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A discrete-event and hybrid traffic simulation model based on SimEvents for intelligent transportation system analysis in Mcity

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Abstract

An intelligent transportation systems (ITS) is a typical cyber-physical system (CPS) in which physical components, for example, Connected Automated Vehicles (CAVs), are monitored and controlled through a network of cyber and physical components. Such systems, therefore, contain event-driven dynamics along with time-driven dynamics. The proposed discrete-event and hybrid simulation framework based on SimEvents facilitates testing for safety and performance evaluation of an ITS and has been used to build a traffic simulation model of the Mcity test facility. It is specifically designed for testing CAVs and contains various road/lane configurations and a complete instrumentation system. This enables users to study traffic at the microscopic level, including the effectiveness of new control algorithms for CAVs under different traffic scenarios, the event-driven aspects of transportation systems, and the effects of communication delays. The framework spans multiple toolboxes including MATLAB\(^{{\circledR }}\), Simulink\(^{{\circledR }}\), and SimEvents\(^{{\circledR }}\).

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References

  • Benekohal R, Treiterer J (1988) Carsim: Car-following model for simulation of traffic in normal and stop-and-go conditions. Transp Res Rec 1194:99–111

    Google Scholar 

  • Bettisworth C, Burt M, Chachich A, Harrington R, Hassol J, Kim A, Lamoureux K, LaFrance-Linden D, Maloney C, Perlman D et al (2015) Status of the dedicated short-range communications technology and applications: report to congress. Tech. rep., United States. Department of Transportation. Intelligent Transportation

  • Cameron GD, Duncan GI (1996) Paramics-parallel microscopic simulation of road traffic. J Supercomput 10(1):25–53

    Article  Google Scholar 

  • Cassandras CG, Lafortune S (2009) Introduction to Discrete Event Systems. Springer Science & Business Media

  • Clune MI, Mosterman PJ, Cassandras CG (2006) Discrete event and hybrid system simulation with SimEvents. In: Proceedings of the 8th International Workshop on Discrete Event Systems, pp 386–387

  • Fellendorf M (1994) Vissim: A microscopic simulation tool to evaluate actuated signal control including bus priority. In: 64th Institute of Transportation Engineers Annual Meeting, Springer, pp 1–9

  • Ferrara A, Sacone S, Siri S (2018) Freeway Traffic Modelling and Control. Springer, Berlin

    Book  Google Scholar 

  • Hellström E, ÅSlund J, Nielsen L (2010) Design of an efficient algorithm for fuel-optimal look-ahead control. Control Eng Pract 18(11):1318–1327

    Article  Google Scholar 

  • Hult R, Zanon M, Gras S, Falcone P (2018) An miqp-based heuristic for optimal coordination of vehicles at intersections. In: 2018 IEEE Conference on Decision and Control (CDC), IEEE, pp 2783–2790

  • Kato S, Tsugawa S, Tokuda K, Matsui T, Fujii H (2002) Vehicle control algorithms for cooperative driving with automated vehicles and intervehicle communications. IEEE Trans Intell Transp Syst 3(3):155–161

    Article  Google Scholar 

  • Krajzewicz D, Hertkorn G, Rössel C, Wagner P (2002) Sumo (simulation of urban mobility)-an open-source traffic simulation. In: Proceedings of the 4th Middle East Symposium on Simulation and Modelling (MESM20002), pp 183–187

  • Lee J, Park B (2012) Development and evaluation of a cooperative vehicle intersection control algorithm under the connected vehicles environment. IEEE Trans Intell Transp Syst 13(1):81–90

    Article  Google Scholar 

  • Li SE, Peng H, Li K, Wang J (2012) Minimum fuel control strategy in automated car-following scenarios. IEEE Trans Veh Technol 61(3):998–1007

    Article  Google Scholar 

  • Li W, Mani R, Mosterman PJ (2016) Extensible discrete-event simulation framework in simEvents. In: Proceedings of the 2016 Winter Simulation Conference, IEEE Press, pp 943–954

  • Liu A, Salvucci D (2001) Modeling and prediction of human driver behavior. In: Intl Conference on HCI

  • Macadam CC (2003) Understanding and modeling the human driver. Veh Syst Dyn 40(1-3):101–134

    Article  Google Scholar 

  • Malikopoulos AA, Cassandras CG, Zhang Y (2018) A decentralized energy-optimal control framework for connected automated vehicles at signal-free intersections. Automatica 93:244–256

    Article  MathSciNet  Google Scholar 

  • MathWorks\({~}^{\circledR }\) (2016a) MATLAB\({~}^{\circledR }\) Object-Oriented Programming (R2016b) mathworks\({~}^{\circledR }\), Natick, MA

  • MathWorks\({~}^{{\circledR }}\) (2016b) MATLAB\(^{{\circledR }}\), Primer (R2016b) MathWorks\({~}^{{\circledR }}\), Natick, MA

