scholarly journals Capacity and Delay Estimation for Roundabouts Using Conflict Theory

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Zhaowei Qu ◽  
Yuzhou Duan ◽  
Hongyu Hu ◽  
Xianmin Song
Keyword(s):  
Queuing Theory ◽  
High Volume ◽  
Conflict Theory ◽  
Model Parameters ◽  
Delay Model ◽  
Highway Capacity ◽  
Highway Capacity Manual ◽  
Traffic Characteristics ◽  
Capacity Model ◽  
Proposed Model

To estimate the capacity of roundabouts more accurately, the priority rank of each stream is determined through the classification technique given in the Highway Capacity Manual 2010 (HCM2010), which is based on macroscopical analysis of the relationship between entry flow and circulating flow. Then a conflict matrix is established using the additive conflict flow method and by considering the impacts of traffic characteristics and limited priority with high volume. Correspondingly, the conflict relationships of streams are built using probability theory. Furthermore, the entry capacity model of roundabouts is built, and sensitivity analysis is conducted on the model parameters. Finally, the entrance delay model is derived using queuing theory, and the proposed capacity model is compared with the model proposed by Wu and that in the HCM2010. The results show that the capacity calculated by the proposed model is lower than the others for an A-type roundabout, while it is basically consistent with the estimated values from HCM2010 for a B-type roundabout.

Arrival-Based Uniform Delay Model for Oversaturated Signalized Intersections with Poor Progression

2005 ◽  
Vol 1920 (1) ◽  
pp. 86-94
Author(s):  
Rahim F. Benekohal ◽  
Sang-Ock Kim
Keyword(s):  
Signalized Intersections ◽  
Delay Model ◽  
Adjustment Factor ◽  
Highway Capacity ◽  
New Approach ◽  
Highway Capacity Manual ◽  
Traffic Conditions ◽  
Proposed Model ◽  
Uniform Delay ◽  
Control Delays

For oversaturated traffic conditions, the Highway Capacity Manual (HCM) does not apply a progression adjustment factor to the delay model for signalized intersections when there is an initial queue. This causes counterintuitive results in the calculation of delay; for some cases, delay for a nonzero initial queue condition ends up being less than the delay with zero initial queue conditions. Also, for oversaturated traffic conditions, the delay model in the 2000 edition of HCM yields the same uniform delay values for all arrival types when there is an initial queue. This does not seem reasonable because it ignores the effect of platooning on delay. This paper introduces a new approach for computing uniform delay for oversaturated traffic conditions when progression is poor. This approach directly considers the platooning effects in delay and thus eliminates the need to apply a progression adjustment factor. The proposed model is applicable whether there is an initial queue or not. The approach was validated by a comparison of the control delays obtained from a CORSIM simulation to the delays from the proposed model. Validation procedures were conducted on the basis of zero and nonzero initial queue conditions. The proposed approach resulted in more accurate delay values than the HCM model.

Generalized Delay Model for Signalized Intersections and Arterial Streets

1997 ◽  
Vol 1572 (1) ◽  
pp. 112-121 ◽  
Author(s):  
Daniel B. Fambro ◽  
Nagui M. Rouphail
Keyword(s):  
Performance Measure ◽  
Signalized Intersections ◽  
Level Of Service ◽  
Delay Model ◽  
Highway Capacity ◽  
Average Delay ◽  
Variable Demand ◽  
Highway Capacity Manual ◽  
Arterial Streets ◽  
Proposed Model

Average delay per vehicle is the primary measure for determining the level of service at signalized intersections. This performance measure is also a major component in the calculation of average travel speed used to determine the level of service on arterial streets. The most widely used models for estimating delay at signalized intersections are those in Chapters 9 ("Signalized Intersections") and 11 ("Urban and Suburban Arterials") of the Highway Capacity Manual. This research reviewed the literature on models for estimating delay at signalized intersections to identify limitations and formulate revised models to address those limitations. Specific problems that were addressed included the inability to account for actuated-control parameters, oversaturation and variable demand, and metering and filtering by upstream traffic signals. The research team developed a generalized delay model to address these limitations and then validated the generalized model with both field and simulation data. The proposed model is sensitive to actuated-control parameter settings, oversaturation and variable demand conditions, and filtering and metering effects of upstream signals. The proposed model is also a good predictor of delays observed in the field and estimated by microscopic traffic simulation programs for the conditions studied. The generalized delay model is recommended for inclusion in future editions of the Highway Capacity Manual.

