Development of Driver Population Factors for Capacity Analysis of Signalized Intersections

2000 ◽  
Vol 1710 (1) ◽  
pp. 239-245 ◽  
Author(s):  
Yanhu Zhou ◽  
Jian John Lu ◽  
Edward A. Mierzejewski ◽  
Xuewen Le
Keyword(s):  
Flow Rate ◽  
Signalized Intersections ◽  
Capacity Analysis ◽  
Study Results ◽  
Adjustment Factors ◽  
Saturation Flow Rate ◽  
High Level ◽  
Saturation Flow ◽  
The Impact ◽  
Population Adjustment

In the Highway Capacity Manual (HCM), driver population factors are included to adjust for the impact of nonlocal drivers on freeway capacity. There are no such factors in the HCM to account for the possible change of capacity at signalized intersections caused by unfamiliar drivers in the traffic stream. The results obtained from a research study to develop driver population adjustment factors for capacity analysis of signalized intersections are summarized. Detailed procedures for quantifying driver population adjustment factors are presented. The factors were derived on the basis of data collected in Hillsborough, Pinellas, Orange, and Osceola counties in Florida. Study results indicated that nonlocal drivers had a significant impact on the saturation flow rate. When a signalized intersection was identified with a high level of nonlocal drivers, the saturation flow rate as well as the capacity could be reduced by 19 percent, which corresponded to a driver population factor as low as 0.81.

scholarly journals Impact of Guideline Markings on Saturation Flow Rate at Signalized Intersections

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Zhengtao Qin ◽  
Jing Zhao ◽  
Shidong Liang ◽  
Jiao Yao
Keyword(s):  
Flow Rate ◽  
Signalized Intersections ◽  
Estimation Model ◽  
Left Turn ◽  
Proposed Model ◽  
Research Goal ◽  
Saturation Flow Rate ◽  
Saturation Flow ◽  
The Impact

Many intersections around the world are irregular crossings where the approach and exit lanes are offset or the two roads cross at oblique angles. These irregular intersections often confuse drivers and greatly affect operational efficiency. Although guideline markings are recommended in many design manuals and codes on traffic signs and markings to address these problems, the effectiveness and application conditions are ambiguous. The research goal was to analyze the impact of guideline markings on the saturation flow rate at signalized intersections. An adjustment estimation model was established based on field data collected at 33 intersections in Shanghai, China. The proposed model was validated using a before–after case study. The underlying reasons for the impact of intersection guideline markings on the saturation flow rate are discussed. The results reveal that the improvement in the saturation flow rate obtained from painting guide line markings is positively correlated with the number of traffic lanes, offset of through movement, and turning angle of left-turns. On average, improvements of 7.0% and 10.3% can be obtained for through and left-turn movements, respectively.

scholarly journals Effect of U-Turns and Heavy Vehicles on the Saturation Flow Rates of Left-Turn Lanes at Signalized Intersections

2020 ◽  
Vol 12 (11) ◽  
pp. 4485
Author(s):  
Abdelrahman Abuhijleh ◽  
Charitha Dias ◽  
Wael Alhajyaseen ◽  
Deepti Muley
Keyword(s):  
Flow Rate ◽  
Signalized Intersections ◽  
The State ◽  
Heavy Vehicles ◽  
Flow Rates ◽  
Left Turn ◽  
Highway Capacity Manual ◽  
Adjustment Factors ◽  
Saturation Flow Rate ◽  
Saturation Flow

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.

Investigation of saturation flow rate using video camera at signalized intersections in Jordan

2020 ◽  
Vol 11 (1) ◽  
pp. 216-226
Author(s):  
Bara’ W. Al-Mistarehi ◽  
Ahmad H. Alomari ◽  
Mohamad S. Al Zoubi
Keyword(s):  
Flow Rate ◽  
Standard Procedure ◽  
Video Camera ◽  
Signalized Intersections ◽  
Speed Limit ◽  
Local Conditions ◽  
Highway Capacity Manual ◽  
Saturation Flow Rate ◽  
Turning Radius ◽  
Saturation Flow

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.

scholarly journals Estimation Impact of Capital Development Projects on Adjacent Street and Road Network in Organization of Traffic by Means of Signal Controlled Intersections

