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  • 學位論文

在SUMO環境下建立宏觀車流理論之交通行動服務自駕車控制策略模擬模型

Two-Dimensional Network Simulation in SUMO for MFD-Based Operation Model of Autonomous Vehicle Mobility Service

指導教授 : 坂井勝哉

摘要


近年來,智慧運輸系統(ITS)變得越來越流行。世界各地的國家都在嘗試制定與ITS相關的政策和基礎架構。 智慧運輸系統中包含許多主題,例如,公共交通系統集成,智慧號誌系統和移動即服務(MaaS)等。實際上,它是交通系統的新概念。總而言之,智慧運輸系統是一個概念,每個運具都能夠與其他交通運具非常快速的聯繫,代表車輛或其他交通運具會上傳其當前訊息及車輛概況,並下載其他運具的資訊。如此高頻率的訊息交換,亦是5G發展的另一個主要原因。車輛可以透過互連技術相互連接,其中一項技術為自動駕駛技術。本文將開發一自動車營運系統控制策略的模擬模型。 該控制策略主要參考Kusakabe(2020)該篇論文的控制策略。該策略試圖通過動態控制共享自動駕駛系統的服務車隊規模來最大程度地減少乘客的總旅行時間,這意味著服務車隊規模是隨時間變化的。另外,根據宏觀車流理論基本圖(Daganzo,2007),可以得知系統中的車輛數和車輛平均速度的關係圖為負相關性。 本文將重新開發動態控制策略,並架構事件導向的模擬邏輯。事件導向的邏輯是由各個旅行事件組成:候車事件,乘客上車事件,乘客下車事件等。為了驗證該控制策略是否有用以及模擬模型是否正確,本文將在一維路網中測試,並在模擬軟體SUMO中定義一個更實際的二維模擬,以確保動態控制策略在更現實的路網中可行。

並列摘要


In recent years, intelligent transportation system (ITS) becomes more and more popular. Countries all over the world are trying to develop the policies and infrastructure related to ITS. There are many topics included in ITS, for example, public transportation system integration, smart signaling system, and mobility as a service, etc. Actually, it is a new concept of transportation system. In a small conclusion, ITS is a concept that every modal has a strong connection to others, which means vehicles or other modals upload their current information and download others very frequently. This is the reason why 5G is also another popular issue. Vehicles can connect to each other with the interconnecting technology, one of which is known as the auto-pilot technology. This paper focus on developing a simulation model with an operation strategy for the autonomous vehicles. The operation strategy is mainly referred from Kusakabe (2020). This strategy tries to minimize the total travel time for passengers by controlling the serving fleet size of a sharing autonomous vehicle system dynamically, which means the service fleet size is time variable. In addition, based on the macroscopic fundamental diagram (Daganzo, 2007), it can be seen that more vehicles in the system causes low speed of vehicles. This paper will re-develop the dynamic operation model and construct an event-based simulation logic. Those events are the traveling events: waiting for vehicles, picked up by vehicles, dropped off by the vehicles, etc. To validate that the operation strategy is useful and the simulation model is correct, this paper will run a simplified one-dimensional simulation case. Then, this paper will define a two-dimensional simulation in SUMO environment, which is more practical to make sure the dynamic operation strategy is workable in more realistic network.

參考文獻


Bruce D. Greenshields, Henry P. George, Neil S. Guerin, M. Ross Palmer Robin T. Underwood (1961). Quality and Theory of Traffic Flow.
Carlos F. Daganzo (2007). Urban gridlock: Macroscopic modeling and mitigation approaches. Transportation Research Part B 41 (2007) 49–62
Chinese Engineering Consultant Inc. (2016) Research of Macroscopic Traffic Flow Model. Annual Research Report (2016)
Erik Jenelius, Ida Kristoffersson Magnus Fransson (2017). Validation of Traffic Simulation Models Based on the Macroscopic Fundamental Diagram. Transportation Research Procedia 27 (2017) 561–568
Kara M. Kockelman (2014). The Travel and Environmental Implications of Shared Autonomous Vehicles, Using Agent-Based Model Scenarios. Transportation Research Part C, Vol 40 (2014): 1-13

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