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.

Uncertainty in Operational Analysis of Two-Lane Highways

2002 ◽  
Vol 1802 (1) ◽  
pp. 105-114 ◽  
Author(s):  
R. Tapio Luttinen
Keyword(s):  
Input Data ◽  
Travel Speed ◽  
Level Of Service ◽  
Model Parameters ◽  
Highway Capacity ◽  
Highway Capacity Manual ◽  
Operational Analysis ◽  
Percent Time ◽  
Different Types ◽  
Percent Time Spent Following

The Highway Capacity Manual (HCM) 2000 provides methods to estimate performance measures and the level of service for different types of traffic facilities. Because neither the input data nor the model parameters are totally accurate, there is an element of uncertainty in the results. An analytical method was used to estimate the uncertainty in the service measures of two-lane highways. The input data and the model parameters were considered as random variables. The propagation of error through the arithmetic operations in the HCM 2000 methodology was estimated. Finally, the uncertainty in the average travel speed and percent time spent following was analyzed, and four approaches were considered to deal with uncertainty in the level of service.

Validation of Generalized Delay Model for Vehicle-Actuated Traffic Signals

1997 ◽  
Vol 1572 (1) ◽  
pp. 105-111 ◽  
Author(s):  
Nagui M. Rouphail ◽  
Mohammad Anwar ◽  
Daniel B. Fambro ◽  
Paul Sloup ◽  
Cesar E. Perez
Keyword(s):  
North Carolina ◽  
Field Data ◽  
Traffic Signals ◽  
Signalized Intersections ◽  
Delay Model ◽  
Highway Capacity ◽  
Generalized Model ◽  
Highway Capacity Manual ◽  
Traffic Volumes ◽  
Isolated Intersection

One limitation of the Highway Capacity Manual (HCM) model for estimating delay at signalized intersections is its inadequate treatment of vehicle-actuated traffic signals. For example, the current delay model uses a single adjustment for all types of actuated control and is not sensitive to changes in actuated controller settings. The objective in this paper was to use TRAF-NETSIM and field data to evaluate a generalized delay model developed to overcome some of these deficiencies. NETSIM was used to estimate delay at an isolated intersection under actuated control, and the delay values obtained from NETSIM were then compared with those estimated by the generalized delay model. In addition, field data were collected from sites in North Carolina, and delays observed in the field were compared with those estimated by the generalized delay model. The delays estimated by the generalized model were comparable with the delays estimated by NETSIM. The data compared favorably for degrees of saturation of less than 0.8. However, at higher degrees of saturation, the generalized model produced delays that were higher than NETSIM’s. Some possible explanations for this discrepancy are discussed. The delays estimated by the generalized model were comparable with delays observed in the field. Researchers have concluded that the generalized delay model is sensitive to changes in traffic volumes and vehicle-actuated controller settings and that the generalized delay model is much improved over the current HCM model in estimating delay at vehicle-actuated traffic signals.

scholarly journals Capacity of Advance Right-Turn Motorized Vehicles at Signalized Intersections for Mixed Traffic Conditions

2019 ◽  
Vol 2019 ◽  
pp. 1-13
Author(s):  
Bing Li ◽  
Wei Cheng ◽  
Yiming Bie ◽  
Bin Sun
Keyword(s):  
Arrival Rate ◽  
Highway Capacity ◽  
Highway Capacity Manual ◽  
Traffic Conditions ◽  
Capacity Model ◽  
Conflict Zone ◽  
Traffic Conflict ◽  
Motorized Vehicles ◽  
The Relationship ◽  
Gap Acceptance Theory

