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Title: | 利用車聯網通訊進階分析高速公路交通狀況及非預期塞車現象 Advanced Analysis of Highway Traffic and Inexplicable Traffic Congestion Phenomenon using V2X Communication |
Authors: | 邱淑玲 Chiu, Shu-Ling |
Contributors: | 蔡子傑 Tsai, Tzu-Chieh 邱淑玲 Chiu, Shu-Ling |
Keywords: | 車聯網 智慧交通 塞車 慢速車 HERMES V2X ITS Traffic Jams Slow-Moving Vehicles |
Date: | 2020 |
Issue Date: | 2020-09-02 13:14:45 (UTC+8) |
Abstract: | 多數高速公路駕駛人都有遇過在天氣晴朗、車流量不多的情況下,忽然塞車,在沒任何原因下,交通忽然又恢復順暢。這類莫名的塞車現象大部份是由於駕駛行為而造成的,「慢速車」長期佔用車道,導致後方車輛堵塞,不僅增加塞車風險,也因為會迫使後方車輛變換車道,甚至煞車不及而造成追撞,增加事故風險,影響高速公路行車安全。雖然這屬於交通違規,但判斷上需要考慮多項條件,若無清楚資料,違規駕駛人常有爭議,而造成取締困難,至今仍然缺乏有效方法改善。目前有許多關於交通管理及路況分析的研究,但還沒有有效偵測車輛超速、慢速違規,甚至偵測慢速車相關的研究。
本篇論文提出一個新的方法,應用車聯網通訊技術(Vehicle-to-Everything, V2X)進行進階的高速公路交通狀況分析,包括:路況分析、慢速車輛偵測、速限違規車輛偵測,車聯網通訊是智能交通系統(ITS)的關鍵技術,因為目前硬體環境限制、基礎設施限制及交通安全問題,無法進行路上實測,本篇論文實作一個模擬高速公路交通管理及改善系統(Highway Efficient tRaffic Management and Enhancement System, HERMES),利用車聯網概念,實現車與車、車與路側設施之間的相互通信模擬,並利用車聯網傳遞獲得的資料進行分析,觀察車流量、傳送頻率、分析頻率對路況、慢速車數量、偵測延遲時間的影響,本篇論文的實驗結果展示了應用V2X通訊技術概念的可行性及能力。 The phenomenon that slow-moving vehicles occupy the lanes when the traffic is not so heavy, is considered as one of the crucial factors contributing to inexplicable traffic jam. It has a negative impact on traffic safety and increases the chance of accidents. It may force the cars behind to change lanes or cause rear-end collisions if cars behind fail to notice the speed. While this phenomenon occurs, it is not easy to detect whether it is a traffic violation because multiple criteria have to be fulfilled. There are many kinds of researches on traffic management or analysis. However, there is no research on the effective detection of speed violations or detection of slow-moving vehicles.
In this thesis, we propose a new application based on Vehicle-to-everything (V2X) communication concept and implement a Highway Efficient tRaffic Management and Enhancement System (HERMES) for simulation and analysis. V2X communication is developed for enabling autonomous driving and enhancing road safety, traffic efficiency, and energy savings. It incorporates various types of communication as V2I (vehicle-to-infrastructure), V2N (vehicle-to-network), V2V (vehicle-to-vehicle), and V2P (vehicle-to-pedestrian). We analyze the real-time vehicle data obtained by V2V and V2I for traffic status detection, suspected blockers detection, and speed violators detection to solve the potential traffic jam problem. We observe the impacts of the number of vehicles, transmission frequency, analysis frequency on traffic, suspected blocker, accuracy rate, and detection delay from several experiments. The results exhibit the feasibility and capability of the methodology. |
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Description: | 碩士 國立政治大學 資訊科學系碩士在職專班 102971003 |
Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0102971003 |
Data Type: | thesis |
DOI: | 10.6814/NCCU202001596 |
Appears in Collections: | [資訊科學系碩士在職專班] 學位論文
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