Saturation Flow Rate Research Articles

Visual Analytic for Traffic Impact Assessment

This study strives to promote the state of traffic impact assessment through high-end visual analytics by incorporating spatial and temporal data visualization to enhance traffic management. Based on a dataset on traffic flow at three major intersections, we married data cleaning, integration, and transformation to set out for a detailed visual analysis. Thus, the critical materials comprise the traffic count in multiple lanes, vehicle types, and saturation flow rates to understand the road network's capacity. They essentially explored the traffic volume variations daily and hourly and pattern identification using heat maps, parallel coordinate charts, and bar plots. Thus, the findings expose the remarkable traffic volume and pattern differences by distinguishing peak and off-peak hours on weekdays and weekends. The level of service at each junction was determined by the volume-to-capacity ratio, identifying potential congested areas. As such, this work points to the importance of further improvements to visual analytic techniques to accurately predict traffic patterns and evaluate traffic management strategies effectively. Predictive models based on visual analytic findings can pave the way for proactive traffic control and congestion mitigation, making urban traffic management more efficient and safer. The current study provides a scaffold for additional exploration of the above-detailed methods and their penal outcomes in urban development planning and policy provision in terms of developing sustainable traffic control strategies and real-time decision-making improvements.

Combination of two-fluid model and delayed equilibrium model for the critical flow in a slit

Accurately predicting the mass flux, pressure profile, and velocity profile of the critical flow in a slit is essential for analyzing the breaking process of the liquid phase and calculating the aerosol source term for leak-before-break (LBB) monitoring and Loss of Coolant Accident (LOCA) risk analysis. A new critical flow model combining Two-fluid Model (TFM) and Delayed Equilibrium Model (DEM) is built to get accurate profiles while avoiding the same phase velocity in DEM and the arbitrary critical flow criterion in TFM. The new model is verified using past experiments of the critical flow in a slit. It proves to be accurate in mass flux but not in critical pressure, with maximum relative errors of around 25% in mass flux and around 80% in critical pressure. The new model is optimized for higher accuracy in critical pressure. The empirical equation of saturated phase mass flow rate fraction gradient is optimized by conducting approximate pressure profile calculation and regression analysis. The maximum relative error decreases little while the ratio of critical pressure relative errors lying in the range of ±40% increases after optimization. In contrast, the difference in the average abstract relative error of pressure between original TFM-DEM and DEM is much larger, for the maximum relative error of mass flux and critical pressure are around 25% and 110%. The comparison between the original and optimized TFM-DEM proves that the new critical flow model is accurate in mass flux and can be optimized to raise pressure calculation accuracy. The comparison between the original TFM-DEM and DEM proves that the phase velocity difference is the major source of accuracy improvement in the pressure profile.

Telemedicine in Pediatric Respiratory Care: Benefits, Challenges, and Future Directions

This study explores the impact of telemedicine on pediatric respiratory care, focusing on its benefits, challenges, and future directions. A mixed-methods approach was employed, involving 150 pediatric patients with chronic respiratory conditions such as asthma and cystic fibrosis, who were randomly assigned to either telemedicine or traditional care groups. The telemedicine group used a digital platform for video consultations, remote monitoring, and health management over a 12-month period. Quantitative data on clinical outcomes, including emergency department visits and hospitalizations, were collected from electronic health records, while patient-reported outcomes were assessed through surveys. Qualitative data were gathered via semi-structured interviews with patients and caregivers. Results indicated that the telemedicine group experienced significantly fewer emergency visits and hospitalizations, higher quality of life scores, better treatment adherence, and greater patient satisfaction compared to the traditional care group. Average oxygen saturation and peak flow rates were also higher in the telemedicine group, and more frequent monitoring alerts were noted.

