scholarly journals Estimation of Saturation Flow Rates at Signalized Intersections

2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
Chang-qiao Shao ◽  
Xiao-ming Liu

The saturation flow rate is a fundamental parameter to measure the intersection capacity and time the traffic signals. However, it is revealed that traditional methods which are mainly developed using the average value of observed queue discharge headways to estimate the saturation headway might lead to underestimate saturation flow rate. The goal of this paper is to study the stochastic nature of queue discharge headways and to develop a more accurate estimate method for saturation headway and saturation flow rate. Based on the surveyed data, the characteristics of queue discharge headways and the estimation method of saturated flow rate are studied. It is found that the average value of queue discharge headways is greater than the median value and that the skewness of the headways is positive. Normal distribution tests were conducted before and after a log transformation of the headways. The goodness-of-fit test showed that for some surveyed sites, the queue discharge headways can be fitted by the normal distribution and for other surveyed sites, the headways can be fitted by lognormal distribution. According to the queue discharge headway characteristics, the median value of queue discharge headways is suggested to estimate the saturation headway and a new method of estimation saturation flow rates is developed.

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Linhong Wang ◽  
Yunhao Wang ◽  
Yiming Bie

Saturation flow rate (SFR) is a fundamental parameter to the level of service evaluation, lane capacity calculation, and signal timing plan optimization at signalized intersections. It is affected by a variety of factors including weather conditions, lane width, and the type of the driver. How to accurately estimate the SFR remains one of the most important tasks in traffic engineering. Existing studies generally rely on the field measurement method which requires a large number of people collecting data at the intersection. As a result, the method incurs a high economic cost and cannot adapt to the dynamic change of SFR. In recent years, video detectors have been widely installed at intersections which are capable of recording the time each vehicle passes the stop line, the number plate of each vehicle, and the vehicle type. This paper therefore aims to propose an automatic estimation method for the SFR based on video detector data in order to overcome the limitation of the field measurement method. A prerequisite for estimating the SFR is to recognize the saturation headway. We consider the actual vehicle headway as time series and build an auxiliary regression equation whose parameters are estimated through the ordinary least squares method. We employ the Dickey-Fuller test to verify whether the headways in the time series are saturation headways. An iterative method using quantiles is proposed to filter out abnormal data. The SFR is finally calculated using the average value of saturation headways. To demonstrate the proposed method, we conduct a case study using data from an intersection with three entrance lanes in Qujing city, Yunnan Province, China. The overall estimation process is displayed and the impacts of quantile selection and data duration on the estimation accuracy are analyzed.


2020 ◽  
Vol 12 (11) ◽  
pp. 4485
Author(s):  
Abdelrahman Abuhijleh ◽  
Charitha Dias ◽  
Wael Alhajyaseen ◽  
Deepti Muley

The Saturation Flow Rate (SFR) is a primary measure that can be used when estimating intersection capacity. Further, the efficiency of signal control parameters also depends on the accuracy of assumed SFR values. Driver behavior, type of movement, vehicle type, intersection layout, and other factors may have a significant impact on the saturation flow rate. Thus, it is expected that driving environments that have heterogeneous driver populations with different driving habits and cultures may have different SFRs. In practice, the proposed SFRs based on US standards (Highway Capacity Manual, 2016) have been adopted in the State of Qatar without validation or calibration to consider the local road environment and the characteristics of the driving population. This study aims to empirically analyze the saturation flow rates for exclusive left-turn lanes and shared left- and U-turn lanes at two signalized intersections in Doha city, while considering the effects of heavy vehicles and U-turn maneuvers. Empirical observations revealed that the average base SFR, i.e., when the influences from heavy vehicles and U-turns were excluded, could vary approximately from 1800 vehicles per hour per lane (vphpl) to 2100 vphpl for exclusive left-turning lanes and approximately from 1800 vphpl to 1900 vphpl for shared left- and U-turning lanes. Furthermore, this study proposed different adjustment factors for heavy vehicle and U-turn percentages which can be applied in practice in designing signalized intersections, particularly in the State of Qatar.


