COMPARATIVE ANALYSIS OF DELAY AND SATURATION FLOW USING VARIOUS PCU ESTIMATION METHODS

Heterogeneous traffic existing in developing countries such as in India is characterized by vehicles with very diverse static and dynamic characteristics. The various types of vehicles, other than cars in the heterogeneous traffic stream can be converted into equivalent passenger cars so as to express the heterogeneous traffic volume in terms of corresponding passenger car units (PCU). The subject of PCU has been studied on intercity, urban roads and at intersections controlled by traffic signals quite extensively. But studies on PCU values of vehicles on the downstream of signalized intersections have not been explored so far. The arterial links existing at downstream of traffic signals are designed to progress traffic with varying acceleration and deceleration. Vehicular interactions which take place within platoons and between platoons along such arterials are the predominant factors affecting vehicular progression. Hence there is a need to derive PCU values of vehicles along signalized corridors. The present study analyzes traffic flow data collected at the downstream of a signalized urban arterial to determine PCU values for various types of vehicles based on three methods. One method is the homogenisation coefficient method whereas the other one is the speed-area ratio method. The third one is a new method based on speed differential and area ratio is proposed in this paper which considers the effect of speed variation of vehicles for estimating PCU values. In this study, PCU values estimated based on speed differential-area ratio concept are found to be more logical compared to other methods as this method could incorporate the considerable variation in static and dynamic characteristics of various vehicles which progress along the downstream of intersections.

This study proposes a time occupancy approach to estimate passenger car units (PCUs) at urban signalized intersections with different interaction levels between vehicles under saturated green time conditions. The study shows a variation in PCUs with varied traffic and geometric conditions. Traffic data have been collected through videography techniques at signalized intersections in three metropolitan cities in India. Traffic flow discharge and clearance time of different vehicular categories have been extracted from the video during the saturated green time. The observed ranges of dynamic PCU values for two-wheelers, three-wheelers, big cars, light commercial vehicles, and heavy vehicles are 0.12 to 0.32, 0.45 to 0.80, 1.40 to 1.80, 1.60 to 2.20, and 3.50 to 6.50, respectively. Regression-based PCU models have been developed for each vehicle category to address the variation of individual vehicle PCUs with traffic compositions and flow rates. The model analysis shows that traffic compositions and flow rates are significantly affecting the PCU values. The PCU is a complex parameter requiring several field attributes. Therefore, to overcome the complexity of estimating PCUs, a concept of flow equivalency factor (FEF) has been proposed based on the estimated PCUs. The FEF can directly convert the mixed motorized vehicular flow into an equivalent standard passenger car flow without actually making use of different vehicles’ PCU factors. All the developed models have been validated for field conditions and results are found promising with field data. The developed approach can be used effectively for developing countries with a mixed traffic stream.

This study demonstrates that passenger car unit (PCU) values for a vehicle are not static and vary with traffic volume and composition. Data collected at eight urban arterial roads in India were analyzed to explain the dynamic nature of the PCU factor. All vehicles in the traffic stream were divided into five categories, and simultaneous equations were developed to determine the speed of a vehicle type from information on traffic volume and composition. These equations were used to show the variation in PCU values with traffic volume and composition on a road. The change in PCU values was explained on the basis of the relative interaction of vehicle type in the traffic stream at different volume levels. A proposed range of PCU values for big vehicles was from 1.47 to 1.65 for big cars and for heavy vehicles from 5.51 to 6.54, respectively, when their proportions in the mix remained within an observed range in the field. Similarly, a range of PCU values for motorized three-wheelers of 0.99 to 1.01 and a set of PCU values for motorized two-wheelers of 0.20 to 0.23 were obtained. Accuracy of the PCU values estimated through simultaneous equations was checked by comparing the estimated values with those calculated directly from the field data. Statistical testing showed that there was no significant difference between field-estimated and model-predicted PCU values. Further, the speed–volume relationships developed by using two sets of PCU factors yielded the capacity values with a difference of less than 2%; this result indicates the correctness of the methodology in this study.

Traffic-related analyses are essential to implementing traffic management approaches to create mobility more convenient. In this context, Passenger Car Unit (PCU) values as a uniform measure of vehicles are instrumental in analysis such as traffic capacity estimation, traffic flow model development, level of service determination, etc. These studies always demand a recently calculated set of PCU values since the traffic conditions in arterials often change. PCU values for expressway and three-lane (one-way) road types have not been calculated in the Sri Lankan context, and the available set of values has become somewhat outdated. Hence, this study used Chandra's method to assess the PCU values of ten vehicle categories for four different mid-block road sections in the Colombo district, Sri Lanka. The data relating to the two main variables of this method, categorical speed, and area of vehicles, were collected from field surveys. The results of four-lane arterials were aggregated and compared with the existing PCU values, intending to propose an updated set for general transportation studies in Sri Lanka.

