Skip to main content
SpringerLink
Log in

Simulation methods and tools for collaborative embedded systems: with focus on the automotive smart ecosystems

  • Special Issue Paper
  • Published:
SICS Software-Intensive Cyber-Physical Systems

Abstract

Embedded Systems are increasingly equipped with open interfaces that enable communication and collaboration with other embedded systems. Collaborative embedded systems (CES) can be seen as an emerging new class of systems which, although individually designed and developed, can form collaborations at runtime. When embedded systems collaborate with each other, functions developed independently need to be integrated for performing evaluation of the resulting system in order to discover unwanted side-effects. Traditionally, early-stage validation and verification (V&V) of systems composed of collaborative subsystems is performed by function integration at design time. Simulation is used at this stage to verify system’s behaviour in a predefined set of test scenarios. In this paper we provide a survey of simulation methods and tools for the V&V of CES. In the context of one use case from the automotive domain (vehicle platooning) we present solutions (methods and tools) and challenges brought by evaluating vehicle collaboration using simulation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

  1. Collaborative Embedded Systems (CrESt) project: https://crest.in.tum.de/

  2. Ipg automotive gmbh, karlsruhe, germany. carmaker 3.5 (2011). www.ipg.de

  3. ISO 26262 -international standard for road vehicles-functional safety (2011). http://www.iso.org/

  4. Matlab7simulink. https://www.mathworks.com/

  5. Open Dynamics Engine. http://www.ode.org/

  6. Open SystemC - tutorial. http://www.asic-world.com/systemc/tutorial.html

  7. QEMU - homepage : https://www.qemu.org/

  8. Synopsis - Virtualizer. https://www.synopsys.com/verification/virtual-prototyping/virtualizer.html

  9. Virtual System Platform. https://www.cadence.com/content/cadence-www/global/en_US/home/tools/system-design-and-verification/software-driven-verification/virtual-system-platform.html

  10. Vista Virtual Prototyping. https://www.mentor.com/esl/vista/virtual-prototyping

  11. Bach J, Bauer K L, Holzäpfel M, Hillenbrand M, Sax E (2015) Control based driving assistant functions’ test using recorded in field data. In: 7. Tagung Fahrerassistenzsysteme

  12. Besanger Y, Tran QT, Boudinnet C, Nguyen TL, Brandl R, Strasser TI et al. (2017) Using power-hardware-in-the-loop experiments together with co-simulation for the holistic validation of cyber-physical energy systems. In: Innovative smart grid technologies conference Europe, 2017 IEEE PES, pp 1–6

  13. Bokc T, Maurer M, Farber G (2007) Validation of the vehicle in the loop (vil); a milestone for the simulation of driver assistance systems. In: 2007 IEEE intelligent vehicles symposium, pp 612–617. https://doi.org/10.1109/IVS.2007.4290183

  14. Cioroaica E, Jahić J, Kuhn T, Peper C, Uecker D, Dropmann C, Munk P, Rakshith A, Thaden E (2017) Accelerated simulated fault injection testing. In: IEEE international symposium on software reliability engineering workshops (ISSREW), pp 228–233

  15. Cioroaica E, Kuhn T, Bauer T (2018) Prototyping automotive smart ecosystems. In: 2018 48th annual IEEE/IFIP international conference on dependable systems and networks workshops (DSN-W). IEEE

  16. Cioroaica E, Kuhn T, Buhnova B, (Do not) trust in ecosystems. In: Proceedings of the 41th international conference on software engineering (ICSE-NIER 2019). ACM (2019). Pre-print available at https://www.researchgate.net/publication/331498836_Do_Not_Trust_in_Ecosystems

  17. Cioroaica E, Kuhn T (2016) Simulator coupling for network fault injection testing. In: Proceedings of EUROSIM conference on modeling and simulation 2016. Linköping electronic conference proceedings . https://doi.org/10.1109/EUROSIM.2016.160

  18. Duracz A, Eriksson H, Bartha F A, Xu F, Zeng Y, Taha W (2015) Using rigorous simulation to support ISO 26262 hazard analysis and risk assessment. In: High Performance computing and communications (HPCC), 2015 IEEE 7th International Symposium on Cyberspace Safety and Security (CSS), pp 1093–1096. IEEE

  19. Fu D, Becker M, Szczerbicka H (2015) On the potential of optimized data exchange in distributed embedded simulation. In: 2015 IEEE/ACM 19th international symposium on distributed simulation and real time applications (DS-RT), pp 179–186

  20. Fu D, Becker M, Szczerbicka H (2015) Universal simulation engine (use): a model-independent library for discrete event simulation. In: SpringSim

  21. Hermans T, Ramaekers P, Denil J, De Meulenaere P, Anthonis J (2011) Incorporation of autosar in an embedded systems development process: a case study. In: 37th EUROMICRO conference on software engineering and advanced applications (SEAA), pp 247–250

  22. Ilieskou N, Blom M, Somers L, Reniers M, Basten T (2015) Multi-domain virtual prototyping in a systemc sil framework: a heating system case study. In: 2015 International conference on embedded computer systems: architectures, modeling, and simulation (SAMOS), pp 286–294

  23. Krajzewicz D, Erdmann J, Behrisch M, Bieker L (2012) Recent development and applications of sumo-simulation of urban mobility. Int J Adv Syst Meas 5(3&4):128–138

    Google Scholar 

  24. Kuhn T, Forster T, Braun T, Gotzhein R (2013) Feral–framework for simulator coupling on requirements and architecture level. In: Eleventh IEEE/ACM international conference on formal methods and models for codesign (MEMOCODE), pp 11–22

