Total Capacities at All-Way Stop-Controlled Intersections: Validation and Comparison of Highway Capacity Manual Procedure and Addition-Conflict-Flow Technique

Author(s):  
Ning Wu

An iterative model for computing capacities at all-way stop-controlled (AWSC) intersections has been included in the new Highway Capacity Manual (HCM) 2000. The model is based on five saturation headway values, each reflecting a different level of conflict faced by the subject-approach driver. From this model the capacity and service time at any approach can be computed using iterative calculations. The model in the HCM is a so-called approach-based model, which only takes into account the conflicting cases among the approaches. The effect of turning streams or movements is not modeled in sufficient detail. In contrast, a theoretical, stream-based model for determination of capacities at AWSC intersections has been developed. This model is based on the addition-conflict-flow (ACF) method developed from graph theory and takes into account all the traffic streams at the intersection. This allows a systematic and realistic analysis of the traffic process at AWSC intersections. The computational procedure included in the model can be conducted without iterative calculation steps. The ACF and the HCM models for intersections with single-lane approaches were comprehensively validated, as well as a modified version of the HCM model that significantly enhances its features. The results of the validation indicate that the total capacity of an AWSC intersection with single-lane approaches based on the HCM model ranges between 1,450 and 1,550 passenger cars per hour (pc/h), whereas the total capacity based on the ACF model ranges between 1,600 and 2,000 pc/h. The modified HCM model yields total capacities ranging between 1,700 and 2,000 pc/h. The ACF model and the modified HCM model yield similar capacity results under normal traffic flow conditions.

2017 ◽  
Vol 23 (1) ◽  
pp. 69
Author(s):  
EPF. Eko Yulipriyono ◽  
Djoko Purwanto

Passenger Car Equivalent (PCE) is a conversion factor to make equal the various types of vehicles that operating on the road section into one type of vehicles i.e. passenger cars. Indonesian Highway Capacity Manual (MKJI) 1997 has set the PCE values for various types of vehicle groups either motorized. PCE values of various types of vehicles are not absolute because many factors that affect can change over time and development of automotive technology. This study aimed to find out the changes of PCE value that occurs. As for the purpose of research to determine the current number of PCE values due to the change of operational characteristics of vehicles on a highway especially for urban highways. Data analysis for the determination of PCE values used: time headway method, speed method, capacity method, and vehicle dimension method. The conclusion of this study: PCE of light vehicles (LV) = 1 still in accordance with MJKI 1997; PCE of heavy vehicles (HV) varied depending on the road types. PCE of heavy vehicles that according to MKJI 1997 is used as a median; PCE of motorcycles (MC) of MKJI 1997 need to be adjusted to 0.4 or more, particularly in the calculation of actualy traffic flow.


2014 ◽  
Vol 69 (6) ◽  
Author(s):  
Othman Che Puan ◽  
Muttaka Na’iya Ibrahim ◽  
Usman Tasiu Abdurrahman

There exists a need to evaluate the performance indicator that reflects the current level of service (LOS) of the subject facility to justify any decision making on expenditures to be made for improving the performance level of a road facility. Free-flow speed (FFS) is one of the key parameters associated with LOS assessment for two-lane highways. Application of a more realistic approach for assessing road’s performance indicators would result in better estimates which could in turn suggest the most appropriate decision to be made (for situations where upgrading is needed); especially, in terms of finance, materials and human resources. FFS is the driver’s desired speed at low traffic volume condition and in the absence of traffic control devices. Its estimation is significant in the analysis of two-lane highways through which average travel speed (ATS); an LOS indicator for the subject road class is determined. The Highway Capacity Manual (HCM) 2010 offers an indirect method for field estimation of FSS based on the highway operating conditions in terms of base-free-flow-speed (BFFS). It is however, recommended by the same manual that direct field FSS measurement approach is most preferred. The Malaysian Highway Capacity Manual (MHCM) established a model for estimating FFS based on BFFS, the geometric features of the highway and proportion of motorcycles in the traffic stream. Estimating FFS based on BFFS is regarded as an indirect approach which is only resorted to, if direct field measurement proved difficult or not feasible. This paper presents the application of moving car observer (MCO) method for direct field measurement of FFS. Data for the study were collected on six segments of two-lane highways with varying geometric features. FFS estimates from MCO method were compared with those based on MHCM model. Findings from the study revealed that FFS values from MCO method seem to be consistently lower than those based on MHCM model. To ascertain the extent of the difference between the FFS values from the two approaches, student t-statistics was used. The t-statistics revealed a P–value of less than 0.05 (P < 0.05) which implies that there is a statistically significant difference between the two sets of data. Since MCO method was conducted under low traffic flow (most desired condition for field observation), it can be suggested that MCO estimates of FFS represent the actual scenario. A relationship was therefore developed between the estimates from the two methods. Thus, if the MHCM model is to be applied, the measured value needs to be adjusted based on the relationship developed between the two approaches.


