簡易檢索 / 詳目顯示

研究生: 吳峻廷
Wu, Chun-Ting
論文名稱: 基於自駕車模擬環境之智慧路側設備與車端通訊軟體平台:​以路口防碰撞警示應用為例​
A Carla-Based Software Platform for Vehicle-To-Everything Application Development: ​A Case Study on the Intersection Movement Assist Application​
指導教授: 涂嘉恒
Tu, Chia-Heng
學位類別: 碩士
Master
系所名稱: 電機資訊學院 - 資訊工程學系
Department of Computer Science and Information Engineering
論文出版年: 2023
畢業學年度: 111
語文別: 英文
論文頁數: 35
中文關鍵詞: 智能交通系統 、路口移動輔助應用 、模擬器
外文關鍵詞: Intelligent Transportation System, Intersection Movement Assist Application, Simulation
相關次數: 點閱:128  下載:0 
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • 隨著科技的進步,智能交通系統(ITS) 正在在迅速擴展和發展。ITS 已成為現代交通中越來越重要的組成部分,為個人和社會提供更高的安全性、效率和可持續性。隨著各廠商對ITS 的快速採用和產品系統原型的不斷完善,該領域取得了重大進展。然而,由於這些產品並非適用於每個地區或國家的限制,系統設計仍然存在重大挑戰。由於各種因素,開發ITS 系統需要與不同地方合作,因此很難為每個國家提出固定的解決方案。因此,我們提出了一個可以在模擬器中測試的ITS 框架,以提高交通安全並促進開發,利用現有的自動駕駛汽車模擬器框架進行開發,同時滿足汽車工程師協會定義的性能規範。我們知道聯網車輛可以使用路邊單元檢測非聯網車輛,進一步提高道路交通安全。我們將使用交叉路口移動輔助應用程序作為示例來測試我們提出的框架。

    As technology advances, the Intelligent Transportation System (ITS) is rapidly expanding and evolving. ITS has become an increasingly crucial component in modern transportation, offering improved safety, efficiency, and sustainability for both individuals and society[10]. With the quick adoption of ITS by various manufacturers and continuous improvement of their product’s system prototypes, significant progress has been made in the field. However, there are still significant challenges in system design due to limitations that may not be applicable in every region or country. Developing ITS systems requires collaboration with different countries due to various factors that make it difficult to propose a fixed solution for every country. Therefore, we propose an ITS framework that can be tested in simulation to improve traffic safety and facilitate development. This framework utilizes the existing framework of autonomous vehicle simulators for development purposes while meeting the performance specifications defined by the Society of Automotive Engineers. We are aware that connected vehicles can use roadside units to detect disconnected vehicles, further improving road traffic safety. We will use the Intersection Movement Assist Application as an example to test our proposed framework. Through this ITS framework, we aim to optimize traffic safety and facilitate the development of ITS in a simulation environment, while meeting the unique requirements of different countries and regions. This will provide us with a more reliable and scalable solution to address the increasingly complex traffic challenges.

    摘要 i Abstract ii 誌謝 iii Table of Contents iv List of Tables v List of Figures vi Chapter 1. Introduction 1 Chapter 2. Background and Related Work 5 2.1. Vehicle to Everything Standards and Applications 5 2.2. Improving Road Safety through Vehicle-Centric Approaches 7 2.3. Simulator for Self-driving and ITS Application 8 2.3.1. Simulation of Urban MObility 8 2.3.2. OpenCDA 9 2.3.3. Carla Simulator 10 2.3.4. Autoware 11 Chapter 3. Method 13 3.1. Overview 13 3.2. Framework Architecture 15 3.2.1. Vehicle Simulation with CARLA 18 3.2.2. Communications 19 3.2.3. Self-Driving Sensing 21 Chapter 4. EXPERIMENTAL RESULTS 23 4.1. Target Case 23 4.2. Environmental Setup 24 4.3. List of Experiments 26 4.3.1. Functional Validation 26 4.3.2. Cost Efficient RSU HW Designs over CPS Implementations 26 4.4. Functional Validation in Autoware 27 4.5. Cost Efficient RSU HW Designs over CPS Implementations 28 Chapter 5. Conclusion 33 References 34

    [1] Khadige Abboud, Hassan Aboubakr Omar, and Weihua Zhuang. Interworking of dsrc and cellular network technologies for v2x communications: A survey. IEEE Transactions on Vehicular Technology, 65(12):9457–9470, 2016.
    [2] CARLA. Carla website, 2020.
    [3] George Dimitrakopoulos and Panagiotis Demestichas. Intelligent transportation systems. IEEE Vehicular Technology Magazine, 5(1):77–84, 2010.
    [4] ETSI EN 302 637-2 V1.3.2 (2014-11). Intelligent transport systems (its); vehicular communications; basic set of applications; part 2: Specification of cooperative awareness basic service, December 2014.
    [5] Shinpei Kato, Eijiro Takeuchi, Yoshio Ishiguro, Yoshiki Ninomiya, Kazuya Takeda, and Tsuyoshi Hamada. An open approach to autonomous vehicles. 35:60–68, December 2015.
    [6] John B. Kenney. Dedicated short-range communications (dsrc) standards in the united states. Proceedings of the IEEE, 99(7):1162–1182, 2011.
    [7] Kernel.org. perf: Linux profiling with performance counters, October 2019.
    [8] Wei-Hsun Lee and Chi-Yi Chiu. Design and implementation of a smart traffic signal control system for smart city applications. Sensors, 20(2), 2020.
    [9] Pablo Alvarez Lopez, Michael Behrisch, Laura Bieker-Walz, Jakob Erdmann, Yun-
    Pang Flötteröd, Robert Hilbrich, Leonhard Lücken, Johannes Rummel, Peter Wagner, and Evamarie Wießner. Microscopic traffic simulation using sumo. In The 21st IEEE International Conference on Intelligent Transportation Systems. IEEE, 2018.
    [10] Ehsan Moradi-Pari, Danyang Tian, Hossein Nourkhiz Mahjoub, and Sue Bai. The smart intersection: A solution to early-stage vehicle-to-everything deployment. IEEE Intelligent Transportation Systems Magazine, pages 2–17, 2021.
    [11] Morgan Quigley, Brian Gerkey, Ken Conley, Josh Faust, Tully Foote, Jeremy Leibs, Eric Berger, Rob Wheeler, and Andrew Ng. Ros: an open-source robot operating system. In ICRA, page 5, May 2009.
    [12] SAE J2735. V2X Communications Message Set Dictionary, July 2020.
    [13] SAE J2945/1. On-Board System Requirements for V2V Safety Communications, April 2020.
    [14] Hyun-Soo Seo, Dong-Gyu Noh, Chang-Jin Lee, and Sang-Sun Lee. Design and implementation of intersection movement assistant applications using v2v communications. In 2013 Fifth International Conference on Ubiquitous and Future Networks (ICUFN), pages 49–50, 2013.
    [15] Chih-Han Su. Design and implementation of roadside unit middleware for intelligent transportation system applications, 10 2021.
    [16] Lijun Wei, Cindy Cappelle, and Yassine Ruichek. Camera/laser/gps fusion method for vehicle positioning under extended nis-based sensor validation. 62:3110–3122, November 2013.
    [17] Runsheng Xu, Yi Guo, Xu Han, Xin Xia, Hao Xiang, and Jiaqi Ma. Opencda:an open cooperative driving automation framework integrated with co-simulation. In 2021 IEEE Intelligent Transportation Systems Conference (ITSC). IEEE, 2021.

    下載圖示
    2026-07-24公開
    QR CODE