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アイテム
二分決定図と空間行動粒度に基づくローカルダイナミックマップを実装可能にする手法に関する研究
https://doi.org/10.18997/00009023
https://doi.org/10.18997/000090232fab4959-dbb4-45d9-b5a8-01d7391a49b3
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
sei_k_449.pdf (31.6 MB)
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| アイテムタイプ | 学位論文 = Thesis or Dissertation(1) | |||||||
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| 公開日 | 2022-12-05 | |||||||
| 資源タイプ | ||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_db06 | |||||||
| 資源タイプ | doctoral thesis | |||||||
| タイトル | ||||||||
| タイトル | A Feasible Solution of the Local Dynamic Map Based on Binary Decision Diagrams and Spatial-Behavioral Granularity | |||||||
| 言語 | en | |||||||
| タイトル | ||||||||
| タイトル | 二分決定図と空間行動粒度に基づくローカルダイナミックマップを実装可能にする手法に関する研究 | |||||||
| 言語 | ja | |||||||
| 言語 | ||||||||
| 言語 | eng | |||||||
| 著者 |
Kumar, Arvind
× Kumar, Arvind
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| 抄録 | ||||||||
| 内容記述タイプ | Abstract | |||||||
| 内容記述 | Autonomous vehicles （AVs） have been increasing rapidly on the road in recent years. However, the safety of AVs is of significant concern, which we must ensure. AVs use sensor information to achieve autonomy, but sensors such as cameras and lidar have limitations, and vehicles cannot rely on them entirely for safe navigation. To assist AVs with static information, high-definition maps （HD maps） can facilitate the complex static details of the surrounding for safe autonomy. However, we can model complex static information using HD maps for navigation; detecting and maintaining the traffic participant’s dynamic information using sensors of the ego vehicle alone is still a significant concern for safe navigation. In such a situation of sensing limitations, Cooperative Intelligent Transport Systems （C-ITS） is one approach to facilitate vehicle navigation through sharing information between the traffic participants. The C-ITS approach has various Intelligent transportation system （ITS） station units, namely Personal, Vehicle, Road-side and Central ITS station units. A Local Dynamic Map （LDM） is a critical component in any ITS station’s facilities layer. LDM is one way to maintain static and dynamic information of the traffic participants in a consistent geometrical way. It is a necessary facility in C-ITS to share sensor information between participating traffic agents. Moreover, it maintains information about the objects that are either part of the traffic or influenced by it. The International Organization for Standardization （ISO） and European Telecommunications Standards Institute （ETSI） have also made standardization efforts. Since its inception in the SAFESPOT project, implementations of LDM have been mostly four-layer data organizations. Where Layer 1 and Layer 2 maintain static information and transient static information. Then, Layer 3 and Layer 4 contain transient dynamic and highly dynamic data. Depending upon the requirement, the LDM community realized memory-based or database-based LDM. We utilized the decision diagram to enhance the safety aspect of the traffic participants in the memory/ database-based LDM setup. We utilized Shared Binary Decision Diagram （SBDD） and Geohash granular properties to detect the near-miss situation, i.e. when vehicles come very close. However, besides DynaMap, there is also a common understanding since the SAFESPOT project introduced LDM to use the database and supported query language to retrieve data from the LDM. Hence, most implementations use different databases and query languages to execute it. Although, the LDM community has explored LDM depending on the database variants. Nevertheless, remarkably less emphasis has been given to the type of data stored in the LDM. This thesis attempted to fill this gap in the LDM to enhance the moving vehicle’s safety aspect. We proposed a novel method of data representation for vehicle future geographical occupancy information using a binary decision diagram （BDD）. We show that sharing BDD-based information is consistent with the C-ITS nature of the data sharing since the algebraic operation between the exchanged BDDs can confirm the possibility of future interaction. We calculated potential future occupancy using Kamm’s circle, shown in the ROS-based simulator and modified the mid-point circle generation algorithm to find the BDD representing the set of Geohash enclosing the Kamm’s circle. We also reported data insertion and collision avoidance check time of the linked list-based BDD on PostgreSQL database-based LDM. | |||||||
| 言語 | en | |||||||
| 目次 | ||||||||
| 内容記述タイプ | TableOfContents | |||||||
| 内容記述 | 1 Introduction||2 Literature Review||3 Methodology||4 Results||5 Discussion||6 Summary | |||||||
| 備考 | ||||||||
| 内容記述タイプ | Other | |||||||
| 内容記述 | 九州工業大学博士学位論文 学位記番号：生工博甲第449号 学位授与年月日：令和4年9月26日 | |||||||
| キーワード | ||||||||
| 主題Scheme | Other | |||||||
| 主題 | Local Dynamic Map | |||||||
| キーワード | ||||||||
| 主題Scheme | Other | |||||||
| 主題 | Binary Decision Diagram | |||||||
| キーワード | ||||||||
| 主題Scheme | Other | |||||||
| 主題 | Geohash | |||||||
| キーワード | ||||||||
| 主題Scheme | Other | |||||||
| 主題 | Automated Driving | |||||||
| キーワード | ||||||||
| 主題Scheme | Other | |||||||
| 主題 | Collision Avoidance | |||||||
| キーワード | ||||||||
| 主題Scheme | Other | |||||||
| 主題 | Kamm’s Circle | |||||||
| アドバイザー | ||||||||
| 我妻, 広明 | ||||||||
| 学位授与番号 | ||||||||
| 学位授与番号 | 甲第449号 | |||||||
| 学位名 | ||||||||
| 学位名 | 博士（工学） | |||||||
| 学位授与年月日 | ||||||||
| 学位授与年月日 | 2022-09-26 | |||||||
| 学位授与機関 | ||||||||
| 学位授与機関識別子Scheme | kakenhi | |||||||
| 学位授与機関識別子 | 17104 | |||||||
| 学位授与機関名 | 九州工業大学 | |||||||
| 学位授与年度 | ||||||||
| 内容記述タイプ | Other | |||||||
| 内容記述 | 令和4年度 | |||||||
| 出版タイプ | ||||||||
| 出版タイプ | VoR | |||||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||||
| アクセス権 | ||||||||
| アクセス権 | open access | |||||||
| アクセス権URI | http://purl.org/coar/access_right/c_abf2 | |||||||
| ID登録 | ||||||||
| ID登録 | 10.18997/00009023 | |||||||
| ID登録タイプ | JaLC | |||||||