A Grid-based Framework for Managing Autonomous Vehicles' Movement at Intersections

With a full fleet of autonomous vehicles (AV) in the future, the concept of signal-free intersections has attracted transportation researchers. Multiple studies have investigated different methods and protocols to facilitate vehicle decision-making at intersections. Most of these methods have relied on strong centralized or inter-vehicle communications. This research aims to develop a new protocol for managing vehicle movement at four-leg intersections assuming a fully automated fleet. The main concept of the proposed protocol is to maintain a continuous movement of vehicles entering the intersection, without stopping in queues, by controlling their sequence of movements. In the methodology a dynamic occupancy grid (DOG) approach is applied by initially dividing the intersection into dynamic grids (i.e. cells). The cells are in a virtual movement, emanating away from each lane-group without overlapping, like a gear machine. Each vehicle sits on a specific cell to traverse the intersection safely at a predetermined time. In other words, vehicles approaching an intersection must register their speed and position by certain sensors, and in return receive the appropriate acceleration and speed to finally be allocated to the suitable moving grids. The efficiency of the applied protocol was demonstrated by a practical example that presented a higher intersection capacity value exceeding the ideal saturation flow rate in some cases. This reflects the efficiency of the implemented protocol and its applicability to different low to high traffic flows. Moreover, the protocol shows more flexibility in dealing with different weather, geometric and traffic conditions.

A Stochastic Approach for Modeling the Saturation Flow Rate at Traffic Signals in Jordan

A Stochastic Approach for Modeling the Saturation Flow Rate at Traffic Signals in Jordan

Capacity & Level of Service Assessment of Gwarko Intersection

This report gives an overall view of the existing condition of the Gwarko intersection & various routes for accessing the location. This intersection is one of the busiest and major intersections of the valley that connects various major places that are Satdobato, Imadol, Mangalbazar, and Balkumari. The performance of the intersection is determined in terms of the control delay and by following methodologies of the Indo Highway Capacity Manual (Indo HCM) 2017. The traffic volume was estimated through CCTV film from the Metropolitan Police Office, Ranipokhari, Kathmandu. The classified vehicle count is done to determine the traffic flow at peak traffic conditions. The data collected refers to the weekday flows for the office hours between 8:00 am to 11:00 am and 4:00 pm to 7:00 pm (2020/08/05-2020/08/08). From the result, we got to know that the motorcycles/cycle volume is comparatively more than the volume of any other vehicle while the 3- wheeler & HGV volume was least among all. Then the pinnacle 15-minute progression of the pinnacle hour was taken to decide the least Pinnacle Hour Variable and the least PHF were utilized to decide the pinnacle hour stream for additional estimations. Saturation flow for each of the approaches of base intersection from the equation of unit base saturation flow, Base saturation flow is calculated (USF0) by different adjustment factors were calculated by multiplying to the Unit base saturation flow to obtain saturation flow rate of each bound. The vehicle development was isolated into various stages. Immersion stream rate, successful green time and general cycle length of every heading are taken as the contribution for limit computation. The absolute control postponement of every leg and the course of the stream were taken as the contribution to the investigation of the degree of administration assurance. At last, the LOS of every heading of the stream was acquired, which showed the LOS is preferable toward the beginning of the day over at night.

Understanding the Determinants of Lane Inefficiency at Fully Actuated Intersections: An Empirical Analysis

As urban traffic challenges intensify, the growing interest for fully actuated control systems in intersection management is on the rise due to their capacity to adapt to dynamic traffic demands. These systems play a crucial role in sustainable traffic solutions, significantly reducing delays and emissions and enhancing overall system efficiency. The optimal performance of these systems relies on effectively facilitating vehicle discharge at the saturation flow rate throughout the green period. This study introduces a new parameter, lane inefficiency, evaluating vehicle discharge effectiveness by comparing saturation flow rate with instantaneous discharge for each green period. It provides a comprehensive assessment of green utilization for specific lanes. This study also explores the impact of signal control system parameters and traffic flow characteristics on lane inefficiency using principal component analysis (PCA) and multiple linear regression models. This approach holistically evaluates how both signal control system and traffic flow parameters collectively influence efficient green period utilization. The findings emphasize the impact of critical factors on lane inefficiency, including green time, the proportion of total unused green time to green time, total unused green time, the percentage of heavy vehicles in departing traffic, the ratio of effective green time to cycle time, the total time headways of the first four vehicles, and queue length. Decision makers need to pay due attention to these parameters to enhance intersection performance and foster a more sustainable urban transportation network.