Right-turn motorized vehicles turn right using channelized islands, which are used to improve the capacity of intersections. For ease of description, these kinds of right-turn motorized vehicles are called advance right-turn motorized vehicles (ARTMVs) in this paper. The authors analyzed four aspects of traffic conflict involving ARTMVs with other forms of traffic flow. A capacity model of ARTMVs is presented here using shockwave theory and gap acceptance theory. The proposed capacity model was validated by comparison to the results of the observations based on data collected at a single intersection with channelized islands in Kunming, the Highway Capacity Manual (HCM) model and the VISSIM simulation model. To facilitate engineering applications, the relationship describing the capacity of the ARTMVs with reference to the distance between the conflict zone and the stop line and the relationship describing the capacity of the ARTMVs with reference to the effective red time of the nonmotorized vehicles moving in the same direction were analyzed. The authors compared these results to the capacity of no advance right-turn motorized vehicles (NARTMVs). The results show that the capacity of the ARTMVs is more sensitive to the changes in the arrival rate of nonmotorized vehicles when the arrival rate of the nonmotorized vehicles is 500  (veh/h)~2000  (veh/h) than when the arrival rate is some other value. In addition, the capacity of NARTMVs is greater than the capacity of ARTMVs when the nonmotorized vehicles have a higher arrival rate.

Accounting for Nonrandom Arrivals in Estimate of Delay at Signalized Intersections

1996 ◽  
Vol 1555 (1) ◽  
pp. 9-16 ◽  
Author(s):  
Janice Daniel ◽  
Daniel B. Fambro ◽  
Nagui M. Rouphail
Keyword(s):  
Field Data ◽  
Empirical Studies ◽  
Primary Objective ◽  
Signalized Intersections ◽  
Degree Of Saturation ◽  
Delay Model ◽  
Highway Capacity ◽  
Highway Capacity Manual ◽  
Research Show

The primary objective of this research was to determine the effect of nonrandom or platoon arrivals on the estimate of delay at signalized intersections. The delay model used in the 1994 Highway Capacity Manual (HCM) accounts for nonrandom arrivals through the variable m, which can be shown to be equal to 8kI, where k describes the arrival and service distributions at the intersection and I describes the variation in arrivals due to the upstream intersection. The 1994 HCM delay model m-values are a function of the arrival type, where the arrival type describes the quality of progression at the intersection. Although an improvement to the fixed k I-value used in the 1985 delay model, the 1994 m values are based on empirical studies from limited field data and do not account for the decrease in random arrivals as the volume approaches capacity at the downstream intersection. This research provides an estimate of the variable kI for arterial conditions. An analytical equation was developed as a function of the degree of saturation, and a separate equation was developed for each signal controller type. The results from this research show that the proposed kI's provide delay estimates closer to the measured delay compared with the delay estimates using the kI-values in the 1994 HCM delay model.

Validation of Generalized Delay Model for Oversaturated Conditions

1997 ◽  
Vol 1572 (1) ◽  
pp. 122-130 ◽  
Author(s):  
Roelof J. Engelbrecht ◽  
Daniel B. Fambro ◽  
Nagui M. Rouphail ◽  
Aladdin A. Barkawi
Keyword(s):  
Simulation Model ◽  
Close Agreement ◽  
Signalized Intersections ◽  
Delay Model ◽  
Traffic Operations ◽  
Microscopic Simulation ◽  
Highway Capacity ◽  
Traffic Demand ◽  
Highway Capacity Manual ◽  
The U.S

With today’s ever-increasing traffic demand, more and more signalized intersections are experiencing congestion for longer periods of time. To better quantify oversaturated conditions, it is necessary to accurately estimate oversaturation delay. The generalized delay model, proposed for inclusion in the next update of the U.S. Highway Capacity Manual (HCM), is introduced here. The generalized delay model differs from the model in the 1994 edition of the HCM as it is sensitive to the duration of the analysis period and is not restricted to degrees of saturation less than 1.2. The TRAF-NETSIM microscopic simulation model was used to verify the generalized delay equation for oversaturated conditions. A simulation model was used, because it is extremely difficult to measure oversaturated delay in the field. The study was designed to cover as much of the domain of oversaturated traffic operations as possible. The variability in simulated delays was investigated, and an equation was developed to predict the standard deviation of oversaturated delay estimates. It was found that delays estimated by the proposed generalized delay model are in close agreement with those simulated by TRAF-NETSIM. On average, simulated delays are overestimated slightly, but the error is small compared with actual delays. The proposed generalized delay model is expected to provide a good estimate of actual oversaturation delays that occur in the field.

