Decision-Making Model of Autonomous Driving at Intersection Based on Unified Driving Operational Risk Field
Safety and comfort are the two major requirements for the successful implementation of self-driving cars, which are anticipated to constitute the future generation of transportation. To create safe and effective self-driving car trajectories, a novel behavioral decision model is developed. First, a...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-02-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/13/4/2094 |
| _version_ | 1827758921611214848 |
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| author | Ziming Lu Weiwei Zhang Bo Zhao |
| author_facet | Ziming Lu Weiwei Zhang Bo Zhao |
| author_sort | Ziming Lu |
| collection | DOAJ |
| description | Safety and comfort are the two major requirements for the successful implementation of self-driving cars, which are anticipated to constitute the future generation of transportation. To create safe and effective self-driving car trajectories, a novel behavioral decision model is developed. First, a risk field model for driving activities based on vehicle kinematics and Eulerian solenoids is constructed. From there, the principle of least action is applied to produce the best trajectory points. Finally, nine typical unit scenarios are simulated by matlab’s driving scenario designer to verify the feasibility of the decision-making algorithm. This study illustrates how an unified operational risk field can efficiently increase intersection passing efficiency while ensuring safety, utilizing the principle of least action. The experimental results show that in the scenario of unprotected left turn and more than 5 vehicles in the intersection, the decision-making model improves the pass rate by 23% compared with the TTI (Time To Intersection) threshold method. |
| first_indexed | 2024-03-11T09:13:28Z |
| format | Article |
| id | doaj.art-d0b574de504b4894aea925bfeb3ce696 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-11T09:13:28Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-d0b574de504b4894aea925bfeb3ce6962023-11-16T18:50:47ZengMDPI AGApplied Sciences2076-34172023-02-01134209410.3390/app13042094Decision-Making Model of Autonomous Driving at Intersection Based on Unified Driving Operational Risk FieldZiming Lu0Weiwei Zhang1Bo Zhao2School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai 201620, ChinaSchool of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai 201620, ChinaSchool of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai 201620, ChinaSafety and comfort are the two major requirements for the successful implementation of self-driving cars, which are anticipated to constitute the future generation of transportation. To create safe and effective self-driving car trajectories, a novel behavioral decision model is developed. First, a risk field model for driving activities based on vehicle kinematics and Eulerian solenoids is constructed. From there, the principle of least action is applied to produce the best trajectory points. Finally, nine typical unit scenarios are simulated by matlab’s driving scenario designer to verify the feasibility of the decision-making algorithm. This study illustrates how an unified operational risk field can efficiently increase intersection passing efficiency while ensuring safety, utilizing the principle of least action. The experimental results show that in the scenario of unprotected left turn and more than 5 vehicles in the intersection, the decision-making model improves the pass rate by 23% compared with the TTI (Time To Intersection) threshold method.https://www.mdpi.com/2076-3417/13/4/2094autonomous drivingartificial fieldprinciple of least actiondecision making modelcollision avoidance |
| spellingShingle | Ziming Lu Weiwei Zhang Bo Zhao Decision-Making Model of Autonomous Driving at Intersection Based on Unified Driving Operational Risk Field Applied Sciences autonomous driving artificial field principle of least action decision making model collision avoidance |
| title | Decision-Making Model of Autonomous Driving at Intersection Based on Unified Driving Operational Risk Field |
| title_full | Decision-Making Model of Autonomous Driving at Intersection Based on Unified Driving Operational Risk Field |
| title_fullStr | Decision-Making Model of Autonomous Driving at Intersection Based on Unified Driving Operational Risk Field |
| title_full_unstemmed | Decision-Making Model of Autonomous Driving at Intersection Based on Unified Driving Operational Risk Field |
| title_short | Decision-Making Model of Autonomous Driving at Intersection Based on Unified Driving Operational Risk Field |
| title_sort | decision making model of autonomous driving at intersection based on unified driving operational risk field |
| topic | autonomous driving artificial field principle of least action decision making model collision avoidance |
| url | https://www.mdpi.com/2076-3417/13/4/2094 |
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