Abstract
Effective navigation and distribution of traffic flow in large cities has become a hot topic in recent years. The authors have developed an advanced server side routing system which, together with client side navigation systems, is able not only to navigate cars according to their routing requests, but also to distribute traffic flow within a city. The main goal of the paper is to propose a distributed environment used for an advanced server side navigation system with a focus on effective usage of computational resources for different tasks that need to be solved within the system. A combination of cloud and high performance computing resources in one environment is proposed. The authors also developed a simulator for testing these distributed computational resources. The system and the simulator were tested on the infrastructure at IT4Innovations National Supercomputing Center in the Czech Republic.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Behrisch, M., Bieker, L., Erdmann, J., Krajzewicz, D.: Sumo – simulation of urban mobility an overview. In: SIMUL 2011, The Third International Conference on Advances in System Simulation, pp. 63–68 (2011)
Cowley, R., Joss, S., Dayot, Y.: The smart city and its publics: insights from across six UK cities. Urban Res. Pract. 11(1), 53–77 (2018). https://doi.org/10.1080/17535069.2017.1293150
Fellendorf, M., Vortisch, P.: Microscopic traffic flow simulator VISSIM. In: Fundamentals of Traffic Simulation. International Series in Operations Research & Management Science, vol. 145 (2010)
Golasowski, M., Bispo, J., Martinovič, J., Slaninová, K., Cardoso, J.M.: Expressing and applying C++ code transformations for the HDF5 API through a DSL. In: IFIP International Conference on Computer Information Systems and Industrial Management, pp. 303–314. Springer, Cham (2017)
Golasowski, M., Tomis, R., Martinovič, J., Slaninová, K., Rapant, L.: Performance evaluation of probabilistic time-dependent travel time computation. In: IFIP International Conference on Computer Information Systems and Industrial Management, pp. 377–388. Springer, Cham (2016)
Horni, A., Nagel, K., Axhausen, K.W.: Introducing MATSim. In: The Multi-Agent Transport Simulation MATSim. Ubiquity Press (2016)
Jeong, J., Jeong, H., Lee, E., Oh, T., Du, D.H.C.: SAINT: self-adaptive interactive navigation tool for cloud-based vehicular traffic optimization. IEEE Trans. Veh. Technol. 65(6), 4053–4067 (2016). https://doi.org/10.1109/TVT.2015.2476958
Ma, J., Smith, B.L., Zhou, X.: Personalized real-time traffic information provision: agent-based optimization model and solution framework. Transp. Res. Part C: Emerg. Technol. 64, 164–182 (2016). https://doi.org/10.1016/j.trc.2015.03.004. http://www.sciencedirect.com/science/article/pii/S0968090X15000832
Ptošek, V., Ševčík, J., Martinovič, J., Slaninová, K., Rapant, L., Cmar, R.: Real time traffic simulator for self-adaptive navigation system validation (2018)
Seo, T., Bayen, A.M., Kusakabe, T., Asakura, Y.: Traffic state estimation on highway: a comprehensive survey. Annu. Rev. Control 43, 128–151 (2017). https://doi.org/10.1016/j.arcontrol.2017.03.005. http://www.sciencedirect.com/science/article/pii/S1367578817300226
Silvano, C., Agosta, G., Bartolini, A., Beccari, A.R., Benini, L., Besnard, L., Bispo, J., Cmar, R., Cardoso, J.M., Cavazzoni, C., et al.: The ANTAREX domain specific language for high performance computing. arXiv preprint arXiv:1901.06175 (2019)
Smith, L., Beckman, R., Anson, D., Nagel, K., Williams, M.: TRANSIMS: transportation analysis and simulation system. In: National Transportation Planning Methods Applications Conference (1995)
Tomis, R., Rapant, L., Martinovič, J., Slaninová, K., Vondrák, I.: Probabilistic time-dependent travel time computation using monte carlo simulation. In: Kozubek, T., Blaheta, R., Šístek, J., Rozložník, M., Čermák, M. (eds.) High Performance Computing in Science and Engineering, pp. 161–170. Springer, Cham (2016)
Vitali, E., Gadioli, D., Palermo, G., Golasowski, M., Bispo, J., Pinto, P., Martinovic, J., Slaninova, K., Cardoso, J.M., Silvano, C.: An efficient Monte Carlo-based probabilistic time-dependent routing calculation targeting a server-side car navigation system. arXiv preprint arXiv:1901.06210 (2019)
Acknowledgements
This work was supported by The Ministry of Education, Youth and Sports from the National Programme of Sustainability (NPS II) project ‘IT4Innovations excellence in science - LQ1602’, by the IT4Innovations infrastructure which is supported from the Large Infrastructures for Research, Experimental Development and Innovations project ‘IT4Innovations National Supercomputing Center – LM2015070’, and partially by the SGC grant No. SP2019/108 ‘Extension of HPC platforms for executing scientific pipelines’, VŠB - Technical University of Ostrava, Czech Republic.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Martinovič, J. et al. (2020). A Distributed Environment for Traffic Navigation Systems. In: Barolli, L., Hussain, F., Ikeda, M. (eds) Complex, Intelligent, and Software Intensive Systems. CISIS 2019. Advances in Intelligent Systems and Computing, vol 993. Springer, Cham. https://doi.org/10.1007/978-3-030-22354-0_27
Download citation
DOI: https://doi.org/10.1007/978-3-030-22354-0_27
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-22353-3
Online ISBN: 978-3-030-22354-0
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)