A review of methodological approaches for saturation flow estimation at signalized intersections

2020 ◽  
Vol 47 (3) ◽  
pp. 237-247 ◽  
Author(s):  
Satyajit Mondal ◽  
Ankit Gupta
Keyword(s):  
Influencing Factors ◽  
Discharge Rate ◽  
Estimation Procedure ◽  
Signalized Intersections ◽  
Signalized Intersection ◽  
Factors Affecting ◽  
Flow Estimation ◽  
Soft Computing Techniques ◽  
Methodological Approaches ◽  
Saturation Flow

The estimation of the saturation flow is the utmost component for performance evaluation of a signalized intersection. The flow rate estimation procedure includes the analysis of the vehicles headway, vehicles discharge rate, passenger car unit, effective green time and cycle length of the signalling system. This study attempts to exhaustively review the existing literature and its suitability along with the multiple factors affecting the performance of signalized intersection. Different methodological approaches and soft computing techniques used worldwide by the researchers both in developed and developing countries are emphasized. This study also highlights the several influencing factors that have a significant impact on saturation flow value and several methodological approaches to determine the flow value through normalizing the influencing factors, which lead to a better way for planning and designing of a signalized intersection.

Effect of Bicycles on Capacity of Signalized Intersections

1998 ◽  
Vol 1646 (1) ◽  
pp. 87-95 ◽  
Author(s):  
D. Patrick Allen ◽  
Joseph E. Hummer ◽  
Nagui M. Rouphail ◽  
Joseph S. Milazzo
Keyword(s):  
Signalized Intersections ◽  
Signalized Intersection ◽  
Motor Vehicles ◽  
Highway Capacity ◽  
Highway Capacity Manual ◽  
Flow Adjustment ◽  
Conflict Zone ◽  
Pedestrian Traffic ◽  
Saturation Flow ◽  
The Impact

Although much is known about the operation of signalized intersections, little or no empirical research has been conducted regarding the effect of bicycles on signalized intersection capacity. The purpose of this study was to accurately quantify the effects of bicycles on signalized intersection capacity through the videotaping of several intersections that had significant bicycle traffic. Through the videotaping of intersections in Davis, California, and Gainesville, Florida, a relationship was determined between bicycle volumes and the percent of the green phase during which bicycle traffic occupies a conflict zone between bicycles and right-turning motor vehicles. It was also determined that one can ascertain the total net occupancy due to pedestrians and bicycles by taking the overlapping effects between bicycles and pedestrians into account. Using this total occupancy due to bicycles and pedestrians, one can calculate a saturation flow adjustment factor ( fRph) that reflects the reduction in saturation flow, and ultimately lane group capacity, for lane groups containing vehicles making permissive right turns in the presence of bicycles and pedestrians. The proposed procedure yields lower saturation flows and capacities than the current Highway Capacity Manual (HCM) procedure. In other words, on the basis of empirical data, when combined with pedestrian effects, the impact of bicycles on the saturation flow of lane groups containing right-turning vehicles is probably more detrimental than previously believed, and the capacities of intersections with significant bicycle and pedestrian traffic may be overestimated by using the current HCM procedures.

scholarly journals U-turn capacity at signalized intersections

2021 ◽  
Author(s):  
Dmitri Martiakhin ◽  
Tatiana Komarova ◽  
Dmitri Nemchinov ◽  
Alexandr Mikhailov
Keyword(s):  
Traffic Flow ◽  
Field Observation ◽  
Signalized Intersections ◽  
Signalized Intersection ◽  
Flow Volume ◽  
Traffic Lane ◽  
Flow Geometry ◽  
Saturation Flow ◽  
Traffic Organization

The article presents the results of a study of the intersections capacity, at which the U-turn lane is organized, depending on the traffic flow volume and its organization. Signalized intersection capacity depends on traffic flow, geometry, traffic organization type, driver’s behaviour and headways between drivers in each traffic lane. To analyse signalized intersection capacity it is necessary to determine traffic lanes saturation flow. The study presents field observation analyses of headways between drivers and saturation flow on U-turn lanes at signalised intersections in Moscow. To conduct research and identify patterns, intersections in Moscow were chosen with different conditions and different organization of the U-turns.

scholarly journals Capacity of Bicycle Platoon Flow at Two-Phase Signalized Intersection: a Case Analysis of Xi’an City

2011 ◽  
Vol 23 (3) ◽  
pp. 177-186 ◽  
Author(s):  
Yong-Gang Wang ◽  
Gang Wei ◽  
Xu Zhu ◽  
Yu-Long Pei
Keyword(s):  
Arrival Rate ◽  
Signalized Intersections ◽  
Signalized Intersection ◽  
Pedestrian Flow ◽  
Two Phase ◽  
Signal Parameters ◽  
Capacity Model ◽  
Saturation Flow ◽  
The Impact ◽  
Xi’An City

