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研究生:廖晉毅
研究生(外文):Liao, Chin-Yi
論文名稱:高速公路入口匝道匯流區之隨機容量分析
論文名稱(外文):A Stochastic Capacity Analysis in Freeway Merge Areas
指導教授:黃家耀黃家耀引用關係
指導教授(外文):Wong, Ka Io
口試委員:黃家耀胡守任邱裕鈞
口試委員(外文):Wong, Ka IoHu, Shou-RenChiou, Yu-Chiun
口試日期:2020-07-29
學位類別:碩士
校院名稱:國立交通大學
系所名稱:運輸與物流管理學系
學門:運輸服務學門
學類:運輸管理學類
論文種類:學術論文
論文出版年:2020
畢業學年度:108
語文別:中文
論文頁數:37
中文關鍵詞:高速公路匯流影響區車流崩潰隨機容量韋伯分布
外文關鍵詞:FreewayMerge influence areaTraffic breakdownStochastic capacityWeibull distribution
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  • 被引用被引用:2
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高速公路之車流運行狀況,常因入口匝道匯入主線時,會有許多的車道變換行為發生,進而導致入口匯流區經常為高速公路上發生壅塞之交通瓶頸區,其通過流率之最大值可視為該設施之容量。傳統的分析方法將容量訂定為一固定值,然而,近年歐美國家有不少的研究指出,若以一天交通壅塞發生前之最大通過流率做為容量值,每天的容量值都會稍有不同並具有隨機性,可稱為隨機容量(stochastic capacity)。
本研究探討幾何型態或外在環境等因素對於高速公路匯流區容量之影響,而因容量具有隨機性,應採用隨機容量的分析方法。本研究運用臺灣高速公路國道1號及國道3號之偵測器資料進行分析,考慮的影響因素包括壅塞時段、天氣、主線速限、主線車道數、開放路肩、入口匝道流率,並透過韋伯分布之參數校估,進而比對在不同情境下容量之隨機分布,得出各種情境下之容量參考值。研究發現在平日早上、平日下午、假日之容量有明顯差異,推測通勤旅次為主的時段容量較大、休閒旅次為主的時間容量較小,而三個時段的容量值的大小順序會隨地點而有所不同。以主線三車道的匯流區而言,雨天的容量比晴天的容量低 250 車輛/小時;開放路肩之能使匯流區的容量提高 700 ~1,000 車輛/小時;當進口匝道流率越高,在三車道匯流區之容量值會越高;在匯流區上游總流率固定之情形,當匝道流率越高,其車流崩潰機率也會越高。另外,研究中也有發現與直觀不符的結論,包括主線速限對於容量值無顯著影響,主線四車道匯流區之車道容量值比主線三車道多出 150 車輛/小時/車道,可能是符合分析條件地點的可用資料有限,比較分析尚不夠全面所導致。本研究結果將能夠得出各種情境下之容量參考值,可供政府單位於匯流區在管制上作為容量參考依據,使高速公路於匯流區之運作更有效率。
The bottleneck of a freeway usually happens at the on-ramp merge areas when the incoming flows from the upstream and on ramp exceeds the capacity of the ramp merge area. The maximum flow rate that can pass through a facility can be seen as the capacity of the facility. The traditional analysis sets the capacity as a fixed value. However, recent studies found that such maximum flow rates observed in each day could be quite different, subject to stochasticity, instead of a deterministic value. This is known as the stochastic capacity in traffic flow. This study investigates the stochastic capacity of the ramp merge areas of the freeway system. The aim is to find out the effects of geometric and external environments on the capacity of merging areas. We analyze the maximum pre-breakdown flow rates for the probability functions of traffic breakdown using Product Limit Method and Weibull distribution method. Using the vehicle detector data of National Freeway No. 1 and No. 3, we explore the effects of congestion periods, raining, shoulder lane opening, and on-ramp flow rate on the capacity. It is found that the capacity is significantly different in the weekday mornings, weekday afternoons, and holidays, and the order of the capacity values of the three time-periods varies by locations. The capacity during rainy days is lower than the capacity on sunny days by 250 veh/hr at three-lane sites. Opening shoulder lane can increase the capacity by 700 ~1,000 veh/hr. When the on-ramp flow rate is higher, the capacity value will be higher. Higher the ramp flows result in a higher traffic breakdown probability. The results of this study will be able to obtain capacity values in various scenarios in addition to the geometric parameters, which can be used as a reference by the freeway traffic operators in evaluating their traffic control and operation strategies for the freeway ramp merge areas.
