機車在號誌化路口混合車流中之疏解特性研究

Abstract

機車在進入一般號誌化交叉路口之臨進路段時，駕駛者就需要衡量自身加、減速與改變位移方向，而由於路口中無明確行車方向規定，機車本身又擁有高度的機動性，加上駕駛人尋找最短路徑的傾向，使得機車成為路口及其臨進路段上秩序混亂的來源；解決之道應以疏導車流順利通過路口為主，為求機車疏解研究之完整，本研究對機車車隊疏解特性進行分析，探討疏解率並建構模式，根據模式結果與變數之影響，推論機車成為路口亂象的原因，以提出改善建議。 本研究進行錄影調查、模式建構、比較各變數與各模式之結果，確認機車在綠燈始亮後2~4秒間，疏解率會升至一高峰值；之後下降直到綠燈亮後20~40秒，從上游放行的機車到達使疏解率稍微上升，至綠燈時相結束止；從每二秒疏解率圖形上亦可區分出此三段。 本研究對機車車隊進行疏解率模式之建構，並將車隊分為前後段，二路口最終共得到模式3式，包括機車車隊前段疏解率、信義復興後段疏解率、忠孝復興後段疏解率，可用以預測與本研究調查現場類似的路口機車車隊疏解率；本研究對各變數做進一步應用之分析，並認為對忠孝復興現場尖峰時段的機車疏解效率的改善，以加強管制、防止違規穿越為最優先。

Riders have to mention the acceleration, deceleration and changes of the displacement directions of themselves when they enter the approach of general signalized intersections. Because there is no exact rule of moving direction on the middle of intersection, and the high mobility of motorcycles, and riders usually try to find the shortest path, motorcycles become the cause of the disorder on the intersections and approaches. The basic solution of this problem is to dredge the flow of motorcycles across the intersection smoothly. In this study, we proceed to analyze the departure characteristics of the motorcycles and derive the departure rate of motorcycles and its model, then discuss the reason why motorcycles become the cause of disorders on the intersections from the outcome of the model and the effect of factors, and bring up the suggestion of improvement. In this study, we proceed to video investigation, models construction, and the outcome of variables and models comparison. We confirm that the departure rate of motorcycles would rise to the top from 2 to 4 seconds after the beginning of green light. After that, it would fall down until 20 to 40 seconds after the beginning of green. When the motorcycles upstream arrive, the departure rate would rise a little until the green light ends. We can also separate the three parts from the 2-second departure rate figures. We proceed to construct the departure rate model and separate the queue of motorcycle to two parts—front-queue and back-queue. There are three final models at both intersections, including the motorcycle departure rate model of front-queue, the model of back-queue at SinYi - FuSing intersection, and the model of back-queue at ZhongSiao - Fusing intersection. Those can be useful to predict the motorcycle queue departure rate at similar intersections. We continue to analyze the application of effective factors. And consider that management enhancing and preventing drivers against traffic regulations in crossing are the first thing we should do to improve the traffic at rush hours on Zhong - Siao intersection.