Although much is known about the operation of signalized intersections, little or no empirical research has been conducted regarding bicycle capacity at these locations and the correspondent contributory factors. The purpose of this study is to accurately quantify the capacity of bikeway at signalized intersection through a fluid dispersion approach, and ultimately the lane group capacity. Using this total dispersion of bicycle flow, a relationship is also described between bicycle volume per hour and per unit width, signal parameters (length of signal cycle and green time), bicycle flow (arrival rate, density, moving velocity) and geometric intersection distance. Through the videotaping of four intersections that have significant bicycle traffic around Xiaozhai in Xi’an, China, it is ascertained that bicycle capacity varies linearly (but limited by an asymptote domain) associated with the adjustment of these parameters. The analytical results indicate that the impact saturation flow of lane groups containing right-turning vehicles and pedestrian flow at signalized intersections on bicycles is being underestimated. If this is the case, then capacity is being overestimated through the HCM 2000 capacity model and JJ37-90 approach and intersections are not being adequately designed, due to the neglect of conflict nature of mixed traffic arrivals in competing for space.

Effects of U-Turns on Capacities of Signalized Intersections

2005 ◽  
Vol 1920 (1) ◽  
pp. 74-80 ◽  
Author(s):  
Pan Liu ◽  
Jian John Lu ◽  
Jingjing Fan ◽  
Juan C. Pernia ◽  
Gary Sokolow
Keyword(s):  
Regression Model ◽  
Signalized Intersections ◽  
Signalized Intersection ◽  
Left Turn ◽  
Highway Capacity Manual ◽  
Bay Area ◽  
Study Team ◽  
Adjustment Factors ◽  
Left Turns ◽  
Saturation Flow

In Florida, the increased use of restrictive medians and directional median openings has generated many U-turns at signalized intersections. There is no widely accepted procedure for estimating the effects of U-turning vehicles on signalized intersection capacity. In the 2000 edition of the Highway Capacity Manual, U-turns are treated as left turns for estimation of saturation flow rates. However, the operational effects of U-turns and left turns are different. This study analyzed the effects of U-turning vehicles on the left-turn saturation flow rate. Data were collected at three signalized intersections in the Tampa Bay area in Florida. In total, the study team recorded the queue discharge times for 260 queues, including 571 U-turning vehicles and 1,441 left-turning vehicles. On the basis of the data collected in the field, a regression model was developed to estimate the relationship between the average queue discharge time for each turning vehicle and the various percentages of U-turning vehicles in the left-turn traffic stream. Adjustment factors for various percentages of U-turning vehicles were also developed by using the regression model. The adjustment factors developed in this study can be directly used to estimate the capacity reduction due to the presence of various percentages of U-turning vehicles at a signalized intersection.

Headway Compression during Queue Discharge at Signalized Intersections

2005 ◽  
Vol 1920 (1) ◽  
pp. 81-85 ◽  
Author(s):  
Feng-Bor Lin ◽  
Daniel R. Thomas
Keyword(s):  
New York ◽  
Discharge Rate ◽  
Green Light ◽  
The United States ◽  
Signalized Intersections ◽  
Discharge Characteristics ◽  
Traditional Concept ◽  
Highway Capacity Manual ◽  
Discharge Rates ◽  
Saturation Flow

Current methodologies for estimation of intersection capacity are based mainly on the concept of saturation flow. Saturation flow is the steady maximum queue discharge rate after the green light is turned on. According to the U.S. Highway Capacity Manual, this steady maximum rate is generally reached after the fourth queuing vehicle is discharged. Two recent studies conducted in Hawaii and Taiwan, however, have found that queue discharge headways tend to undergo compression for a considerable time as more vehicles in the same queue are discharged. Consequently, queue discharge rates often kept rising even after the 15th vehicle has entered the intersection. If this queue discharge characteristic is common in the United States, then there is a need to assess the implications of con-tinued use of the traditional concept of saturation flow rate for capacity analysis of signalized intersections. To provide insight into this potential problem, this study examines the queue discharge characteristics at three intersections on Long Island, New York. The queue discharge characteristics at all three intersections were found to be similar to those observed in Taiwan and Hawaii.