  25. Lopez P A, Behrisch M, Bieker-Walz L, Erdmann J, Flötteröd Y, Hilbrich R, Lücken L, Rummel J, Wagner P, WieBner E (2018) Microscopic traffic simulation using SUMO. In: 2018 21st international conference on intelligent transportation systems (ITSC), pp 2575–2582 . https://doi.org/10.1109/ITSC.2018.8569938

  26. Manikas K (2016) Revisiting software ecosystems research: a longitudinal literature study. J Syst Softw 117:84–103

    Article  Google Scholar 

  27. Mueller W, Becker M, Elfeky A, DiPasquale A (2012) Virtual prototyping of cyber-physical systems. In: 17th Asia and South Pacific design automation conference (ASP-DAC), pp 219–226

  28. Nentwig M, Stamminger M (2010) A method for the reproduction of vehicle test drives for the simulation based evaluation of image processing algorithms. In: 13th International IEEE conference on intelligent transportation systems, pp 1307–1312

  29. Nentwig M, Stamminger M (2011) Hardware-in-the-loop testing of computer vision based driver assistance systems. In: 2011 IEEE intelligent vehicles symposium (IV), pp 339–344

  30. von Neumann-Cosel K, Dupuis M, Weiss C (2009) Virtual test drive-provision of a consistent tool-set for [d, h, s, v]-in-the-loop. In: Proceedings of the Driving Simulation Conference Monaco

  31. Popovski P (2014) Ultra-reliable communication in 5g wireless systems. In: 1st international conference on 5G for ubiquitous connectivity, pp 146–151. https://doi.org/10.4108/icst.5gu.2014.258154

  32. Popp K M (2010) Goals of software vendors for partner ecosystems–a practitioner s view. In: International conference of software business. Springer, Berlin, pp 181–186

  33. Pudlitz F, Vogelsang A (2019) A lightweight multilevel markup language for connecting software requirements and simulations. In: 25th International working conference on requirements engineering: foundation for software quality (REFSQ)

  34. Raith A, Sattler K, Ertlmeier R, Brandmeier T (2011) Networking and integration of active and passive safety systems. In: 2011 Proceedings of the ninth international workshop on intelligent solutions in embedded systems, pp 75–80

  35. Riley GF, Henderson TR (2010) The ns-3 network simulator. In: Wehrle K, Güneş M, Gross J (eds) Modeling and tools for network simulation. Springer, Berlin, pp 15–34

    Chapter  Google Scholar 

  36. Roesener C, Fahrenkrog F, Uhlig A, Eckstein L (2016) A scenario-based assessment approach for automated driving by using time series classification of human-driving behaviour. In: 2016 IEEE 19th international conference on intelligent transportation systems (ITSC), pp 1360–1365

  37. Rosen R, Von Wichert G, Lo G, Bettenhausen KD (2015) About the importance of autonomy and digital twins for the future of manufacturing. IFAC-PapersOnLine 48(3):567–572

    Article  Google Scholar 

  38. Schlingloff BH (2016) Cyber-physical systems engineering. In: Bowen JP, Liu Z, Zhang Z (eds) Engineering trustworthy software systems. Springer, Berlin, pp 256–289

    Chapter  Google Scholar 

  39. Schünemann B (2011) V2x simulation runtime infrastructure vsimrti: an assessment tool to design smart traffic management systems. Comput Netw 55(14):3189–3198

    Article  Google Scholar 

  40. da Silva Amorim S, Neto F S S, McGregor J D, de Almeida E S, von Flach G Chavez C (2017) How has the health of software ecosystems been evaluated?: A systematic review. In: Proceedings of the 31st Brazilian symposium on software engineering, pp 14–23

  41. Sommer C, German R, Dressler F (2011) Bidirectionally Coupled Network and Road Traffic Simulation for Improved IVC Analysis. IEEE Trans Mob Comput 10(1):3–15. https://doi.org/10.1109/TMC.2010.133

    Article  Google Scholar 

  42. Varga A, Hornig R (2008) An overview of the OMNeT++ simulation environment. p. 60. ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering) . http://dl.acm.org/citation.cfm?id=1416222.1416290

  43. Wachenfeld W, Winner H (2016) The release of autonomous vehicles. Springer, Berlin, pp 425–449

    Google Scholar 

  44. Wang Y, Zhou X, Liang D (2012) Study on integrated modeling methods toward co-simulation of cyber-physical system. In: 2012 IEEE 14th international conference on high performance computing and communication 2012 IEEE 9th international conference on embedded software and systems, pp 1736–1740 . https://doi.org/10.1109/HPCC.2012.261

  45. Zofka M R, Kohlhaas R, Schamm T, Zollner J M (2014) Semivirtual simulations for the evaluation of vision-based adas. In: Intelligent vehicles symposium proceedings, pp 121–126

Download references

Acknowledgements

This work has been funded by the German Ministry of Education and Research (BMBF) through the BMBF project CrESt (Collaborative Embedded Systems).

Author information

Authors and Affiliations

  1. Fraunhofer Platz 1, 67663, Kaiserslautern, Germany

    Emilia Cioroaica & Thomas Kuhn

  2. Ernst-Reuter-Platz 7, 10587, Berlin, Germany

    Florian Pudlitz

  3. Boltzmannstrasse 3, 85748, Garching bei München, Germany

    Ilias Gerostathopoulos

Authors
  1. Emilia Cioroaica
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Florian Pudlitz
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ilias Gerostathopoulos
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Thomas Kuhn
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Emilia Cioroaica.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cioroaica, E., Pudlitz, F., Gerostathopoulos, I. et al. Simulation methods and tools for collaborative embedded systems: with focus on the automotive smart ecosystems. SICS Softw.-Inensiv. Cyber-Phys. Syst. 34, 213–223 (2019). https://doi.org/10.1007/s00450-019-00426-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00450-019-00426-5

Keywords

Search

Navigation