  • MathWorks\({~}^{{\circledR }}\) (2016c) Simevents\({~}^{{\circledR }}\), User’s Guide (R2016b) MathWorks\({~}^{{\circledR }}\), Natick, MA

  • MathWorks\({~}^{{\circledR }}\) (2016d) Simulink\({~}^{{\circledR }}\), User’s Guide (R2016b) MathWorks\({~}^{{\circledR }}\), Natick, MA

  • Meng X, Cassandras CG (2018) Optimal control of autonomous vehicles for non-stop signalized intersection crossing. In: 57th IEEE Conference on Decision and Control (to appear)

  • Miculescu D, Karaman S (2014) Polling-systems-based control of high-performance provably-safe autonomous intersections. In: 53rd IEEE Conference on Decision and Control, IEEE, pp 1417–1423

  • Shladover SE, Desoer CA, Hedrick JK, Tomizuka M, Walrand J, Zhang WB, McMahon DH, Peng H, Sheikholeslam S, McKeown N (1991) Automated vehicle control developments in the path program. IEEE Trans Veh Technol 40(1):114–130

    Article  Google Scholar 

  • Tian R, Li S, Li N, Kolmanovsky I, Girard A, Yildiz Y (2018) Adaptive game-theoretic decision making for autonomous vehicle control at roundabouts. In: 2018 IEEE Conference on Decision and Control (CDC), IEEE, pp 321–326

  • Treiber M, Hennecke A, Helbing D (2000) Congested traffic states in empirical observations and microscopic simulations. Phys Rev E 62(2):1805

    Article  Google Scholar 

  • Versteegt E, Klunder G, Bv Arem (2009) Modelling cooperative roadside and in-vehicle intelligent transport systems using the its modeller. In: 12Th world Congress on Intelligent Transport Systems 2005, 6 november 2005 through 10 november 2005, San Francisco, pp 1558–1567

  • Wiedemann R (1974) Simulation des strassenverkehrsflusses

  • Zhang Y, Cassandras CG (2018a) A decentralized optimal control framework for connected automated vehicles at urban intersections with dynamic resequencing. In: 57th IEEE Conference on Decision and Control, pp 217–222

  • Zhang Y, Cassandras CG (2018b) The penetration effect of connected automated vehicles in urban traffic: an energy impact study. In: 2nd IEEE Conference on Control Technology and Applications, pp 620–625

  • Zhang Y, Cassandras CG (2019) Decentralized optimal control of connected automated vehicles at signal-free intersections including comfort-constrained turns and safety guarantees. arXiv:1903.04600

  • Zhang Y, Malikopoulos AA, Cassandras CG (2016) Optimal control and coordination of connected and automated vehicles at urban traffic intersections. In: Proceedings of the 2016 American Control Conference, pp 6227–6232

  • Zhang Y, Cassandras CG, Li W, Mosterman PJ (2017a) A simEvents model for hybrid traffic simulation. In: Proceedings of the 2017 Winter Simulation Conference, IEEE Press, pp 1455–1466

  • Zhang Y, Cassandras CG, Malikopoulos AA (2017b) Optimal control of connected automated vehicles at urban traffic intersections: A feasibility enforcement analysis. In: Proceedings of the 2017 American Control Conference, pp 3548–3553

  • Zhang Y, Malikopoulos AA, Cassandras CG (2017c) Decentralized optimal control for connected automated vehicles at intersections including left and right turns. In: 56th IEEE Conference on Decision and Control, pp 4428–4433

  • Zhang Y, Cassandras CG, Li W, Mosterman PJ (2018) A discrete-event and hybrid simulation framework based on simEvents for intelligent transportation system analysis. IFAC-PapersOnLine 51(7):323–328

    Article  Google Scholar 

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Authors and Affiliations

  1. Division of Systems Engineering, Boston University, 15 Saint Mary’s St., Brookline, MA, 02446, USA

    Yue Zhang & Christos G. Cassandras

  2. MathWorks, 1 Lakeside Campus Drive, Natick, MA, 01760, USA

    Wei Li & Pieter J. Mosterman

Authors
  1. Yue Zhang
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  2. Christos G. Cassandras
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  3. Wei Li
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  4. Pieter J. Mosterman
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Correspondence to Yue Zhang.

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This article belongs to the Topical Collection: Applications-2020

Guest Editors: Francesco Basile, Jan Komenda, and Christoforos Hadjicostis

Supported in part by NSF under grants ECCS-1509084 and CNS-1645681, by AFOSR under grant FA9550-12-1-0113, by ARPA-E’s NEXTCAR program under grant DE-AR0000796, and by Bosch, Honda R&D Americas, and MathWorks.

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Zhang, Y., Cassandras, C.G., Li, W. et al. A discrete-event and hybrid traffic simulation model based on SimEvents for intelligent transportation system analysis in Mcity. Discrete Event Dyn Syst 29, 265–295 (2019). https://doi.org/10.1007/s10626-019-00286-w

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  • DOI: https://doi.org/10.1007/s10626-019-00286-w

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