2021 ◽  
Vol 20 (6) ◽  
pp. 506-513
Author(s):  
A. V. Zedgenizov ◽  
D. V. Kapskiy ◽  
R. Yu. Lagerev
Keyword(s):  
Mathematical Model ◽  
Traffic Flow ◽  
Flow Rate ◽  
Road Network ◽  
Signalized Intersections ◽  
Cycle Phase ◽  
Saturation Flow Rate ◽  
Centers Of Mass ◽  
Saturation Flow ◽  
Demand And Capacity

The paper discusses problems of assessing the impact of mass attraction centers on the adjacent street and road network in the process of their functioning, expansion or conversion. The choice of criteria for assessing the organization of traffic flow, given in the Russian and foreign literature, has been substantiated, in particular, it is proposed to use v/c ratio for adjacent junction and corresponding level of traffic service (LOS). The main models for estimating capacity of signalized intersections are presented. The procedures of forming a mathematical model for estimating the load factor of signalized intersections is shown. The concepts of lane group capacity, total lost time per cycle, phase coefficients, saturation flow rate, and coefficients taking into account the decrease in the ideal saturation flow rate are explained. A mathematical model for estimating transport demand is presented, which allows to calculate the intensity of traffic flow to and from the center of mass attraction on the basis of the total traffic flow of correspondence, share of visitors in individual transport, average filling of individual transport, and coefficient of daily irregularity upon arrival and departure of visitors on an individual transport. An integrated mathematical model of loaf factor is proposed which includes parameters for estimating transport demand for centers of mass embarrassment and parameters that determine the signalized intersections capacity. The uniqueness of the integrated model is that it simultaneously involves parameters reflecting the demand and capacity of loading intersection. Recommendations are made on assessing the level of traffic service flows and the v/s ratio, based on the data of transport demand and capacity, adjacent to the centers of mass attraction of the road network. The presented method of estimating the LOS based on the capacity of the signalized intersections allows us to estimate the influence degree of mass attraction centers on the adjacent urban road network.

scholarly journals Dynamic Estimation of Saturation Flow Rate at Information-Rich Signalized Intersections

Information ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 178 ◽  
Author(s):  
Yi Wang ◽  
Jian Rong ◽  
Chenjing Zhou ◽  
Yacong Gao
Keyword(s):  
Neural Network ◽  
Flow Rate ◽  
Network Models ◽  
Signalized Intersections ◽  
Neural Network Models ◽  
The Road ◽  
The Neural Network ◽  
Dynamic Estimation ◽  
Saturation Flow Rate ◽  
Saturation Flow

Intersections are the bottlenecks of the road network. The capacity of signalized intersections restricts the operation of the road network. Dynamic estimation of capacity is necessary for signalized intersections refined management. With the development of technology, more and more detectors were installed near the intersection. It had been the information-rich environment, which provided support for dynamic estimation of capacity. A dynamic estimation method for a saturation flow rate based on a neural network was developed. It would grasp the dynamic change of saturation flow rates and influencing factors. The measure data at three scenarios (through lanes, shared right-turn and through lanes, shared left-turn and through lanes) of signalized intersections in Beijing were taken as examples to validate the proposed method. Firstly, the traffic flow characteristics of the three scenarios and factors affecting the saturation flow rate were analyzed. Secondly, neural network models of the three scenarios were established. Then the hyperparameters of neural network models were determined. After training, the neural network structure and parameters were saved. Lastly, the test set data was validated by the training model. At the same time, the proposed method was compared with the Highway Capacity Manual (HCM) method and the statistical regression method. The results show that both regression models and neural network models have better accuracy than HCM models. In a simple scenario, the neural network models are not much different from the regression models. With the increase of complexity of scenarios, the advantages of neural network models are highlighted. In through-left lane and through-right lane scenarios, the estimated saturation flow rates used by the proposed method were 7.02%, 4.70%, respectively. In the complexity of traffic scenarios, the proposed method can estimate the saturation flow rate accurately and timely. The results could be used for signal control schemes optimizing and operation managing at signalized intersections subtly.

Sign in / Sign up

Export Citation Format

Share Document