A preliminary analysis of base saturation flow rate during first loss time and saturated time at pretimed signalized intersections

Saturation flow rate is a key parameter essential for assessing signalized intersection capacity. The reference often used for signalized intersection planning in Indonesia is Indonesian Highway Capacity Guidelines (PKJI, 2023). In heterogeneous traffic environments, it has been observed that driver characteristics and behaviors exhibit significant variations. Therefore, this study aimed to investigate the prevailing saturation flow rate conditions at signalized intersections within Banda Aceh City. This exploration unfolded through two distinct scenarios, namely saturated time with and without initial lost time. For data acquisition, the focus was set on four signalized intersections, namely Jambo Tape, Pocut Baren, AMD Batoh, and Lhong Raya. This extraction procedure aimed to uncover insights into vehicle composition, movement patterns, and field saturation flow rate at these signalized intersections. In the aspect of analysis, a simple linear regression approach was adopted to recalibrate saturation flow rate coefficient of signalized intersections. This recalibration took into account vehicle compositions at the observation locations. The culmination of this analysis showed that in the scenario devoid of lost time under prevailing conditions, flow rate yielded S0 = 352 x Le. Meanwhile, for the scenario entailing lost time, the calculation produced was S0 = 294 x Le.

Base saturation flow rate (BSFR) and its effect on performance of pretimed signalized intersection with non-lane based urban heterogeneous traffic.

Signalized intersections that are pretimed are commonly used in rapidly developing cities with diverse traffic patterns, including those found in Indonesia. These intersections are a common source of congestion and delays in road networks, particularly when there is non-lane based (NLB) traffic in urban areas. Accurate estimation of both the base saturation flow rate and capacity is essential for this type of facility, as an error in the prediction of the base saturation flow rate can result in significant bias in capacity evaluation and design at signalized intersections. The estimation of capacity at signalized intersections is critical for ensuring optimal signal timings, minimizing delay, and reducing congestion. Heterogeneous traffic, which refers to the presence of various types of vehicles with distinct static and dynamic characteristics, is a common phenomenon. To address this issue, this paper presents a modeling approach for the SFR that takes into account heterogeneous traffic and NLB movements. Indonesia, being an archipelago with 34 provinces, served as the focus of this study, which specifically concentrated on Banda Aceh, the capital province of Aceh province. Employing primary and observed data collected at a specific, predetermined signalized timing, this study aimed to investigate the impact of intersection geometry and heterogeneous traffic composition on the SFR. By adopting the modeling approach for NLB movements, the study formulated the BSFR model. To estimate the scale parameters of the BSFR, the multiple linear regression approach was utilized. The analysis results reveal that the existing BSFR based on the IHCM formula gives a substantially biased estimation because the PCEs from the Indonesian Highway Capacity Manual (IHCM) are underestimated. This source of error could be partially due to the heterogeneous (varied vehicle composition) traffic flow with NLB movements, unlike that observed under the prevailing conditions of IHCM 1997. The empirical results show that the existing IHCM should be improved to avoid overestimation, particularly for effective approach width (We) greater than 4.5 m. A comparison of the BSFR prediction model between IHCM's PCEs and new PCEs shows that the BSFR is predicted more accurately in the latter case. This finding demonstrates that the existing IHCM can be adjusted in two ways: adjusting PCEs or calibrating the BSFR formula. The proposed models can also enhance the accuracy of BSFR prediction, leading to better signalized intersection capacity estimation, providing support for designing traffic operation, alleviating traffic congestion, and reducing congestion delay within the city.

