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| --- | ||
| title: "4C: Custom-and-Correct-by-Construction Controller Synthesis using Multi-modal Human Feedback" | ||
| collection: publications | ||
| permalink: /publication/4c | ||
| excerpt: 'This work addresses the challenge of generating custom and naturalistic autonomous vehicle behaviors to meet individual user expectations while ensuring safety' | ||
| date: 2024-12 | ||
| venue: 'IFAC CPHS' | ||
| # paperurl: 'https://ruyakrgl.github.io/files/4c.pdf' | ||
| citation: 'R. Karagulle, M. A. V. Calderon, N. Ozay. “4C: Custom-and-Correct-by-Construction Controller Synthesis using Multi-modal Human Feedback”. (2024) (accepted - 5th IFAC Workshop on Cyber-Physical & Human Systems)' | ||
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| --- | ||
| This work addresses the challenge of generating custom and naturalistic autonomous vehicle behaviors to meet individual user expectations while ensuring safety. | ||
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| [You can access paper here]('https://ruyakrgl.github.io//files/4c.pdf') | ||
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| <!-- R. Karagulle, M. A. V. Calderon, N. Ozay. “4C: Custom-and-Correct-by-Construction Controller Synthesis using Multi-modal Human Feedback”. (2024) (accepted - 5th IFAC Workshop on Cyber-Physical & Human Systems) --> |
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| Original file line number | Diff line number | Diff line change |
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| --- | ||
| title: "A Preference Learning Approach to Develop Safe and Personalizable Autonomous Vehicles" | ||
| title: "A Safe Preference Learning Approach for Personalization With Applications to Autonomous Vehicles" | ||
| collection: publications | ||
| permalink: /publication/preference_learning_w_STL | ||
| excerpt: 'This work introduces a preference learning method that ensures adherence to traffic rules for autonomous vehicles.' | ||
| date: 2023-09-27 | ||
| venue: 'IEEE RA-L (submitted)' | ||
| date: 2024-02-13 | ||
| venue: 'IEEE RA-L' | ||
| # paperurl: 'https://ruyakrgl.github.io/files/preference_learning_w_STL.pdf' | ||
| citation: 'Karagulle, R., Aréchiga, N., DeCastro, J., Ozay, N. (2023).A Preference Learning Approach to Develop Safe and Personalizable Autonomous Vehicles. (submitted to RA-L)' | ||
| citation: 'R. Karagulle, N. Aréchiga, A. Best, J. DeCastro and N. Ozay, "A Safe Preference Learning Approach for Personalization With Applications to Autonomous Vehicles," in IEEE Robotics and Automation Letters, vol. 9, no. 5, pp. 4226-4233, May 2024, doi: 10.1109/LRA.2024.3375626.' | ||
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| --- | ||
| This work introduces a preference learning method that ensures adherence to traffic rules for autonomous vehicles. | ||
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| [You can download paper here]('https://ruyakrgl.github.io//files/preference_learning_w_STL.pdf') | ||
| [You can access paper here]('https://ruyakrgl.github.io//files/preference_learning_w_STL.pdf') | ||
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| <!-- Recommended citation: Karagulle, R., Aréchiga, N., DeCastro, J., Ozay, N. (2023).A Preference Learning Approach to Develop Safe and Personalizable Autonomous Vehicles. (submitted to RA-L) --> | ||
| <!-- R. Karagulle, N. Aréchiga, A. Best, J. DeCastro and N. Ozay, "A Safe Preference Learning Approach for Personalization With Applications to Autonomous Vehicles," in IEEE Robotics and Automation Letters, vol. 9, no. 5, pp. 4226-4233, May 2024, doi: 10.1109/LRA.2024.3375626. --> |
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| --- | ||
| title: "Incorporating Logic in Online Preference Learning for Safe Personalization of Autonomous Vehicles" | ||
| collection: publications | ||
| permalink: /publication/sapl | ||
| excerpt: 'This work introduces an active preference learning method that ensures adherence to traffic rules for autonomous vehicles by decreasing the number of question asked to the user.' | ||
| date: 2024-05-14 | ||
| venue: 'ACM HSCC' | ||
| # paperurl: 'https://ruyakrgl.github.io/files/sapl.pdf' | ||
| citation: 'Ruya Karagulle, Necmiye Ozay, Nikos Arechiga, Jonathan Decastro, and Andrew Best. 2024. Incorporating Logic in Online Preference Learning for Safe Personalization of Autonomous Vehicles. In Proceedings of the 27th ACM International Conference on Hybrid Systems: Computation and Control (HSCC 24). Association for Computing Machinery, New York, NY, USA, Article 5, 1–11. https://doi.org/10.1145/3641513.3650129' | ||
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| --- | ||
| This work introduces an active preference learning method that ensures adherence to traffic rules for autonomous vehicles by decreasing the number of question asked to the user. | ||
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| [You can access paper here]('https://ruyakrgl.github.io//files/sapl.pdf') | ||
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| <!-- Ruya Karagulle, Necmiye Ozay, Nikos Arechiga, Jonathan Decastro, and Andrew Best. 2024. Incorporating Logic in Online Preference Learning for Safe Personalization of Autonomous Vehicles. In Proceedings of the 27th ACM International Conference on Hybrid Systems: Computation and Control (HSCC '24). Association for Computing Machinery, New York, NY, USA, Article 5, 1–11. https://doi.org/10.1145/3641513.3650129 --> |
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