European Union from the FP7-PEOPLE-2013-IAPP AutoUniMo project “Automotive Production Engineering Unified Perspective based on Data Mining Methods and Virtual Factory Model” (grant agreement no: 612207) and research work financed from funds for science in years 2016–2017 allocated to an international co-financed project (grant agreement no: 3491/7.PR/15/2016/2) and supported by Polish Ministry of Science and Higher Education with subsidy for maintaining research potential.

References

  1. 1.
    Cyber-Physical Systems (CPS) (NSF17529) | NSF - National Science Foundation. https://www.nsf.gov/pubs/2017/nsf17529/nsf17529.htm
  2. 2.
    Wu, F.-J., Kao, Y.-F., Tseng, Y.-C.: From wireless sensor networks towards cyber physical systems. Pervasive Mobile Comput. 7, 397–413 (2011)CrossRefGoogle Scholar
  3. 3.
    Khaitan, S.K., McCalley, J.D.: Design techniques and applications of cyberphysical systems: a survey. IEEE Syst. J. 9, 350–365 (2015)CrossRefGoogle Scholar
  4. 4.
    Wang, Y., Vuran, M.C., Goddard, S.: Cyber-physical systems in industrial process control. ACM SIGBED Rev. 5, 1–2 (2008)CrossRefGoogle Scholar
  5. 5.
    Li, R., Liu, C., Luo, F.: A design for automotive CAN bus monitoring system (2008)Google Scholar
  6. 6.
    Cupek, R., Ziebinski, A., Franek, M.: FPGA based OPC UA embedded industrial data server implementation. J. Circ. Syst. Comput. 22, 1350070 (2013)CrossRefGoogle Scholar
  7. 7.
    Marwedel, P.: Embedded System Design: Embedded Systems Foundations of Cyber-Physical Systems. Springer, New York (2010). doi: 10.1007/978-94-007-0257-8CrossRefMATHGoogle Scholar
  8. 8.
    Jazdi, N.: Cyber physical systems in the context of industry 4.0. Presented at the 2014 IEEE International Conference on Automation, Quality and Testing, Robotics, May 2014Google Scholar
  9. 9.
    Zhou, F., Li, S., Hou, X.: Development method of simulation and test system for vehicle body CAN bus based on CANoe. Presented at the 7th World Congress on Intelligent Control and Automation, 2008, WCICA 2008 (2008)Google Scholar
  10. 10.
    Qianfeng, L., Bo, L., Mingzhao, C.: SJA1000-based CAN-bus intelligent control system design. Tech. Autom. Appl. 1, 61–64 (2003)Google Scholar
  11. 11.
    Ziebinski, A., Cupek, R., Erdogan, H., Waechter, S.: A survey of ADAS technologies for the future perspective of sensor fusion. In: Nguyen, N.T., Iliadis, L., Manolopoulos, Y., Trawiński, B. (eds.) Computational Collective Intelligence, vol. 9876, pp. 135–146. Springer, Cham (2016). doi: 10.1007/978-3-319-45246-3_13CrossRefGoogle Scholar
  12. 12.
    Ziębiński, A., Świerc, S.: The VHDL implementation of reconfigurable MIPS processor. In: Cyran, K.A., Kozielski, S., Peters, J.F., Stańczyk, U., Wakulicz-Deja, A. (eds.) Man-Machine Interactions, vol. 59, pp. 663–669. Springer, Berlin (2009). doi: 10.1007/978-3-642-00563-3_69CrossRefGoogle Scholar
  13. 13.
    Leen, G., Heffernan, D.: Expanding automotive electronic systems. Computer 35, 88–93 (2002)CrossRefGoogle Scholar
  14. 14.
    Bosch, R.: CAN Specification Version 2.0. Rober Bousch GmbH, Postfach (1991)Google Scholar
  15. 15.
    Herpel, T., Hielscher, K.-S., Klehmet, U., German, R.: Stochastic and deterministic performance evaluation of automotive CAN communication. Comput. Netw. 53, 1171–1185 (2009)CrossRefGoogle Scholar
  16. 16.
    CANoe – the Multibus Development and Test Tool for ECUs and Networks. Vector Informatic GmbH (2011)Google Scholar
  17. 17.
    Rasshofer, R., Gresser, K.: Automotive radar and lidar systems for next generation driver assistance functions. Adv. Radio Sci. 3, 205–209 (2005)CrossRefGoogle Scholar
  18. 18.
    Ogawa, T., Sakai, H., Suzuki, Y., Takagi, K., Morikawa, K.: Pedestrian detection and tracking using in-vehicle lidar for automotive application. Presented at the 2011 IEEE Intelligent Vehicles Symposium (IV) (2011)Google Scholar
  19. 19.
    Grzechca, D., Wrobel, T., Bielecki, P.: Indoor location and identification of objects with video surveillance system and WiFi module (2014)Google Scholar
  20. 20.
    Budzan, S., Kasprzyk, J.: Fusion of 3D laser scanner and depth images for obstacle recognition in mobile applications. Opt. Lasers Eng. 77, 230–240 (2016)CrossRefGoogle Scholar
  21. 21.
    Behere, S., Törngren, M.: A functional architecture for autonomous driving. Presented at the Proceedings of the First International Workshop on Automotive Software Architecture (2015)Google Scholar
  22. 22.
    Maka, A., Cupek, R., Rosner, J.: OPC UA object oriented model for public transportation system. Presented at the 2011 Fifth UKSim European Symposium on Computer Modeling and Simulation (EMS) (2011)Google Scholar
  23. 23.
    Cupek, R., Ziebinski, A., Fojcik, M.: An ontology model for communicating with an autonomous mobile platform. In: Kozielski, S., Mrozek, D., Kasprowski, P., Małysiak-Mrozek, B., Kostrzewa, D. (eds.) BDAS 2017. CCIS, vol. 716, pp. 480–493. Springer, Cham (2017). doi: 10.1007/978-3-319-58274-0_38CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Marek Drewniak
    • 1
  • Krzysztof Tokarz
    • 2
  • Michał Rędziński
    • 2
  1. 1.Aiut Sp. z o.o.GliwicePoland
  2. 2.Faculty of Automation Control, Electronics and Computer Science, Institute of InformaticsSilesian University of TechnologyGliwicePoland

Personalised recommendations