Abstract
Automatic lane change is a feature in self-driving cars where the vehicle can change lanes on its own, without driver input. It aims to improve safety and make driving more convenient for the driver. In this paper, adaptive grid and occupancy map methods are proposed for automatic lane change. Nine grids are formed based on the ego vehicle to create an active occupancy grid map on the lane change request of the driver. It is suitable for use in autonomous vehicles that require real-time calculation because it reduces the number of cases from 256 to 32 where target vehicles may exist around the ego vehicle using active occupancy grid maps. The algorithm was programmed with Matlab/Simulink, and the simulation environment was constructed using CarMaker. Simulation results show that the proposed algorithm can make safe automatic lane change even in a crowded traffic condition.
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Acknowledgements
This work was partly supported by Institute of Information and communications Technology Planning and Evaluation (IITP) grant funded by the Korea government (MSIT) (No. RS-2022-00155911, Artificial Intelligence Convergence Innovation Human Resources Development (Kyung Hee University)) and Defense Venture Innovation Technology Support Project, Industry-Academia-Research Collabo R&D (V220022, G21S325576801) supervised by the Defense Acquisition Program Administration, Ministry of SMEs and Startups and E Intelligence, Integrated Education Institute for Frontier Science and Technology (BK21 Four) (5199991413915).
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Woo, S. et al. (2024). Automatic Lane Change Using Adaptive Grid Map. In: Lee, SG., An, J., Chong, N.Y., Strand, M., Kim, J.H. (eds) Intelligent Autonomous Systems 18. IAS 2023. Lecture Notes in Networks and Systems, vol 795. Springer, Cham. https://doi.org/10.1007/978-3-031-44851-5_6
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DOI: https://doi.org/10.1007/978-3-031-44851-5_6
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