交通大數據分析以公車動態資料為例
| dc.contributor | 周學政 | zh_TW |
| dc.contributor | Chou, Hsueh-Cheng | en_US |
| dc.contributor.author | 蔡承晏 | zh_TW |
| dc.contributor.author | Cai, Cheng-Yan | en_US |
| dc.date.accessioned | 2023-12-08T07:42:43Z | |
| dc.date.available | 2022-08-23 | |
| dc.date.available | 2023-12-08T07:42:43Z | |
| dc.date.issued | 2022 | |
| dc.description.abstract | 一般大眾運輸動態饋給規格(General Transit Feed Specification，GTFS)制定了各類型的大眾交通運輸數據的資料格式，內容包含：停靠的站點、營運的路徑、行進的順序以及時刻表等資訊，透過統一的格式，使資料能夠互通使用。國內也有公共運輸整合資訊流通服務平臺(Public Transport Data eXchange，PTX)，與其他運輸平台，共同建立格式統一、標準化之資料模型包括：航空、鐵路、公車、自行車等項目，累積了大量的交通運輸資料。然而，目前對於公車動態資料的相關研究甚少。本研究以供給層面探討大眾運輸系統的可及性現況，並利用軌道運輸及公車運輸具有固定的停靠點、行駛路線以及班次之特性，由公車動態資料拓展至大眾交通運輸資料建立以及分析系統開發，設計一套可供交通可及性分析資料架構，經過本研究所建立之清洗流程進行處理，建立交通資料庫，開發可及性及視覺化模組，應用於快速且自動化進行公共運輸系統的交通可及性評估。在案例分析的部分，本研究利用臺北市市區公車動態車機資料，並透過交通可及性分析系統進行分析。研究結果顯示，在旅行時間30分鐘之內，以臺北火車站周遭的區域交通可及性最佳，從臺北市整體來看，可及性呈現西高東低的現象，並且於納入臺北捷運系統後，大多的分區可及性皆有所提升，尤其原先市區外圍可及性較差的區域，若鄰近捷運站，其可及性有明顯地改善。 | zh_TW |
| dc.description.abstract | The General Transit Feed Specification (GTFS) defines the data format of various types of public transportation data, including stops, operating routes, travel sequences, and timetables. A unified design enables data to be used interchangeably. There is also a public transport integrated information circulation service platform (Public Transport Data eXchange, PTX) in Taiwan. Together with other transport platforms, they establish a unified and standardized data model including aviation, railway, bus, bicycle and other projects, accumulating a large amount of traffic data. However, there are few related studies on dynamic bus system data.This study explores the accessibility status of mass transit systems from the supply aspect, utilizes the characteristics of rail transit and bus transport with fixed stops, travel routes and schedules, and extends from dynamic bus data to the establishment of mass transit data and analysis system development , design a set of the data structure for traffic accessibility analysis, process it through the cleaning process established by this research, build a traffic database, develop accessibility and visualization modules, and apply it to the rapid, automated public transportation system accessibility assessment.In the example of this implementation case, the traffic accessibility analysis system is used for analysis by using the dynamic bus system data of the city bus in Taipei. The research results show that within 30 minutes of travel time, the area around Taipei Station has the best traffic accessibility. In Taipei, accessibility is higher in the west and lower in the east. After incorporating the Taipei MRT, accessibility has improved in most districts, especially in areas with poorer accessibility outside the urbanarea, which have significantly improved if they are close to Metro stations. | en_US |
| dc.description.sponsorship | 地理學系 | zh_TW |
| dc.identifier | 60723015L-42037 | |
| dc.identifier.uri | https://etds.lib.ntnu.edu.tw/thesis/detail/55541e5eca6ad256b6d7fa49e0f7b130/ | |
| dc.identifier.uri | http://rportal.lib.ntnu.edu.tw/handle/20.500.12235/119928 | |
| dc.language | 中文 | |
| dc.subject | 市區公車 | zh_TW |
| dc.subject | 地理資訊系統 | zh_TW |
| dc.subject | 公車動態資料 | zh_TW |
| dc.subject | 可及性 | zh_TW |
| dc.subject | City Bus | en_US |
| dc.subject | GIS | en_US |
| dc.subject | Dynamic Bus System Data | en_US |
| dc.subject | Accessibility | en_US |
| dc.title | 交通大數據分析以公車動態資料為例 | zh_TW |
| dc.title | Traffic Big Data Analysis – Take Dynamic Bus System Data as an Example | en_US |
| dc.type | etd |
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