scholarly journals Determining passenger car equivalent (PCEs) for pretimed signalized intersections with severe motorcycle composition using Bayesian linear regression

PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0256620
Author(s):  
Sugiarto Sugiarto ◽  
Fadhlullah Apriandy ◽  
Yusria Darma ◽  
Sofyan M. Saleh ◽  
Muhammad Rusdi ◽  
...  
Keyword(s):  
Linear Regression ◽  
Heterogeneous Traffic ◽  
Signalized Intersection ◽  
Common Source ◽  
Passenger Car ◽  
Traffic Characteristics ◽  
Bayesian Linear Regression ◽  
Passenger Car Equivalent ◽  
Saturation Flow ◽  
Traffic Operation

Pretimed signalized intersection is known as a common source of congestion, especially in urban heterogeneous traffic. Furthermore, the accuracy of saturation flow rate is found to cause efficient and vital capacity estimation, in order to ensure optimal design and operation of the signal timings. Presently, the traffic also consists of diverse vehicle presence, each with its own static and dynamic characteristics. The passenger car equivalent (PCE) in an essential unit is also used to measure heterogenous traffic into the PCU (Passenger Car Unit). Based on the collection of observed data at three targets in Banda Aceh City, this study aims to redetermine the PCEs by using Bayesian linear regression, through the Random-walk Metropolis-Hastings and Gibbs sampling. The result showed that the obtained PCE values were 0.24, 1.0, and 0.80 for motorcycle (MC), passenger car (PC), and motorized rickshaw (MR), respectively. It also showed that a significant deviation was found between new and IHCM PCEs, as the source of error was partially due to the vehicle compositions. The present traffic characteristics were also substantially different from the prevailing conditions of IHCM 1997. Therefore, the proposed PCEs enhanced the accuracy of base saturation flow prediction, provided support for traffic operation design, alleviated congestion, and reduced delay within the city, which in turn improved the estimation of signalized intersection capacity.

Saturation Flow Model for Signalized Intersection under Mixed Traffic Condition

2018 ◽  
Vol 2672 (15) ◽  
pp. 55-65 ◽  
Author(s):  
Sabyasachi Biswas ◽  
Souvik Chakraborty ◽  
Indrajit Ghosh ◽  
Satish Chandra
Keyword(s):  
Conventional Method ◽  
Detailed Comparison ◽  
Heterogeneous Traffic ◽  
Signalized Intersection ◽  
Percentage Error ◽  
Mixed Traffic ◽  
Kriging Method ◽  
Traffic Condition ◽  
Saturation Flow ◽  
The Impact

Saturation flow is one of the most important functional parameters at signalized intersections. It is to be noted that saturation flow is a functional measure of the intersection operation, which indicates the probable capacity if working in an ideal situation. However, determination of the saturation flow is a challenging task in developing countries like India where vehicles with diverse static and dynamic characteristics use the same carriageway. At the same time, it is influenced by several other factors. In this context, the present research is carried out to examine the effects of traffic composition, approach width and right-turning movements on saturation flow under heterogeneous traffic conditions. This paper proposes a model for computing saturation flow at the signalized intersection under mixed traffic condition based on Kriging approach. A detailed comparison of the mean saturation flow values obtained by the conventional method, regression method, and Kriging method has also been presented. Low mean absolute percentage error values (<5%) have been obtained for saturation flow by Kriging method with respect to the conventional method. Finally, the proposed models are used to evaluate the impact of right-turning vehicles on saturation flow under shared lane condition.

scholarly journals Delay-based Passenger Car Equivalent at Signalized Intersections in Iran

2017 ◽  
Vol 29 (2) ◽  
pp. 135-142 ◽  
Author(s):  
Habibollah Nassiri ◽  
Sara Tabatabaie ◽  
Sina Sahebi
Keyword(s):  
Signalized Intersections ◽  
Simulation Software ◽  
Heavy Vehicles ◽  
Passenger Cars ◽  
Highway Capacity ◽  
Passenger Car ◽  
Highway Capacity Manual ◽  
Operational Characteristics ◽  
Passenger Car Equivalent ◽  
Traffic Operation

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.

