Online Local Path Planning on the Campus Environment for Autonomous Driving Considering Road Constraints and Multiple Obstacles
In this paper, an urban-based path planning algorithm that considered multiple obstacles and road constraints in a university campus environment with an autonomous micro electric vehicle (micro-EV) is studied. Typical path planning algorithms, such as A*, particle swarm optimization (PSO), and rapid...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-04-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/11/9/3909 |
| _version_ | 1797536233433333760 |
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| author | Changhyeon Park Seok-Cheol Kee |
| author_facet | Changhyeon Park Seok-Cheol Kee |
| author_sort | Changhyeon Park |
| collection | DOAJ |
| description | In this paper, an urban-based path planning algorithm that considered multiple obstacles and road constraints in a university campus environment with an autonomous micro electric vehicle (micro-EV) is studied. Typical path planning algorithms, such as A*, particle swarm optimization (PSO), and rapidly exploring random tree* (RRT*), take a single arrival point, resulting in a lane departure situation on the high curved roads. Further, these could not consider urban-constraints to set collision-free obstacles. These problems cause dangerous obstacle collisions. Additionally, for drive stability, real-time operation should be guaranteed. Therefore, an urban-based online path planning algorithm, which is robust in terms of a curved-path with multiple obstacles, is proposed. The algorithm is constructed using two methods, A* and an artificial potential field (APF). To validate and evaluate the performance in a campus environment, autonomous driving systems, such as vehicle localization, object recognition, vehicle control, are implemented in the micro-EV. Moreover, to confirm the algorithm stability in the complex campus environment, hazard scenarios that complex obstacles can cause are constructed. These are implemented in the form of a delivery service using an autonomous driving simulator, which mimics the Chungbuk National University (CBNU) campus. |
| first_indexed | 2024-03-10T11:57:42Z |
| format | Article |
| id | doaj.art-2c77f9c4975e4fb99c855908f824fe01 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T11:57:42Z |
| publishDate | 2021-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-2c77f9c4975e4fb99c855908f824fe012023-11-21T17:10:45ZengMDPI AGApplied Sciences2076-34172021-04-01119390910.3390/app11093909Online Local Path Planning on the Campus Environment for Autonomous Driving Considering Road Constraints and Multiple ObstaclesChanghyeon Park0Seok-Cheol Kee1Department of Smart Car Engineering, Chungbuk National University, Seowon-gu Chungdae-ro 1, Cheongju-si 28644, KoreaSmart Car Research Center, Chungbuk National University, Seowon-gu Chungdae-ro 1, Cheongju-si 28644, KoreaIn this paper, an urban-based path planning algorithm that considered multiple obstacles and road constraints in a university campus environment with an autonomous micro electric vehicle (micro-EV) is studied. Typical path planning algorithms, such as A*, particle swarm optimization (PSO), and rapidly exploring random tree* (RRT*), take a single arrival point, resulting in a lane departure situation on the high curved roads. Further, these could not consider urban-constraints to set collision-free obstacles. These problems cause dangerous obstacle collisions. Additionally, for drive stability, real-time operation should be guaranteed. Therefore, an urban-based online path planning algorithm, which is robust in terms of a curved-path with multiple obstacles, is proposed. The algorithm is constructed using two methods, A* and an artificial potential field (APF). To validate and evaluate the performance in a campus environment, autonomous driving systems, such as vehicle localization, object recognition, vehicle control, are implemented in the micro-EV. Moreover, to confirm the algorithm stability in the complex campus environment, hazard scenarios that complex obstacles can cause are constructed. These are implemented in the form of a delivery service using an autonomous driving simulator, which mimics the Chungbuk National University (CBNU) campus.https://www.mdpi.com/2076-3417/11/9/3909path planningartificial potential fieldsteering kinematicsautonomous vehicleMORAI simulator |
| spellingShingle | Changhyeon Park Seok-Cheol Kee Online Local Path Planning on the Campus Environment for Autonomous Driving Considering Road Constraints and Multiple Obstacles Applied Sciences path planning artificial potential field steering kinematics autonomous vehicle MORAI simulator |
| title | Online Local Path Planning on the Campus Environment for Autonomous Driving Considering Road Constraints and Multiple Obstacles |
| title_full | Online Local Path Planning on the Campus Environment for Autonomous Driving Considering Road Constraints and Multiple Obstacles |
| title_fullStr | Online Local Path Planning on the Campus Environment for Autonomous Driving Considering Road Constraints and Multiple Obstacles |
| title_full_unstemmed | Online Local Path Planning on the Campus Environment for Autonomous Driving Considering Road Constraints and Multiple Obstacles |
| title_short | Online Local Path Planning on the Campus Environment for Autonomous Driving Considering Road Constraints and Multiple Obstacles |
| title_sort | online local path planning on the campus environment for autonomous driving considering road constraints and multiple obstacles |
| topic | path planning artificial potential field steering kinematics autonomous vehicle MORAI simulator |
| url | https://www.mdpi.com/2076-3417/11/9/3909 |
| work_keys_str_mv | AT changhyeonpark onlinelocalpathplanningonthecampusenvironmentforautonomousdrivingconsideringroadconstraintsandmultipleobstacles AT seokcheolkee onlinelocalpathplanningonthecampusenvironmentforautonomousdrivingconsideringroadconstraintsandmultipleobstacles |