第一章 緒論 1
1.1 研究背景 1
1.2 研究目的 2
1.3 研究範圍及分析對象 2
1.4 研究架構 3
第二章 文獻回顧 5
2.1 容量隨機性分析 5
2.2 車流崩潰之定義 6
2.3 匝道匯流區容量的影響因素 6
2.4 文獻回顧重點與研究缺口 7
第三章 研究方法 9
3.1 車流崩潰之判斷 9
3.2 容量隨機性分布 12
第四章 數值分析 13
4.1 調查地點選定 13
4.2 容量隨機性分布 16
4.3 外在因素對容量隨機性分布之影響 22
第五章 結論與建議 33
5.1 結論 33
5.2 後續研究之建議 34
參考文獻 36
交通部運輸研究所(2011),2011年臺灣公路容量手冊。
交通部運輸研究所(2018),高速公路匝道分匯流區車流特性調查之先期規劃。
歐陽恬恬、林豐博、曾平毅、蘇振維(2016),「高速公路主線及匝道匯流區車流特性之研究」,交通學報,第16卷第1期,頁19-38。
Asgharzadeh, M., & Kondyli, A. (2020), “Effect of Geometry and Control on the Probability of Breakdown and Capacity at Freeway Merges,” Journal of Transportation Engineering, Part A: Systems, Vol. 146, No. 7, 04020055.
Brilon, W., Geistefeldt, J., & Regler, M. (2005), “Reliability of freeway traffic flow: a stochastic concept of capacity,” Proceedings of the 16th International Symposium on Transportation and Traffic Theory, Vol. 125143, Maryland: College Park.
Chung, K., Rudjanakanoknad, J., & Cassidy, M. J. (2007), “Relation between traffic density and capacity drop at three freeway bottlenecks,” Transportation Research Part B: Methodological, Vol. 41, No. 1, pp. 82-95.
Dehman, A., & Drakopoulos, A. (2016), “Revisiting Merge-Influence Area Empirically: Operations Inside Recurrent Freeway Bottlenecks,” Transportation Research Record, Vol. 2553, No. 1, pp. 52-62.
Elefteriadou, L., Roess, R. P., & McShane, W. R. (1995), “Probabilistic nature of breakdown at freeway merge junctions,” Transportation Research Record, Vol. 1484.
Elefteriadou, L., Kondyli, A., Washburn, S., Brilon, W., Lohoff, J., Jacobson, L., Hall, F., & Persaud, B. (2011), “Proactive ramp management under the threat of freeway-flow breakdown,” Procedia-Social and Behavioral Sciences, Vol. 16, pp. 4-14.
Geistefeldt, J., & Brilon, W. (2009), “A comparative assessment of stochastic capacity estimation methods,” Transportation and Traffic Theory 2009: Golden Jubilee, Boston: Springer, pp. 583-602.
Gubbala, P. S. S. S. (2017), Effect of On-Ramp Demand on Capacity at Merge Bottleneck Locations, M.E. Thesis, University of Kansas.
Heikoop, H., & Henkens, N. (2016), “Recent developments and history of the Dutch HCM,” Transportation research procedia, Vol. 15, pp. 51-62.
Heshami, S., Kattan, L., Gong, Z., & Aalami, S. (2019), “Deterministic and stochastic freeway capacity analysis based on weather conditions,” Journal of Transportation Engineering, Part A: Systems, Vol. 145, No. 5, 04019016.
Kondyli, A., Elefteriadou, L., Brilon, W., Hall, F. L., Persaud, B., & Washburn, S. (2013), “Development and evaluation of methods for constructing breakdown probability models,” Journal of Transportation Engineering, Vol. 139, No. 9, pp. 931-940.
Kondyli, A., Gubbala, P., & Elefteriadou, L. (2016), “The Contribution of Ramp Demand in the Capacity of Merge Bottleneck Locations,” Transportation Research Procedia, Vol. 15, pp. 346-355.
Lorenz, M. R., & Elefteriadou, L. (2001), “Defining freeway capacity as function of breakdown probability,” Transportation Research Record, Vol. 1776, No. 1, pp. 43-51.
Srivastava, A., & Geroliminis, N. (2013), “Empirical observations of capacity drop in freeway merges with ramp control and integration in a first-order model,” Transportation Research Part C: Emerging Technologies, Vol. 30, pp. 161-177.
Van Beinum, A., Farah, H., Wegman, F., & Hoogendoorn, S. (2018), “Driving behaviour at motorway ramps and weaving segments based on empirical trajectory data,” Transportation Research Part C: Emerging Technologies, Vol. 92, pp. 426-441.
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