Estimating Saturation Flow Rate of Signalized Intersections Using 511 Traveler System Cameras in Louisiana

Estimating Saturation Flow Rate of Signalized Intersections Using 511 Traveler System Cameras in Louisiana

Different methods for estimation of dynamic passenger car units – A review

In India, heterogeneous traffic conditions are prevailing due to a variety of vehicles with different static and dynamic characteristics. It is necessary to convert mixed traffic into homogeneous traffic by using Passenger Car Unit (PCU) values. Roadway and traffic conditions on urban roads vary considerably across the cities which generally affects the PCU values of different vehicles and the capacity of the roadway. This shows the dynamic nature of PCU values. PCU values are widely used in traffic capacity analysis, determination of Level Of Service (LOS), saturation flow rate, signal design and coordination, and development of traffic flow models. Because of these wide applications, the accuracy of dynamic PCU values is very important. Many researches have been carried out on the estimation of dynamic PCU values. This paper presents different methods for estimating dynamic PCU appropriate for heterogeneous traffic conditions on Indian roads. The challenges in estimating PCU values and future directions for improving the PCU estimation methods are also presented in this paper.

Implementing survival analysis to capture stochastic characteristics of saturation flow rate considering the impacts of adverse road-weather conditions

Saturation flow rate (SFR) variations were analyzed using the video data collected at a signalized intersection in Winnipeg, Canada, to investigate the implications of adverse road-weather (RW) conditions for SFR distributions and characteristics. Survival analysis was implemented to develop stochastic SFR distribution functions considering censored data and a statistical analysis method was developed for determining the optimal critical vehicle (CV) for measurement of saturation headway. The analysis findings suggest that adverse RW conditions decrease SFR significantly and moves CV to the front of the queue while having little impact on SFR considering heavy vehicles. Furthermore, the findings imply that the conventional SFR estimation method overestimates the probability of saturation at a given flow rate. The proposed analysis method reveals stochastic characteristics of SFR and provides a method to estimate SFR distributions under different RW conditions, which is essential for improving the operation of signalized intersections, particularly in cold regions.

Modeling Adjustment Factors for Pedestrians and Bicycles on Turning Vehicle Movements at Signalized Intersections

At signalized intersections, the capacity of turning vehicle streams can be affected by conflicting pedestrians and bicycles who share the same signal phase. To analyze this effect, measurements at 12 pedestrian and bicycle crossings at signalized intersections in Germany covering more than 4,300 signal cycles were conducted. The reduction in capacity can be accounted for by estimating the blockage time of possible turning vehicle departures. In addition to the pedestrian or bicycle volume, the empirical analyses revealed several other parameters influencing the blockage time such as the duration of the green time and the cycle time of signal control as well as the width of the pedestrian crossing. The influencing parameters were further analyzed by microscopic simulation. Since the current quality-of-service assessment procedures in the U.S. Highway Capacity Manual (HCM) and the German Highway Capacity Manual (HBS) do not consider all of these parameters sufficiently, a new model based on the gap-acceptance theory has been derived. The new model uses the relevant influencing parameters directly as input variables so that a precise calculation of the blockage time is achieved. The new model has been derived in such a way that it can be incorporated into the existing quality-of-service assessment procedures to determine the adjustment factors of the saturation flow rate or the capacity for turning movements. For practical applications, a simplification of the exact model is also presented with a good fit of the data.

