Abstract
The paper is proposing an advanced simulation tool for evaluating the behavior of semi and fully autonomous vehicles in the presence of the actions and decisions of the drivers (acquired and automated competencies). The vehicle simulator is built on a hexapod platform, the driver is interacting with steering wheel and pedals with the virtual vehicle. The selected traffic scenario is a roundabout with several vehicles. The behavior of these vehicles is imposed by computing their speed with a deterministic finite state automaton while maintaining the imposed path. These vehicles have simplified kinematic models (the acceleration is controlled) and they are obeying traffic rules. The driver will negotiate the roundabout while studying and evaluating the behavior of the other vehicles. The outcome of this simulation environment will be a new human-machine interaction evaluation introduced through a real-time simulation system in which the semi and fully autonomous vehicles’ behavior is evaluated. The assessment of the driving experience of the vehicles in the new age of the autonomous vehicle is an important step in the algorithm development for autonomous decision-making systems and will contribute to safety analysis and the fidelity of the simulation models.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Katrakazas, C., Quddus, M., Chen, W.H., Deka, L.: Real-time motion planning methods for autonomous on-road driving: state-of-the-art and future research directions. Transp. Res. Part C: Emerg. Technol. 60, 416–444 (2015)
Schwarting, W., Alonso-Mora, J., Rus, D.: Planning and decision-making for autonomous vehicles. Annu. Rev. Control Robot. Auton. Syst. 1, 187–210 (2018)
Tian, R., Li, N., Kolmanovsky, I., Girard, A, Yildiz, Y.: Adaptive game-theoretic decision making for autonomous vehicle control at roundabouts. In: 2018 IEEE Conference on Decision and Control (CDC), pp. 321–326 (2018)
Rastelli, J.P., Penas, M.S.: Fuzzy logic steering control of autonomous vehicles inside roundabouts. Appl. Soft Comput. 35, 662–669 (2015)
Ting, Y., Tai, Y.: Using technology in students’ daily life to teach science. Int. J. Technol. Eng. Educ. 9(1), 21–29 (2012)
Chung, C., Dzan, W., Shih, R., Tsai, H., Lou, S.: Creativity learning through blended teaching for designing amphibious vehicle. Int. J. Technol. Eng. Educ. 9(1), 34–38 (2012)
Dahl, J., Lee, C.: Empirical estimation of capacity for roundabouts using adjusted gap-acceptance parameters for trucks. Transp. Res. Rec. 2312(1), 34–45 (2012)
Toledo, T., Koutsopoulos, H.N., Ben-Akiva, M.: Integrated driving behavior modeling. Transp. Res. Part C: Emerg. Technol. 15(2), 96–112 (2007)
U.S. Department of Transportation Federal Highway Administration: Roundabouts, 3–10 (2010)
Matlab, Simulink, Mathworks Inc Homepage. https://www.mathworks.com/products.html. Accessed 27 May 2020
Michon, J.A.: A critical view of driver behavior models: what do we know, what should we do. In: Human Behavior and Traffic Safety, pp. 485–524. Springer, Boston (1985)
Antonya, C., Carabulea, L., Pauna, C.: Predictive actuation of a driving simulator. In: Burnete, N., Varga, B. (eds.) International Congress of Automotive and Transport Engineering 2018, pp. 128–135. Springer, Cham (2018)
Schwarting, W., Alonso-Mora, J., Paull, L., Karaman, S., Rus, D.: Safe nonlinear trajectory generation for parallel autonomy with a dynamic vehicle model. IEEE Trans. Intell. Transp. Syst. 19(9), 2994–3008 (2017)
Petrovskaya, A., Thrun, S.: Model based vehicle detection and tracking for autonomous urban driving. Auton. Robots 26(2–3), 129–139 (2009)
Wardzinski, A.: Dynamic risk assessment in autonomous vehicles motion planning. In: 1st IEEE International Conference on Information Technology, pp. 1–4 (2008)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Antonya, C., Buzdugan, I.D. (2021). Multimodal Environment for Studying the Behavior of Autonomous Vehicles in Traffic Situations. In: Auer, M.E., Centea, D. (eds) Visions and Concepts for Education 4.0. ICBL 2020. Advances in Intelligent Systems and Computing, vol 1314. Springer, Cham. https://doi.org/10.1007/978-3-030-67209-6_37
Download citation
DOI: https://doi.org/10.1007/978-3-030-67209-6_37
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-67208-9
Online ISBN: 978-3-030-67209-6
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)