Utilization of Auxiliary Through Lanes at Signalized Intersections with Downstream Lane Reductions

1997 ◽  
Vol 1572 (1) ◽  
pp. 167-173 ◽  
Author(s):  
Jamie W. Hurley
Keyword(s):  
Signalized Intersections ◽  
Stepwise Multiple Regression ◽  
Distribution Data ◽  
Highway Capacity ◽  
Left Turn ◽  
Highway Capacity Manual ◽  
Traffic Characteristics ◽  
Geometric Factors ◽  
Auxiliary Through Lanes ◽  
Right Turns

The capacity of multiple through lanes at signalized intersections depends on the distribution of traffic within these lanes, with equal lane distribution corresponding to maximum capacity. However, traffic characteristics, land use, and geometric factors usually prohibit this from occurring. Although the 1994 update of the Highway Capacity Manual considers the case of continuous through lanes at signalized intersections, the default values provided do not address situations in which lane reduction takes place downstream of the intersection. Lane distribution data obtained in the field can remedy the situation but for existing conditions only. This research employed the concept of captive and choice lane users in modeling lane use for intersection configurations with a single continuous through lane and an “auxiliary” through lane, which is continuous upstream of the intersection but is dropped downstream of it. Stepwise multiple regression was performed on data collected at sites in Tennessee to ascertain those factors significantly affecting auxiliary lane use. These factors were found to be ( a) right turns off the facility at the intersection, ( b) total left turns off the facility downstream of the intersection, ( c) right turns onto the facility in the first 122 m (400 ft) upstream of the intersection, ( d) right turns off the facility in the last 152 m (500 ft) of the auxiliary lane, ( e) downstream auxiliary lane length, and ( f) the existence of left-turn bays or two-way continuous left-turn lanes downstream of the intersection. For the configuration studied, lane distribution data often differed considerably from the default values given in the Highway Capacity Manual.

scholarly journals Providing a Model for the Optimal Allocation of Hospital Beds Based on Markov Chain Approach (Case Study: Shiraz-Shahid-Faghihi Hospital)

2021 ◽  
Author(s):  
Mehdi Kabiri Naeini ◽  
Zeynab Elahi ◽  
Abolfazl Moghimi Esfandabadi
Keyword(s):  
Markov Chain ◽  
Waiting Time ◽  
Queuing Theory ◽  
Optimal Allocation ◽  
Referral Rate ◽  
Service Rate ◽  
Model Parameters ◽  
Markov Chain Approach ◽  
Proposed Model ◽  
Hospital Beds

Background: As was observed in the corona crisis, in situations, such as war or natural disasters or epidemic diseases, the intensity of the applicants for medical services causes congestion problems. In this situation, due to the limited capacity of the system, queuing phenomenon for service applicants and in some cases, rejection of clients occur. Reducing the length of hospital stays by improving performance productivity can compensate for the shortage of hospital beds. In order to increase the productivity of personnel and equipment, it is necessary to eliminate unemployment and improve service scheduling. One of the ways to achieve these goals is to optimize the distribution of beds between wards. In the present study, in the form of Markov chain approach, according to the referral rate and service rate, the existing beds were allocated to different wards of the hospital to maximize service and minimize rejection of patients. Methods: The present study is an applied study conducted in 2019 for the optimal distribution of beds between the 3 wards of Shahid Faghihi Hospital in Shiraz. The research problem was modeled in the form of Markov chain approach and assuming the referral of clients according to the continuous-time Markov chain, the model parameters value was identified. The obtained mathematical model was solved by GAMS 24.1.3 software. Results: The proposed model led to an improvement in ward performance in terms of reducing patient waiting time and increasing the number of admitted patients. The proposed model reduced patient rejection by 8.6 %. According to the patients' referral rate to the wards and the service rate of each ward, based on sensitivity analysis, the number of beds allocated to each of the 3 wards was determined. Conclusion: Queuing theory can be applied as a tool to analyze the phenomena of the treatment system and determine the features of the waiting time, queue length, and capacity of the system. Appropriate allocation of hospital beds results in improving the efficiency and decreasing the patient rejection. Therefore, it could be useful in crisis, congestion in patients, and when increasing facilities is required.

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