Capacity characteristics of long-term work zones on signalized intersection approaches

This study explored the capacity characteristics of five long-term WZ configurations at a major signalized intersection in Toronto. In total, 1,766 cycles and 22,057 inter-vehicle headway observations were recorded using over 140 h of real-time traffic videos. The saturation flow rate ranged from 1318.7 to 1767.3 pc/hr/ln across the study sites. Interestingly, the Highway Capacity Manual WZ model was found to significantly overestimate the traffic capacity at the study sites. The analysis assessed the hypothesis that the saturation headway is further compressed when long queues are present on site. The average saturation headway during oversaturated conditions was found to be shorter by 5 to 11% across the study sites as compared to undersaturated conditions. Other influential factors such as day versus night and late-merge were assessed. The saturation flow under daytime conditions was higher by 3 to 5% as compared to nighttimes. Vehicles merging late from the closed lanes had a shorter headway as compared to vehicles approaching from the open lane by around 8 to 10%. Probability distribution functions of the saturation headway were developed, the best-fit curve for all cases was found to be the three-parameter lognormal distribution. The study also developed multiple regression equations to estimate WZ capacity reduction induced by heavy vehicles for a wide range of heavy vehicle percentages. On average, oversaturated conditions yielded a 5.4% additional flow reduction as compared to undersaturated conditions for the same HV%. Moreover, the impact of different snow conditions on the saturation flow was estimated. The fully slushy, partly slushy, and bare-and-wet snow categories resulted in headway elongation of 35.1 to 42%, 21.2 to 23.4%, and 6.2 to 12.6%, respectively. The study explains how the findings can assist transportation agencies and practitioners in improving the policies, practices, and guidelines related to WZ activities and planning.

A capacity model of signalized intersection with dedicated lanes for automated vehicles

ABSTRACT This paper proposes a capacity model to address the impact of automated dedicated lanes on the capacity of the signalized intersection. Firstly, the car-following modes in the mixed traffic flow are analyzed, and the influence of the setting of the automated dedicated lanes on the average headway is discussed. Secondly, a new capacity model with automated dedicated lanes is derived based on the classic capacity model. Then, a signalized intersection capacity model considering the automated dedicated lanes is further derived based on the saturation flow rate method. Finally, numerical simulation experiments are designed to discuss the key parameters on the traffic capacity of a signalized intersection. The results show that (i) the automated dedicated lanes are conducive to improving the traffic capacity; (ii) when the penetration rate of CAVs is less than 52%, the traffic capacity of the signalized intersection can be increased by nearly 1.25 times with the automated dedicated lanes. These findings can provide theoretical support for designing and optimizing signalized intersections in high levels (i.e. L3-L5) CAVs environments.

Effect of cloth mask versus N95 mask on hemodynamic parameters, oxygenation, and peak expiratory flow rate at rest and during physical activity in health-care providers: A cross-over design

Abstract Background: This study aimed to evaluate the effect of cloth mask vs. N95 mask on cardiovascular and pulmonary parameters at rest and during physical activity in health-care providers. Materials and Methods: Hundred health-care providers (45 men and 55 women) were included in the study. The procedure comprised of pre-test and post-test outcome measures like hemodynamic parameters comprising of heart rate,[15] respiratory rate,[16] peak expiratory flow rate[7] and oxygen saturation[7] taken on first day with cloth mask and second day with an N95 mask consecutively. Outcome measures were measured during quite sitting and brisk walking on treadmill, which was a self-paced test. Subjects manually selected their comfortable speed while walking on the treadmill, when exhausted the test was terminated. Comparing values of the outcome measures we found the effect of N95 masks and cloth masks on hemodynamic parameters, oxygenation and peak expiratory flow rate during rest and physical activity. Results: This study resulted in favor of N95 masks (P < 0.05). The difference was significant, concluding a slight increase in the respiratory rate (P = 0.0009) and heart rate (P = 0.0001) while wearing a cloth mask in comparison with an N95 mask. Oxygen saturation and peak expiratory flow rate were significantly maintained during physical activity while wearing an N95 mask, compared to a cloth mask (P = 0.0001). Conclusion: N95 masks should be utilized by health-care providers as, they did not impair respiratory rate, heart rate, oxygenation, and peak expiratory flow rate at rest and during physical activity. In comparison with cloth masks, N95 masks were better in maintaining oxygen saturation and peak expiratory flow rate during physical activity.

