Game-Theoretic Motion Planning with Perception Uncertainty and Right-of-Way Constraints
This paper addresses two challenges in AV motion planning: adherence to right-of-way and handling uncertainties, using two game-theoretic frameworks, namely Stackelberg and Nash Bayesian (Bayesian). By modeling the interactions between road users as a hierarchical relationship, the proposed approach...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-12-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/24/24/8177 |
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| author | Pouya Panahandeh Ahmad Reza Alghooneh Mohammad Pirani Baris Fidan Amir Khajepour |
| author_facet | Pouya Panahandeh Ahmad Reza Alghooneh Mohammad Pirani Baris Fidan Amir Khajepour |
| author_sort | Pouya Panahandeh |
| collection | DOAJ |
| description | This paper addresses two challenges in AV motion planning: adherence to right-of-way and handling uncertainties, using two game-theoretic frameworks, namely Stackelberg and Nash Bayesian (Bayesian). By modeling the interactions between road users as a hierarchical relationship, the proposed approach enables the AV to strategically optimize its trajectory while considering the actions and priorities of other road users. Additionally, the Bayesian equilibrium aspect of the framework incorporates probabilistic beliefs and updates them based on sensor measurements, allowing the AV to make informed decisions in the presence of uncertainty in the sensory system. Experimental assessments demonstrate the efficacy of the approach, emphasizing its ability to improve the reliability and adaptability of AV motion planning. |
| format | Article |
| id | doaj-art-8af7f79f1c854866a819ea8df1b7ea83 |
| institution | Kabale University |
| issn | 1424-8220 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-8af7f79f1c854866a819ea8df1b7ea832024-12-27T14:53:13ZengMDPI AGSensors1424-82202024-12-012424817710.3390/s24248177Game-Theoretic Motion Planning with Perception Uncertainty and Right-of-Way ConstraintsPouya Panahandeh0Ahmad Reza Alghooneh1Mohammad Pirani2Baris Fidan3Amir Khajepour4Mechanical and Mechatronics Engineering Department, University of Waterloo, 200 University Ave W, Waterloo, ON N2L 3G1, CanadaMechanical and Mechatronics Engineering Department, University of Waterloo, 200 University Ave W, Waterloo, ON N2L 3G1, CanadaDepartment of Mechanical Engineering, University of Ottawa, Ottawa, ON K1N 6N5, CanadaMechanical and Mechatronics Engineering Department, University of Waterloo, 200 University Ave W, Waterloo, ON N2L 3G1, CanadaMechanical and Mechatronics Engineering Department, University of Waterloo, 200 University Ave W, Waterloo, ON N2L 3G1, CanadaThis paper addresses two challenges in AV motion planning: adherence to right-of-way and handling uncertainties, using two game-theoretic frameworks, namely Stackelberg and Nash Bayesian (Bayesian). By modeling the interactions between road users as a hierarchical relationship, the proposed approach enables the AV to strategically optimize its trajectory while considering the actions and priorities of other road users. Additionally, the Bayesian equilibrium aspect of the framework incorporates probabilistic beliefs and updates them based on sensor measurements, allowing the AV to make informed decisions in the presence of uncertainty in the sensory system. Experimental assessments demonstrate the efficacy of the approach, emphasizing its ability to improve the reliability and adaptability of AV motion planning.https://www.mdpi.com/1424-8220/24/24/8177motion planningautonomous vehicleuncertaintysensor fusiongame theory |
| spellingShingle | Pouya Panahandeh Ahmad Reza Alghooneh Mohammad Pirani Baris Fidan Amir Khajepour Game-Theoretic Motion Planning with Perception Uncertainty and Right-of-Way Constraints Sensors motion planning autonomous vehicle uncertainty sensor fusion game theory |
| title | Game-Theoretic Motion Planning with Perception Uncertainty and Right-of-Way Constraints |
| title_full | Game-Theoretic Motion Planning with Perception Uncertainty and Right-of-Way Constraints |
| title_fullStr | Game-Theoretic Motion Planning with Perception Uncertainty and Right-of-Way Constraints |
| title_full_unstemmed | Game-Theoretic Motion Planning with Perception Uncertainty and Right-of-Way Constraints |
| title_short | Game-Theoretic Motion Planning with Perception Uncertainty and Right-of-Way Constraints |
| title_sort | game theoretic motion planning with perception uncertainty and right of way constraints |
| topic | motion planning autonomous vehicle uncertainty sensor fusion game theory |
| url | https://www.mdpi.com/1424-8220/24/24/8177 |
| work_keys_str_mv | AT pouyapanahandeh gametheoreticmotionplanningwithperceptionuncertaintyandrightofwayconstraints AT ahmadrezaalghooneh gametheoreticmotionplanningwithperceptionuncertaintyandrightofwayconstraints AT mohammadpirani gametheoreticmotionplanningwithperceptionuncertaintyandrightofwayconstraints AT barisfidan gametheoreticmotionplanningwithperceptionuncertaintyandrightofwayconstraints AT amirkhajepour gametheoreticmotionplanningwithperceptionuncertaintyandrightofwayconstraints |