The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Local Path Planning for Off-Road Autonomous Driving With Avoidance of Static Obstacles
Abstract
In this paper, a real-time path-planning algorithm that provides an optimal path for off-road autonomous driving with static obstacles avoidance is presented. The proposed planning algorithm computes a path based on a set of predefined waypoints. The predefined waypoints provide the base frame of a curvilinear coordinate system to generate path candidates for autonomous vehicle path planning. Each candidate is converted to a Cartesian coordinate system and evaluated using obstacle data. To select the optimal path, the priority of each path is determined by considering the path safety cost, path smoothness, and path consistency. The proposed path-planning algorithms were applied to the autonomous vehicle A1, which won the 2010 Autonomous Vehicle Competition organized by the Hyundai-Kia Automotive Group in Korea.
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Cites
Autonomous driving in urban environments: Boss and the Urban Challenge
Urmson, C., Anhalt, J., Bagnell, D., Baker, C., Bittner, R., Clark, M. N., Dolan, J., Duggins, D., Galatali, T., Geyer, C., et al. (2008) · Journal of Field Robotics · doi:10.1002/rob.20255 · Cited by 1,555
Cited by
A Review of Motion Planning Techniques for Automated Vehicles
Gonzalez, D., Perez, J., Milanes, V., & Nashashibi, F. (2016) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2015.2498841 · Cited by 1,670
Deep Learning for Safe Autonomous Driving: Current Challenges and Future Directions
Muhammad, K., Ullah, A., Lloret, J., Ser, J. D., & de Albuquerque, V. H. C. (2021) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2020.3032227 · Cited by 659
A survey on hybrid human-artificial intelligence for autonomous driving
Ning, H., Yin, R., Ullah, A., & Shi, F. (2022) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2021.3074695 · Cited by 84
Metadata
- Authors
- Chu, K., Lee, M., & Sunwoo, M.
- Venue
- IEEE Transactions on Intelligent Transportation Systems
- Published
- 2012-12
- Volume
- 13
- Issue
- 4
- Pages
- 1599-1616
- ISSN
- 1524-9050 (ISSN-L)
- 1558-0016
- OpenAlex
- W2032325911
- Cited by
- 350
- References
- 1
- FWCI
- 12.79
- Type
- journal article
- Language
- en
- Open access
- closed
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- Chu, K., Lee, M., & Sunwoo, M. (2012). Local Path Planning for Off-Road Autonomous Driving With Avoidance of Static Obstacles. IEEE Transactions on Intelligent Transportation Systems. https://doi.org/10.1109/tits.2012.2198214
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