2018 ◽  
Vol 181 ◽  
pp. 06006
Author(s):  
Najid

Value of Passenger Car Unit or commonly known as PCU value is a value that is given to any vehicle that is classified into heavy vehicles, light vehicles (passenger car) and motorcycles. The value of passenger car unit on Indonesia Highway Capacity Manual (IHCM) set up in 1997 is based on a study conducted from 1980-1990 in several cities in Indonesia At the time of the study, the traffic conditions are very different to the current traffic conditions. That affects of difference traffic conditions are the composition of traffic, traffic regulations, traffic density, traffic discipline and the presence of mass transit, so that the results of traffic analysis do not always correspond to reality as there are anomalies in the determination of the level of road service (Najid, 2014). As well the incompatibility of the capacity value which is considered due to the incompatibility value of Passenger Car Units (PCU). Evaluation PCU become very important to get the value of traffic parameters into compliance with actually occur. In accordance with the traffic density is higher actually, then it is necessary to study for evaluation against PCU current value and the need to approach or to get the value of PCU more in line with current traffic conditions. Data collected at two cities, those are Bandung and Semarang. Based on analysis found PCU’s value that got from survey have difference but not all significantly with PCU value in IHCM.


1976 ◽  
Vol 3 (3) ◽  
pp. 355-371
Author(s):  
John F. Morrall ◽  
Neville Cameron ◽  
Al Werner

Trans-mountain highway capacity is sensitive to the percentage of recreational vehicles in the traffic stream, the manner in which passenger car equivalents for recreational vehicles are used in capacity computations, terrain classification, and the choice of design hourly volume. The sensitivity of capacity to these factors is demonstrated for the trans-mountain portion of the Trans-Canada highway which is a two-lane highway, characterized in many locations by long steep grades. This particular highway has a high percentage of recreational vehicles during summer months. The Highway Capacity Manual does not make any provision for the effect of such vehicles and previous highway planning studies have used the adjustment factors for trucks and buses to estimate their effect. Neglecting the effect of recreational vehicles and/or improper use of their passenger car equivalents in capacity computations can result in serious errors in the determination of highway capacity especially in mountainous areas. Further research is required in the areas of terrain definition, selection of design hourly volume, and the present concept of level of service.


Author(s):  
Jianan Zhou ◽  
Laurence Rilett ◽  
Elizabeth Jones

In the 2016 Highway Capacity Manual (HCM-6), the impact of trucks on freeway operations is measured by passenger car equivalents (PCEs). PCEs are estimated by the equal capacity methodology. The HCM-6 PCE values are based on the assumptions that passenger cars and trucks travel at the same free-flow speed, that they travel on freeways with three lanes per direction, and that they travel in traffic with no more than 25% trucks. On Interstate 80 in western Nebraska, it is observed that the interaction of high truck percentages and large speed differences between passenger cars and trucks may result in moving bottlenecks. It was hypothesized that the current HCM-6 PCEs may be not appropriate for these conditions. A companion paper showed this was true and that the major cause was speed differentials between trucks and passenger cars. In essence, when slow-moving trucks pass each other they create moving bottlenecks, which results in increased PCE values. This paper is an extension to a companion paper and examines a number of issues related to estimation of PCEs. The paper examines the effect of speed limit, truck passing restrictions, and data aggregation interval on PCEs. The results show that: (i) if a higher speed limit is implemented, trucks will affect the passenger cars more severely; (ii) if truck passing is restricted by lane restrictions, the negative impacts of trucks on passenger car operation may be mitigated; and (iii) using a longer data aggregation interval results in lower PCE values, all else being equal.


2010 ◽  
Vol 37 (1) ◽  
pp. 77-87 ◽  
Author(s):  
Shy Bassan ◽  
Abishai Polus

The flow on urban and suburban freeways is characterized typically by high densities, occupancies, and frequent breakdowns, particularly when the volume approaches capacity. This creates unstable flow conditions, resulting in recurrent as well as random congestion. The purpose of this study was twofold: (1) to develop models for evaluating flow characteristics on a busy suburban freeway, specifically speed versus flow and flow versus occupancy; (2) to understand the meaning of capacity by evaluating the actual capacity of a freeway section. The data were collected on Highway 1 in Israel and on Interstate 66 in Virginia, USA. Previous observations showed that both freeways operated at a saturated-flow condition almost daily and that breakdowns of the stream occurred often, though not daily. The paper presents a concept that suggests that freeway capacity is an actual-site specific term. This capacity can change frequently in space and time, depending on the section geometry, the time interval, the prevailing traffic and environmental conditions, and driving behavior. Determination of a representative value of actual capacity for level-of-service or planning analyses is suggested, based on one of three methods: parabolic curve-fitting for free-flow, dense congested stable (DCS) flow, and breakdown-flow data; the intersection of the best-fit stable-flow parabola and the equal-density adjusted line; and curve fitting of one-regime models to flow-occupancy data. Also included is a comparison with the 2000 Highway capacity manual (HCM) models and with capacity estimates from other studies. The results showed similar values of actual capacity estimates for the three methods.