Model for Minimum Driveway Corner Clearances at Signalized Intersections

1997 ◽  
Vol 1579 (1) ◽  
pp. 53-62
Author(s):  
Gary Long ◽  
Cheng-Tin Gan
Keyword(s):  
Signalized Intersections ◽  
Continuous Variables ◽  
Flow Conditions ◽  
Highway Capacity ◽  
Factors Affecting ◽  
Highway Capacity Manual ◽  
Proposed Model ◽  
Adjustment Factors ◽  
Saturation Flow ◽  
The Ideal

A signalized intersection typically operates under both saturated and undersaturated traffic flow conditions at different times of the day. When an intersection operates under saturated flow conditions, its ability to dissipate traffic becomes a primary matter of concern. On the other hand, safety is often the major concern due to higher vehicular travel speeds associated with undersaturated flow conditions. The minimum corner clearance distances required under the two different flow conditions are not the same. To be effective, minimum corner clearances must be set such that the needs under both types of flow conditions are satisfied. Existing guidelines for minimum corner clearances were reviewed, and none were found to address the capacity issue. A new model designed to meet both capacity and safety needs is proposed. The model produces a refined minimum corner clearance distance by applying a set of adjustment factors to an initial minimum corner clearance, a procedure similar to that of the familiar Highway Capacity Manual for adjusting the ideal saturation flow rate. Unlike existing guidelines, the proposed model is flexible, is much less discrete for continuous variables, and can easily incorporate as many factors affecting corner clearance as needed.

Modeling Capacity of Through Movement at Signalized Intersection Affected by Short Left-Turn Bay under Different Signal Settings

2021 ◽  
pp. 036119812110064
Author(s):  
Zihang Wei ◽  
Yunlong Zhang ◽  
Xiaoyu Guo ◽  
Xin Zhang
Keyword(s):  
Cycle Length ◽  
Signalized Intersections ◽  
Signalized Intersection ◽  
Essential Factor ◽  
Highway Capacity ◽  
Left Turn ◽  
Highway Capacity Manual ◽  
Proposed Model ◽  
Vehicle Demand ◽  
The One

Through movement capacity is an essential factor used to reflect intersection performance, especially for signalized intersections, where a large proportion of vehicle demand is making through movements. Generally, left-turn spillback is considered a key contributor to affect through movement capacity, and blockage to the left-turn bay is known to decrease left-turn capacity. Previous studies have focused primarily on estimating the through movement capacity under a lagging protected only left-turn (lagging POLT) signal setting, as a left-turn spillback is more likely to happen under such a condition. However, previous studies contained assumptions (e.g., omit spillback), or were dedicated to one specific signal setting. Therefore, in this study, through movement capacity models based on probabilistic modeling of spillback and blockage scenarios are established under four different signal settings (i.e., leading protected only left-turn [leading POLT], lagging left-turn, protected plus permitted left-turn, and permitted plus protected left-turn). Through microscopic simulations, the proposed models are validated, and compared with existing capacity models and the one in the Highway Capacity Manual (HCM). The results of the comparisons demonstrate that the proposed models achieved significant advantages over all the other models and obtained high accuracies in all signal settings. Each proposed model for a given signal setting maintains consistent accuracy across various left-turn bay lengths. The proposed models of this study have the potential to serve as useful tools, for practicing transportation engineers, when determining the appropriate length of a left-turn bay with the consideration of spillback and blockage, and the adequate cycle length with a given bay length.

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 Aphid–Plant–Phytovirus Pathosystems: Influencing Factors from Vector Behaviour to Virus Spread

Agriculture ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 502
Author(s):  
Junior Corneille Fingu-Mabola ◽  
Frédéric Francis
Keyword(s):  
Influencing Factors ◽  
Virus Transmission ◽  
Physical Factors ◽  
Factors Affecting ◽  
Vector Borne Diseases ◽  
Vector Behaviour ◽  
Crop Fields ◽  
Host Seeking ◽  
The Impact ◽  
Vector Efficiency

Aphids are responsible for the spread of more than half of the known phytovirus species. Virus transmission within the plant–aphid–phytovirus pathosystem depends on vector mobility which allows the aphid to reach its host plant and on vector efficiency in terms of ability to transmit phytoviruses. However, several other factors can influence the phytoviruses transmission process and have significant epidemiological consequences. In this review, we aimed to analyse the aphid behaviours and influencing factors affecting phytovirus spread. We discussed the impact of vector host-seeking and dispersal behaviours mostly involved in aphid-born phytovirus spread but also the effect of feeding behaviours and life history traits involved in plant–aphid–phytovirus relationships on vector performances. We also noted that these behaviours are influenced by factors inherent to the interactions between pathosystem components (mode of transmission of phytoviruses, vector efficiency, plant resistance, …) and several biological, biochemical, chemical or physical factors related to the environment of these pathosystem components, most of them being manipulated as means to control vector-borne diseases in the crop fields.

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