Lane-based analysis of the saturation flow rate considering traffic composition

ABSTRACT Saturation flow rate (SFR) is an essential metric for estimating the capacities of signalized intersections. Many factors, including traffic composition, configuration and geometry of the intersection, and driver behavior, which is typically characterized by social and cultural norms, influence SFR. Most of the previous studies estimated the SFR and adjustment factor to be applied independently without considering the interaction impact between influencing factors. This study aims to empirically examine the influence of the number of lanes, the heavy vehicle proportions, and their interaction effect on the SFR of through movements. A new model was developed to magnify the HV Impact on SFR value considering the number of lanes at the upstream approach. The outcome of this study helps to improve the multiplicative model’s structure for SFRs adjustment factors. Adopting the outcome of this study by the responsible transport authority would optimize the road infrastructure provision.

The Impact of Automated Vehicles on Road and Intersection Capacity

With the rapid development of autonomous driving technology, future road traffic must be composed of autonomous vehicles and artificial vehicles. Although autonomous vehicles have greatly improved road capacity, few studies have involved capacity at signal-controlled intersections, and most of the studies are based on experimental simulation. As such, there is a need to more scientifically analyze the impact of autonomous vehicles on road and intersection capacity. Based on three theories of flow-density relationships, traffic flow equilibrium analysis, and the following model, this paper firstly deduces the flow-density relationship of different vehicle types in a single environment. Secondly, flow-density relationships under different proportions of self-driving vehicles are derived. Through the derivation of these two models, the basic road saturation flow rates under different permeabilities of self-driving vehicles, can be obtained. Based on these results, a revised calculation model for the capacity of signalized intersections with different proportions of autonomous vehicles is proposed, which is essentially to revise the basic saturation flow rate under different permeabilities of autonomous vehicles. By using SUMO 1.15.0 traffic simulation software, the theoretical models are individually tested. The results show that the error rate between the theoretical calculation results and the SUMO simulation results, is less than 16%. This study can provide a basis for the calculation of basic capacity of roads and intersections in a future man-machine hybrid driving environment, and provide theoretical guidance for traffic management and control.

Traffic signal control model for the intersection with a work zone

ABSTRACT When a work zone is located at an intersection, it greatly reduces the capacity and change the traffic flow characteristics. However, the impacts of work zones have not attracted much attention, and the signal control method of the intersection with a work zone has not been investigated yet. This paper focuses on a specific type of work zone, which is located within the area of an intersection. The saturation flow rate model, traffic wave model, traffic delay model, and emptying time model are proposed to capture the traffic flow characteristics of the intersection with an island work zone, and a signal control model is further put forward. The real data is collected to calibrate, validate, and evaluate the proposed models. The results indicate that the proposed signal control model can reduce about 15.6% of queue length and 17.2% of traffic delay for the intersection with an island work zone.

Calculation Method of Lane Saturated Flow Rate Based on Asphalt Material

In order to improve the calculation accuracy and popularity of intersection lane saturated flow rate, we propose a calculation method of lane saturated flow ratebased on asphalt material. Firstly, environmentally friendly modified asphalt material is used to pave the intersection lanes to improve the smoothness and friction of the road surface.Then by millisecond level electric alarmvehicle data for measuring basis, using the small time interval method to extract thedata of green light saturated time interval.By K-means algorithm clustering analysis, the percentage of different time headway clusters after clustering is analyzed, and the average value of time headway of representatives group as saturated time headway, and the saturated flow rate in the measured period is further calculated.Finally, an example analysis is carried out on the vehicle data of Eshan Road and Huajin South Road in Wuhu City. The saturated flow rate calculated by the proposed method is 1478.68veh/h. Compared with the manual observation method, the relative error is less than 3%, which verified the accuracy and effectiveness of the proposed method.