Zusammenfassung
Unsuitable lane-change maneuvers are one of the most common potential safety risks in traffic. Nevertheless, it is a maneuver that must be executed carefully by both human drivers and self-driving cars. Developing a suitable automated driving algorithm for self-driving cars to address the lane changing problem is not straightforward because the problem can only be stated as a high dimension problem with many variables and parameters. Therefore, safe driving needs to be assured by optimal trajectory generating algorithms as well as high-level behavioral planners, which assess the safety of the intended behavior and discard the infeasible trajectory candidates. In this paper, a hybrid approach to a behavioral planner algorithm with lane changing behavior using the Frenet coordinate system was developed to solve the lane changing maneuver problem on roads that consist of road segments with different curvature values. The controllers that need to generate the actuator commands according to the reference trajectory cannot always precisely follow the trajectories. Hence, the waypoint generation algorithm has to adapt to the controller and vehicle dynamics. The road structures for the driving scenarios were modeled according to the OpenDRIVE format and were implemented in a model-based traffic simulation environment MOBATSim. The proposed approach is evaluated and demonstrated by the simulating driving scenarios in the same environment.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Literatur
Kousik, S., Vaskov, S., Johnson-Roberson, M., Vasudevan, R.: Safe trajectory synthesis for autonomous driving in unforeseen environments 58271, V001T44A005 (2017)
Mao, T., Wang, H., Wang, Z.: An efficient lane model for complex traffic simulation. Comput. Animation and Virtual Worlds 26, (2015). https://doi.org/10.1002/cav.1642
Werling, M., Ziegler, J., Kammel, S., Thrun, S.: Optimal trajectory generation for dynamic street scenarios in a frenét frame. In: 2010 IEEE International Conference on Robotics and Automation, S. 987–993 (2010). 10.1109/ROBOT.2010.5509799
Houenou, A., Bonnifait, P., Cherfaoui, V., Yao, W.: Vehicle trajectory prediction based on motion model and maneuver recognition. In: 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems, S. 4363–4369 (2013). 10.1109/IROS.2013.6696982
Voßwinkel, R., Mutlu, I., Alaa, K., Schrödel, F.: A modular and model-free trajectory planning strategy for automated driving. In: 2020 European Control Conference (ECC), S. 1186–1191 (2020). 10.23919/ECC51009.2020.9143746
Shamir, T.: How should an autonomous vehicle overtake a slower moving vehicle: Design and analysis of an optimal trajectory. IEEE Trans. Autom. Control 49(4), 607–610 (2004)
Schmidt, M., Manna, C., Braun, J.H., Wissing, C., Mohamed, M., Bertram, T.: An interaction-aware lane change behavior planner for automated vehicles on highways based on polygon clipping. IEEERobot. Autom.Lett. 4(2), 1876–1883 (2019). https://doi.org/10.1109/LRA.2019.2898093
Jin, L., Fang, W., Zhang, Y., Yang, S., Hou, H.: Research on safety lane change model of driver assistant system on highway. In: 2009 IEEE Intelligent Vehicles Symposium, S. 1051–1056 (2009). 10.1109/IVS.2009.5164426
Zhao, D., Lam, H., Peng, H., Bao, S., LeBlanc, D.J., Nobukawa, K., Pan, C.S.: Accelerated evaluation of automated vehicles safety in lane-change scenarios based on importance sampling techniques. IEEE Trans. Intell. Transp. Syst. 18(3), 595–607 (2017). https://doi.org/10.1109/TITS.2016.2582208
Swaroop, D., Hedrick, J.K., Choi, S.B.: Direct adaptive longitudinal control of vehicle platoons. IEEE Trans. Veh. Technol. 50(1), 150–161 (2001). https://doi.org/10.1109/25.917908
Catino, B., Santini, S., di Bernardo, M.: Mcs adaptive control of vehicle dynamics: An application of bifurcation techniques to control system design. In: 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475), Bd. 3, S. 2252–2257 Vol.3 (2003). 10.1109/CDC.2003.1272953
Saraoglu, M., Morozov, A., Janschek, K.: Mobatsim: Model-based autonomous traffic simulation framework for fault-error-failure chain analysis. IFAC-PapersOnLine 52(8), 239–244 (2019). 10.1016/j.ifacol.2019.08.077. http://www.sciencedirect.com/science/article/pii/S2405896319304100. 10th IFAC Symposium on Intelligent Autonomous Vehicles IAV 2019
Zefran, M.: Continuous methods for motion planning. IRCS Technical Reports Series S. 111 (1996)
Hoffmann, G.M., Tomlin, C.J., Montemerlo, M., Thrun, S.: Autonomous automobile trajectory tracking for off-road driving: Controller design, experimental validation and racing. In: 2007 American Control Conference, S. 2296–2301. IEEE (2007)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature
About this paper
Cite this paper
Yang, Q., Shi, Q., Saraoğlu, M., Janschek, K. (2021). A Hybrid Approach using an Adaptive Waypoint Generator for Lane-changing Maneuver on Curved Roads. In: Bargende, M., Reuss, HC., Wagner, A. (eds) 21. Internationales Stuttgarter Symposium. Proceedings. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-33521-2_10
Download citation
DOI: https://doi.org/10.1007/978-3-658-33521-2_10
Published:
Publisher Name: Springer Vieweg, Wiesbaden
Print ISBN: 978-3-658-33520-5
Online ISBN: 978-3-658-33521-2
eBook Packages: Computer Science and Engineering (German Language)