道路環境和車輛因素對自行車騎乘行為影響之研究;The Impact of Road Environment and Vehicle on the Riding Behavior of Bikers

NCUIR > Engineering College > Graduate Institute of Mechanical Engineering > Electronic Thesis & Dissertation > Item 987654321/65934

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/65934

Title:	道路環境和車輛因素對自行車騎乘行為影響之研究;The Impact of Road Environment and Vehicle on the Riding Behavior of Bikers
Authors:	莊凱翔;Chuang,Kai-hsiang
Contributors:	機械工程學系
Keywords:	自行車騎士;行為觀察;自然騎乘行為;Bicyclist;Behavior observation;Naturalistic riding
Date:	2014-07-18
Issue Date:	2014-10-15 17:18:30 (UTC+8)
Publisher:	國立中央大學
Abstract:	世界衛生組織調查全球75%國家的交通事故情形發現，各國交通事故中有自行車騎士死亡的比例約占總事故死亡人數的2至19%，自行車騎士於騎乘環境中所面對的道路風險已成為阻礙提升人民騎乘自行車使用率來達到節能減碳的最大原因之一。因此，了解自行車騎士騎乘時之風險因素來降低事故發生的比例成為很重要的研究課題。本研究利用機電整合技術開成功發自行車的儀器車輛，透過行車影像紀錄器、加速規、超音波測距儀、近接開關和可變電阻紀錄騎士在騎乘時的行為資料，並規劃騎乘路線，收集40位騎士的實際騎乘行為資料來進行分析。利用資料庫技術及.NET程式對大量實驗數據進行處理和資料減縮，發展出一套大量自然觀察資料的解析方法，篩選出具有進一步觀察價值之潛在事件，以縮減人工影像觀察的工作量，提高影像資料觀察註記的效率，並於影像資料中篩選出有觀察價值的事件，例如本研究中所分析之「機動車輛通過自行車事件」案例進行分析，進而了解自行車騎士在不同事件所受到的外在因素影響情形。研究中以「機動車輛通過自行車事件」為案例，利用變異數分析、t檢定、主成分分析等統計方法，了解道路環境和機動車輛的類型差異下，例如不同車道類型、車道數、大小客車差異對騎士實驗過程中的騎乘空間的影響，經過資料統計後皆有顯著性的差異存在，藉此可了解外在因素環境對自行車騎士行為的影響情形，同時亦揭示本研究開發之儀器自行車所能分析之騎士與機動車輛互動行為的潛力。 ;World Health Organization data have indicated that in 75% of countries worldwide, bicyclists accounted for 2–19% of crash deaths. This crash risk may hamper efforts to increase bicycle usage and take advantage of its low carbon emissions. Therefore, understanding the risks associated with bicyclists′ use of roads will likely reduce crashes and may facilitate the use of bicycles. This research fitted the sensor and device inclouding one global positioning system, 3-axis accelerometer, two ultrasonic distance sensors, eight proximity switches, one variable resistor, and five car camera DVR black boxes into an urban-style bicycle. Then, Using this bicycle to collect 40 bicyclists′ riding behavior data. In order to observe the valuable data from the great amount of row data, we established the data processing method to reduce the data and filter out the worthless data. Throught the data reduction method to find the valuable data, we investigated vehicle-related factors, road-related factors, and bicyclist-related factors influenced motorists′ decisions about initial passing distances and bicyclists′ behaviors after the motorists started to pass. We found that many facotrs including road factor, bicylists′ gender difference and passing vehicles affected the motorists′ initial passing distance. The present study demonstrated that the quasi-naturalistic riding method is capable of collecting rich data concerning bicyclists′ behaviors, which could potentially be utilized in various types of studies.
Appears in Collections:	[Graduate Institute of Mechanical Engineering] Electronic Thesis & Dissertation

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