Transport ◽  
2016 ◽  
Vol 31 (2) ◽  
pp. 295-303 ◽  
Author(s):  
Orazio Giuffrè ◽  
Anna Granà ◽  
Sergio Marino ◽  
Fabio Galatioto

Due to its geometric design, turbo-roundabouts impose greatest constraints to the vehicular trajectories; by consequence, one can expect a more unfavourable impact of heavy vehicles on the traffic conditions than on other types of roundabouts. The present paper addresses the question of how to estimate Passenger Car Equivalents (PCEs) for heavy vehicles driving turbo-roundabouts. The microsimulation approach used revealed as a useful tool for evaluating the variation of quality of traffic in presence of mixed fleets (different percentages of heavy vehicles). Based on the output of multiple runs of several scenarios simulation, capacity functions for each entry lane of the turbo-roundabout were developed and variability of the PCEs for heavy vehicles were calculated by comparing results for a fleet of passenger cars only with those of the mixed fleet scenarios. Results show a dependence of PCEs for heavy vehicles on operational conditions, which characterise the turbo-roundabout. Assuming the values of PCEs for roundabouts provided by the 2010 Highway Capacity Manual (HCM), depending on entering manoeuvring underestimation and overestimation of the effect of heavy vehicles on the quality of traffic conditions have been found.


Author(s):  
Madhav V. Chitturi ◽  
Rahim F. Benekohal

Traffic data were collected from 11 work zones on Interstate highways in Illinois in which one of the two lanes was open. The reductions in free-flow speed (FFS) due to narrow lanes and lateral clearances in work zones were studied. It was found that the reductions in FFSs of vehicles in work zones because of narrow lanes were higher than the reductions given in the Highway Capacity Manual for basic freeway sections. The data also showed that the narrower the lane was, the greater the speed reduction was. The data showed that the FFSs of heavy vehicles were statistically lower than the FFSs of passenger cars, even though the speed limit was the same for both types of vehicles. In addition, the reduction in the FFSs of heavy vehicles was greater than the reduction in the FFSs of passenger cars. This greater reduction in the speed of heavy vehicles affected the performance of the traffic stream in work zones. Thus, it should be considered in the computation of the passenger car equivalence for heavy vehicles. It is recommended that 10, 7, 4.4, and 2.1 mph be used for speed reduction in work zones for lane widths of 10, 10.5, 11, and 11.5 ft, respectively.


2017 ◽  
Vol 29 (2) ◽  
pp. 135-142 ◽  
Author(s):  
Habibollah Nassiri ◽  
Sara Tabatabaie ◽  
Sina Sahebi

Due to their different sizes and operational characteristics, vehicles other than passenger cars have a different influence on traffic operations especially at intersections. The passenger car equivalent (PCE) is the parameter that shows how many passenger cars must be substituted for a specific heavy vehicle to represent its influence on traffic operation. PCE is commonly estimated using headway-based methods that consider the excess headway utilized by heavy vehicles. In this research, the PCE was estimated based on the delay parameter at three signalized intersections in Tehran, Iran. The data collected were traffic volume, travel time for each movement, signalization, and geometric design information. These data were analysed and three different models, one for each intersection, were constructed and calibrated using TRAF-NETSIM simulation software for unsaturated traffic conditions. PCE was estimated under different scenarios and the number of approach movements at each intersection. The results showed that for approaches with only one movement, PCE varies from 1.1 to 1.65. Similarly, for approaches with two and three movements, the PCE varies from 1.07 to 1.99 and from 0.76 to 3.6, respectively. In addition, a general model was developed for predicting PCE for intersections with all of the movements considered. The results obtained from this model showed that the average PCE of 1.5 is similar to the value recommended by the HCM (Highway Capacity Manual) 1985. However, the predicted PCE value of 1.9 for saturated threshold is closer to the PCE value of 2 which was recommended by the HCM 2000 and HCM 2010.


2021 ◽  
Vol 2021 (1) ◽  
pp. 50-59
Author(s):  
Vsevolod Prykhodko ◽  
◽  
Ihor Vikovych ◽  

In this paper, several methods of the assessment of pedestrian objects operation based on the level of service are reviewed. Today, there is a problem that should be assessed, particularly how pedestrian paths respond the level of service. Assessment of this level is the most widespread method of determination the objects` quality that relate to the pedestrian operations. Places, where a significant probability of conflict between different flows and their users, are often called intersections. Moreover, on such intersections, particularly with complex road conditions and on which the movement of cyclists, cars, and different vehicles is present, road users face with complicated situations when every of them should be sure in his safety and forecast further actions and decisions of other road users. The most widespread and generally accepted methods of assessment of level of service on pedestrian path, particularly: Highway capacity manual 2000 method, Australian method, method of the trip quality, Landice model and common approach analysis. Vehicles, signal delay, and interaction of pedestrians and cyclists were determined as the main factors that have impact on the level of service of pedestrians at the intersections. Analysis of different methods in the paper allows assessing and identifying the level of service determining the characteristics that could help in solving the questions concerning the comfort of pedestrian movement. In the range of these methods, the principles of vehicles movement and interaction with pedestrians are also reviewed. Other methods relate more to the design of the objects of pedestrian environment than factual movement of pedestrians. To form the whole understanding of the methodology of determination of the level of service of pedestrian objects, we should analyze and compare the values, obtained by different methods.


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