Despite the adoption of roundabouts in developing countries for traffic management and smooth flow, the concept of traffic heterogeneity management at these intersections is relatively unexplored. Estimating passenger car units (PCUs) for different vehicle types to homogenize traffic is a recognized approach worldwide. In this study, vehicles were classified into five categories to provide a meaningful context for the analysis. The study proposes a model to estimate PCU values for different vehicle types, specifically at roundabouts, after identifying the potential influencing factors. The study was based on data collected from 10 roundabouts in three Indian cities, having different physical and geometrical characteristics. The proposed method yielded PCU values that were partially comparable with existing standards. Comparisons with the Indian Highway Capacity Manual (Indo-HCM) revealed that this publication underestimated PCU values for two-wheelers and three-wheelers by 20% and 11% respectively, but overestimated PCU values for big cars and heavy vehicles by 9% and 12%, respectively. Method appropriateness was ascertained from the lack of prior assumptions made about traffic and geometrical characteristics. To prevent unnecessary re-estimation of PCU values across locations, the idea of a heterogeneity counter component (HCC) was proposed. The model was trained using cross validation on a dataset of seven roundabouts, and its performance was evaluated on a separate dataset using mean absolute percentage error. The relationship between PCUs and the geometrical features of roundabouts, and the effect of traffic characteristics on HCC were studied. The findings might be considered while revising relevant codes and manuals (e.g., IRC-65:2017, Indo-HCM).

Development of Saturation Flow Model at Signalized Intersection for Heterogeneous Traffic

Estimation of Passenger Car Unit on urban roads: A literature review

Passenger car units in saturation flows: Concept, definition, derivation

This paper introduces a novel genetic algorithm (GA)-based optimization model for estimating passenger car units (PCUs) at roundabouts using occupancy time, addressing limitations in the existing methods that overlook traffic heterogeneity. The GA-based model achieved dynamic PCU values with a mean absolute error (MAE) of 3%–6% and a maximum error of 9%–10%, ensuring model simplicity and adaptability through the bias–variance trade-off technique. By estimating PCU values for different vehicle classes and analyzing roundabout geometry and traffic parameters, the model demonstrated high prediction accuracy with R -squared values between 0.995 and 0.998. Overfitting and underfitting were addressed by splitting data into training and testing sets and monitoring MAE changes. The model precision, reliability, and robustness were validated using multiple performance metrics. Monte Carlo sensitivity analysis and single-input single-output analysis assessed the relative importance of input parameters.

Traffic flow consists from various types of vehicles, and it requires a conversion value to represent the traffic flow more accurately in terms of the standard vehicle type, namely passenger cars, commonly referred to as Passenger Car Units (PCU). The conversion factor from different types of vehicles to passenger cars is called Passenger Car Equivalence (PCE). In calculating road capacity in Indonesia, the PCE value used refers to Manual Kapasitas Jalan Indonesia (MKJI) 1997.In this study, a method called the time headway method is used to determine the Passenger Car Equivalence (PCE) value. This method involves recording the convoy of vehicle pairs per green time. The time headway value is obtained from the time difference between two vehicles passing a reference line, which is the stop line, calculated from the front bumper of the preceding vehicle to the front bumper of the following vehicle.Based on the research results, the PCE value using the Time Headway method for motorcycles (MC) at a three-phase intersection located at the signalized intersection of Panca Usaha Street - Bung Hatta Street is 0.57. Meanwhile, at a four-phase intersection located at the signalized intersection of Dr. Sujono Street - TGH Lopan Street, the PCE values for motorcycles (MC) and heavy vehicles (HV) are 0.34 and 2.23, respectively. There are differences in PCE values between MKJI 1997 and the results of the Time Headway method calculation for protected-type signalized intersections, which are 0.2 for motorcycles (MC) and 1.3 for heavy vehicles (HV). These differences occur due to changes in field conditions, such as an increase in the number of vehicles in the intersection arms and changes in green time at intersections

Total cost of ownership, payback, and consumer preference modeling of plug-in hybrid electric vehicles