2020 ◽  
Vol 11 (1) ◽  
pp. 216-226
Author(s):  
Bara’ W. Al-Mistarehi ◽  
Ahmad H. Alomari ◽  
Mohamad S. Al Zoubi

AbstractThis study aimed to investigate a potential list of variables that may have an impact on the saturation flow rate (SFR) associated with different turning movements at signalized intersections in Jordan. Direct visits to locations were conducted, and a video camera was used. Highway capacity manual standard procedure was followed to collect the necessary traffic data. Multiple linear regression was performed to classify the factors that impact the SFR and to find the optimal model to foretell the SFR. Results showed that turning radius, presence of camera enforcement, and the speed limit are the significant factors that influence SFR for shared left- and U-turning movements (LUTM) with R2 = 76.9%. Furthermore, the presence of camera enforcement, number of lanes, speed limit, city, traffic volume, and area type are the factors that impact SFR for through movements only (THMO) with R2 = 69.6%. Also, it was found that the SFR for LUTM is 1611 vehicles per hour per lane (VPHPL),which is less than the SFR for THMO that equals to 1840 VPHPL. Calibration and validation of SFR based on local conditions can improve the efficiency of infrastructure operation and planning activities because vehicles’ characteristics and drivers’ behavior change over time.


Author(s):  
A. M. Tahsin Emtenan ◽  
Christopher M. Day

During oversaturated conditions, common objectives of signal timing are to maximize vehicle throughput and manage queues. A common response to increases in vehicle volumes is to increase the cycle length. Because the clearance intervals are displayed less frequently with longer cycle lengths and fewer cycles, more of the total time is used for green indications, which implies that the signal timing is more efficient. However, previous studies have shown that throughput reaches a peak at a moderate cycle length and extending the cycle length beyond this actually decreases the total throughput. Part of the reason for this is that spillback caused by the turning traffic may cause starvation of the through lanes resulting in a reduction of the saturation flow rate within each lane. Gaps created by the turning traffic after a lane change may also reduce the saturation flow rate. There is a relationship between the proportions of turning traffic, the storage length of turning lanes, and the total throughput that can be achieved on an approach for a given cycle length and green time. This study seeks to explore this relationship to yield better signal timing strategies for oversaturated operations. A microsimulation model of an oversaturated left-turn movement with varying storage lengths and turning proportions is used to determine these relationships and establish a mathematical model of throughput as a function of the duration of green, storage length, and turning proportion. The model outcomes are compared against real-world data.


2016 ◽  
Vol 18 (2) ◽  
pp. 139-148
Author(s):  
Togani Cahyadi Upomo ◽  
Rini Kusumawardani

Rainfall event is a stochastic process, so to explain and analyze this processes the probability theory and frequency analysisare used. There are four types of probability distributions.They are normal, log normal, log Pearson III and Gumbel. To find the best probabilities distribution, it will used goodness of fit test. The tests consist of chi-square and smirnov-kolmogorov. Results of the chi-square test for normal distribution, log normal and log Pearson III was 0.200, while for the Gumbel distribution was 2.333. Results of Smirnov Kolmogorov test for normal distribution D = 0.1554, log-normal distribution D = 0.1103, log Pearson III distribution D = 0.1177 and Gumbel distribution D = 0.095. All of the distribution can be accepted with a confidence level of 95%, but the best distribution is log normal distribution.Kejadian hujan merupakan proses stokastik, sehingga untuk keperluan analisa dan menjelaskan proses stokastik tersebut digunakan teori probabilitas dan analisa frekuensi. Terdapat empat jenis distribusi probabilitas yaitu distribusi normal, log normal, log pearson III dan gumbel. Untuk mencari distribusi probabilitas terbaik maka akan digunakan pengujian metode goodness of fit test. Pengujian tersebut meliputi uji chi-kuadrat dan uji smirnov kolmogorov. Hasil pengujian chi kuadrat untuk distribusi normal, log normal dan log pearson III adalah 0.200, sedangkan untuk distribusi gumbel 2.333. Hasil pengujian smirnov kolmogorov untuk distribusi normal dengan nilai D = 0.1554, distribusi log normal dengan nilai D = 0.1103, distribusi log pearson III dengan nilai D = 0.1177 dan distribusi gumbel dengan nilai D = 0.095. Seluruh distribusi dapat diterima dengan tingkat kepercayaan 95%, tetapi distribusi terbaik adalah distribusi log normal.


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