Abstract
In this study, a maneuver prediction and planning framework is proposed on the basis of game theories for complex traffic scenarios. In this framework, the interaction and gaming between multiple vehicles are considered by employing the extensive form game theories, which were extensively researched for sequential gaming problems. Finally, this framework is applied and proved in different lane-change scenarios. The results show that this framework could predict other vehicles’ driving maneuvers and plan maneuvers for ego vehicles by considering interaction and gaming between multiple vehicles, which helps AVs understand the environment better and make the cooperative maneuver planning in complex traffic scenarios.
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Acknowledgments
This work was supported by China Postdoctoral Science Foundation Special Funded Projects under Grant No. 2018T110095, Project funded by China Postdoctoral Science Foundation under Grant No. 2017M620765, National Key Research and Development Program of China under Grant No. 2017YFB0102603, and Junior Fellowships for Advanced Innovation Think-tank Program of China Association for Science and Technology under Grant No. DXB-ZKQN-2017-035.
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Gao, H., Xie, G., Wang, K., Liu, Y., Li, D. (2019). Behavior Prediction and Planning for Intelligent Vehicles Based on Multi-vehicles Interaction and Game Awareness. In: Sun, F., Liu, H., Hu, D. (eds) Cognitive Systems and Signal Processing. ICCSIP 2018. Communications in Computer and Information Science, vol 1006. Springer, Singapore. https://doi.org/10.1007/978-981-13-7986-4_39
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DOI: https://doi.org/10.1007/978-981-13-7986-4_39
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