This study evaluates the operational performance of Serdang Intersection, an unsignalized three-leg junction located in a commercial area connecting Serang–Cilegon Road and Waringinkurung Road. The assessment combines analytical procedures from the Indonesian Highway Capacity Manual 2023 and microsimulation modelling using PTV Vissim software. Analysis of current conditions shows a traffic flow of 3206 passenger car units per hour, a degree of saturation of 0.75, an average delay of 12.75 seconds per passenger car unit, and a queue probability ranging from 23 percent to 46 percent, corresponding to level of service B. Projections for 2033 indicate that traffic flow will increase to 4602 passenger car units per hour, the degree of saturation will exceed capacity at 1.08, average delay will rise to 23.80 seconds per passenger car unit, and queue probability will reach 47 percent to 94 percent, resulting in level of service D. These findings underscore the urgency of infrastructure interventions such as intersection geometry optimization, priority lane adjustments, and the installation of traffic signals to mitigate congestion risks. The study demonstrates the effectiveness of integrating the Indonesian Highway Capacity Manual 2023 with microsimulation modelling using PTV Vissim (Planning Transport Traffic-Traffic in Cities Simulation Model) in comprehensively forecasting traffic performance, and it offers strategic recommendations for urban planners and policymakers.

Economic growth involves massive movement of logistics, where goods transported by land become the main choice by supplier. One of them being the main access for connecting Java and Sumatera is the Tangerang – Merak toll road. An increase in traffic volume occurs every year, followed by additional problems such as congestion which obviously affects traffic performance. Given this reason, it is necessary to evaluate traffic performance through parameter assessments, which are the degree of saturation and travel speed. This research was carried out on the Tangerang - Merak toll road section KM 32,300 to KM 35,500 towards Jakarta for one week using traffic CCTV recordings, then selected on 17 April 2024. The calculation results obtained for each average weighted value for the degree of saturation (Ds) at 0.36 and average of the Space Mean Speed is at 33.08 kph. Based on traffic performance analysis, the volume parameter does not indicate a problem, and is included in the LOS A category. However, the travel speed parameter shows an issue and included in the LOS F category. This will be the focus problem within the scope of the research. On the other side, traffic composition which includes variations in the number of vehicles per time and type of vehicle. Given this kind of variation, a Passenger Car Unit value is needed that can equalize the existing different vehicle types into a uniform standard, including who commit over dimensional violations. Where the value of passenger car equivalent of an over-dimensional vehicle is changing, it is necessary to re-calibrate the emp value. Researchers used the Volume Delay Function formula to calculate travel time, then explore a combination of emp values using the dynamic programming method by comparing survey travel time with the simulation one. The difference between the PKJI standard value and the calibrated pce value proves the problem of these vehicles commit over dimension violations on the Tangerang – Merak toll road. For this reason, it is hoped that this research which evaluate traffic performance, travel time and passenger car equivalent values, can be used as a basis for further policy making to improve the performance of the Tangerang – Merak toll road.

Movement in non-rural areas effects well-being as well as traffic of that area. Greater the congested activity, worse will be the traffic impacts. These traffic impacts can be minimized by movement diminishment, or by moving more passengers from personal to alternate methods of transport with less negative effects for which a comprehensive traffic study needs to be done. In the present study, Phagwara, area of Jalandhar has been taken for such analysis. These studies can be used to control traffic jams on roads due to increment in vehicles. The study can also be used for saving time at intersections. Travel time data is an important parameter of many Intelligent Transportation Systems/Frameworks (ITS) applications. Quantity of vehicles in India has been increasing enormously resulting in blockage and pollution of urban areas during peak periods. If we can control congestion to a certain limit, things like pollution will also get minimized and there will be less accident rate due to less delay to the road users. This all is possible only when we are able to shift more passengers from their personal vehicles to public transport/ vehicles by providing them better comfort and good services. We can also provide latest technologies to the public vehicles so that the passenger gets attracted to these facilities. For achieving the goal, Advanced Public Transportation System/ Frameworks (APTS) plays a great role. ITS applications should be added to the movement circumstances in India so as to reduce the effects caused by traffic congestion. India is a developing country and has low economy rate so this is not possible for any developing country to implement in each and every city. Our main aim is to find out the traveller/ Passenger Car Unit (PCU) for many types of vehicles in non-homogeneous situations. The study shows that the traffic volume increasing enormously with non-homogeneous traffic on the roadway of Six-Laned Two-way traffic. The relation between volume of traffic and speed of vehicles represents third- and fourth-degree curve.

Traffic Modeling and Safety Analysis on Motorway Ramps