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  • 學位論文

應用移動式偵測器執行考量旅客消費影響之號誌控制研究

A Study of Applying Mobile Detector on Traffic Signal Control Which Considering Travelers consumption Impact

指導教授 : 張堂賢
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摘要


隨著科技的進步,網際網路以及無線通訊技術的提升使得資訊的傳輸門檻大幅降低。同一時間硬體設施也在技術的進步下越來越精良,如今,智慧型行動裝置已經成為人手一台的基本配備,其所具備的功能也不再侷限在通訊而已,近年來物聯網 (Internet of Things,IOT) 的崛起讓人、車、路的溝通不再困難;智慧型個人裝置的強大功能讓偵測、資料蒐集以及資料傳輸的困難度大幅降低,配合大量的使用族群,彷彿建立了一個現成的資料蒐集平台。在此平台下僅需要花費少量的成本即可蒐集各式所需的資訊以供使用,在資料科學 (Data Science) 發展快速的現今,利用各式各樣的資料進行分析與預測對於使用者及管理單位都有非常大的助益。 除了科技上的進步與改變,想法上的改變也正在影響整個社會,交通運輸也從以車為本漸漸轉變成以人為本,同時環保、永續等議題亦同時影響的交通運輸的發展;拜科技發展之賜,現今偵測技術及通訊技術的進步使得資料蒐集的方法及類型越來越多元,傳統的號誌控制是建立在以車為本的狀態下蒐集特定資料進行演算;利用不同型態的資料在以人為本的號誌控制則沒有太多相關研究。因此本研究將利用移動式車輛偵測器進行旅客消費資料蒐集,並利用蒐集而來的消費資料配合傳統的號誌演算法得到新的號誌控制模式,在結果方面除了傳統的停等延滯外,同時考慮旅客消費對地方所帶來的經濟效益以及行車所造成的碳排放所造成的負面效果。研究成果將可作為日後以不同形態資料進行號誌演算之參考,對未來第五代的交通運輸觀念能有所貢獻。

並列摘要


With the rapid development of technology, Internet and wireless communication technology have been widely accessible to the general public. Concurrently, the sophistication of hardware facilities is significantly increased. Nowadays, smart mobile devices have become the necessity for people and are not limited for communication use merely. In recent years, the rise of the Internet of Things (IOT) facilitates the integration of communication, control, and information processing across various transportation systems. Applications of the IOT have been extended to broad aspects of transportation system management, which addresses the communications between road users, vehicles, and infrastructures. Flexible and real-time interaction between the components of a transportation system enables inter/intra vehicular communication, smart traffic control, dynamic data acquisition, road assistance, etc. Smart mobile devices are so powerful that have greatly lowered the barrier and cost for traffic detection, thereby making it possible to establish a data collection platform in a short time. The progress in communication science and technology also shifts the way of thinking of the whole society, leading a trend of transportation development from a vehicle-based context to a human-based one. Traditional traffic control is built largely based on vehicle-oriented considerations and operated by using the associated data. Hence, this study seeks to use smart mobile devices as detectors to collect a new type of traffic data, such as passenger/consumer information and to develop an adaptive control algorithm thereupon, where both delay and carbon emission are considered.

參考文獻


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