Measuring the Passenger Car Equivalent of Small Cars and SUVs on Rainy and Sunny Days

2018 ◽  
Vol 2672 (31) ◽  
pp. 110-119 ◽  
Author(s):  
Majid Zahiri ◽  
Xiqun (Michael) Chen
Keyword(s):  
Field Investigation ◽  
Urban Traffic ◽  
Heterogeneous Traffic ◽  
Motor Vehicles ◽  
Mixed Traffic ◽  
Passenger Cars ◽  
Passenger Car ◽  
Passenger Car Equivalent ◽  
The Government ◽  
Rainy Days

Traffic volume is a fundamental measurement in traffic analyses. In mixed traffic, vehicles vary in size, length, headway, spacing, and acceleration/deceleration. Therefore, if we can categorize the vehicles in mixed traffic in greater detail, the estimated passenger car equivalent (PCE) number will be more accurate. Practical and appropriate methods that convert different vehicles into the equivalent number of passenger cars need to be employed to determine PCE factors for heterogeneous traffic. Following economic growth and increased use of motor vehicles in developing countries, the purchase of sports utility vehicles (SUVs) continues to grow, though the government encourages people to buy small cars because of the limited road capacity, as well as air pollution problems. In this research, we categorize passenger cars into three subsets: small cars (hatchback cars without a trunk), SUVs, and standard cars (taxis and typical family cars). A field investigation shows that the penetration rates of these passenger cars are 12%, 23%, and 55%, respectively (10% are other vehicles) in Hangzhou, China. We also measure the PCE value for small cars and SUVs using the mean time headway method. Because different countries have different weather conditions, we continue to measure the PCE values for sunny days and moderate rainy days. The results show that PCE values for small cars and SUVs are 0.87 and 1.26 on sunny days, and 0.87 and 1.31 on rainy days, respectively. By using the PCE with high precision, urban managers can accomplish the analysis of urban traffic with greater accuracy.

scholarly journals Passenger Car Equivalent Estimation Methods of Trucks in Traffic Stream

2020 ◽  
Vol 8 (5) ◽  
pp. 710-716
Keyword(s):  
Performance Measures ◽  
Heterogeneous Traffic ◽  
Estimation Methods ◽  
Tabular Form ◽  
Static Characteristics ◽  
Passenger Car ◽  
Flow Rates ◽  
Passenger Car Unit ◽  
Traffic Stream ◽  
Passenger Car Equivalent

In Most Of Developing Countries, The Traffic Is Heterogeneous In Nature Consisting Of Wide Variety Of Vehicles Having Different Dynamic And Static Characteristics. Passenger Car Unit (PCU) / Passenger Car Equivalent (PCE) Values Show A Vital Job In Changing Over Heterogeneous Traffic Stream Into Comparable Homogeneous Traffic, Which Comprises Of Traveller Vehicles As It Were. PCE Values Are Vital In Rush Hour Gridlock Stream Investigations. This Paper Reviews The Previous Researches Carried Out About The Estimation Of Passenger Car Equivalents With Different Performance Measures At Mid-Block Sections And Summarizes PCE Variation With Percentage Of Trucks And Flow Rates In The Tabular Form.

scholarly journals HTPC: heterogeneous traffic-aware partition coding for random packet spraying in data center networks

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Jiawei Huang ◽  
Shiqi Wang ◽  
Shuping Li ◽  
Shaojun Zou ◽  
Jinbin Hu ◽  
...  
Keyword(s):  
Data Center ◽  
Large Scale ◽  
Network Performance ◽  
Rooted Tree ◽  
Heterogeneous Traffic ◽  
Data Center Networks ◽  
Packet Reordering ◽  
Traffic Characteristics ◽  
Network Utilization ◽  
The Impact

AbstractModern data center networks typically adopt multi-rooted tree topologies such leaf-spine and fat-tree to provide high bisection bandwidth. Load balancing is critical to achieve low latency and high throughput. Although the per-packet schemes such as Random Packet Spraying (RPS) can achieve high network utilization and near-optimal tail latency in symmetric topologies, they are prone to cause significant packet reordering and degrade the network performance. Moreover, some coding-based schemes are proposed to alleviate the problem of packet reordering and loss. Unfortunately, these schemes ignore the traffic characteristics of data center network and cannot achieve good network performance. In this paper, we propose a Heterogeneous Traffic-aware Partition Coding named HTPC to eliminate the impact of packet reordering and improve the performance of short and long flows. HTPC smoothly adjusts the number of redundant packets based on the multi-path congestion information and the traffic characteristics so that the tailing probability of short flows and the timeout probability of long flows can be reduced. Through a series of large-scale NS2 simulations, we demonstrate that HTPC reduces average flow completion time by up to 60% compared with the state-of-the-art mechanisms.

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