Derivation of Van Aerde Traffic Stream Model from Tandem-Queuing Theory

2009 ◽  
Vol 2124 (1) ◽  
pp. 18-27 ◽  
Author(s):  
Ning Wu ◽  
Hesham Rakha
Keyword(s):  
Queuing Theory ◽  
Traffic Stream ◽  
Tandem Queuing ◽  
Stream Model

An s-shaped three-parameter (S3) traffic stream model with consistent car following relationship

2021 ◽  
Vol 153 ◽  
pp. 246-271
Author(s):  
Qixiu Cheng ◽  
Zhiyuan Liu ◽  
Yuqian Lin ◽  
Xuesong (Simon) Zhou
Keyword(s):  
Car Following ◽  
Traffic Stream ◽  
Stream Model

scholarly journals Car Delay Model near Bus Stops with Mixed Traffic Flow

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Yang Xiaobao ◽  
Huan Mei ◽  
Gao Ziyou
Keyword(s):  
Probability Theory ◽  
Traffic Flow ◽  
Queuing Theory ◽  
Delay Model ◽  
Mixed Traffic ◽  
Average Delay ◽  
Mixed Traffic Flow ◽  
Operation Conditions ◽  
Traffic Stream ◽  
Bus Stops

This paper proposes a model for estimating car delays at bus stops under mixed traffic using probability theory and queuing theory. The roadway is divided to serve motorized and nonmotorized traffic streams. Bus stops are located on the nonmotorized lanes. When buses dwell at the stop, they block the bicycles. Thus, two conflict points between car stream and other traffic stream are identified. The first conflict point occurs as bicycles merge to the motorized lane to avoid waiting behind the stopping buses. The second occurs as buses merge back to the motorized lane. The average car delay is estimated as the sum of the average delay at these two conflict points and the delay resulting from following the slower bicycles that merged into the motorized lane. Data are collected to calibrate and validate the developed model from one site in Beijing. The sensitivity of car delay to various operation conditions is examined. The results show that both bus stream and bicycle stream have significant effects on car delay. At bus volumes above 200 vehicles per hour, the curbside stop design is not appropriate because of the long car delays. It can be replaced by the bus bay design.

scholarly journals A Novel Traffic Stream Model Deriving from a Bimodal Kinetic Equilibrium 1

1997 ◽  
Vol 30 (8) ◽  
pp. 771-776 ◽  
Author(s):  
Paul Nelson ◽  
Dat Duc Bui ◽  
Alexandros Sopasakis
Keyword(s):  
Traffic Stream ◽  
Stream Model ◽  
Kinetic Equilibrium

scholarly journals Stochastic Model of Ships Traffic Capacity and Congestion — Validation by Real Ships Traffic Data on Świnoujście — Szczecin Waterway

2017 ◽  
Vol 24 (1) ◽  
pp. 177-191 ◽  
Author(s):  
Lucjan Gucma ◽  
Andrzej Bąk ◽  
Sylwia Sokołowska
Keyword(s):  
Monte Carlo ◽  
Stochastic Model ◽  
Main Parameter ◽  
Real Data ◽  
Model Output ◽  
Traffic Data ◽  
Traffic Capacity ◽  
Traffic Stream ◽  
Separate Object ◽  
Stream Model

AbstractPaper presents validation of previously created stochastic ships traffic stream model by the real data of ships delays on Świnoujście — Szczecin waterway. The model is mostly based on Monte Carlo methodology. The model is microscopic which means that each ship’s model is treated as separate object possessing given attributes. As the main parameter of presented validation total waiting (delay) time of ships have been applied. The time of ships delays was possessed from Szczecin VTS centre and compared with the model output.

scholarly journals Calibration of the empirical fundamental relationship using very large databases

TRANSPORTES ◽  
2021 ◽  
Vol 29 (1) ◽  
pp. 212-228
Author(s):  
Juliana Mitsuyama Cardoso ◽  
Lucas Assirati ◽  
José Reynaldo Setti
Keyword(s):  
Model Fitting ◽  
Traffic Monitoring ◽  
Metropolitan Region ◽  
Model Parameters ◽  
Inaccurate Data ◽  
Fundamental Relationship ◽  
Large Databases ◽  
Traffic Stream ◽  
Very Large Databases ◽  
Stream Model

This paper describes a procedure for fitting traffic stream models using very large traffic databases. The proposed approach consists of four steps: (1) an initial treatment to eliminate noisy, inaccurate data and to homogenize the information over the density range; (2) a first fitting of the model, based on the sum of squared orthogonal errors; (3) a second filter, to eliminate outliers that survived the initial data treatment; and (4) a second fitting of the model. The proposed approach was tested by fitting the Van Aerde traffic stream model to 104 thousand observations collected by a permanent traffic monitoring station on a freeway in the metropolitan region of São Paulo, Brazil. The model fitting used a genetic algorithm to search for the best values of the model parameters. The results demonstrate the effectiveness of the proposed approach.

scholarly journals Derivation of Van Aerde Traffic Stream Model and Studying the Effect of Ramp Metering

2015 ◽  
Vol 1 (2) ◽  
pp. 1
Author(s):  
Karan Arora ◽  
Saeid Saidi ◽  
Bidoura Khondaker ◽  
Lina Kattan
Keyword(s):  
Traffic Flow ◽  
Ramp Metering ◽  
Traffic Condition ◽  
Traffic Demand ◽  
Flow Models ◽  
Traffic Stream ◽  
Traffic Flow Models ◽  
Government Of Canada ◽  
Stream Model ◽  
Evening Peak

With increase in population, demand for traffic is increasing tremendously. As a consequence congestion on urban freeways or highways during the morning and evening peak hours is always increasing. This research examines the traffic condition on Highway 2(i.e Deerfoot Trail), Calgary,Canada by providing ramp metering (funded by Government of Canada in Collaboration with MITACS Globalink Program). In order to accommodate increasing traffic demand, constructing new highways and adding lanes is not always the best option. Instead proper management of transportation system can help in increasing its efficiency. It is therefore important to increase our understanding of traffic flow models to help estimating the efficiency of different road facilities and therefore prepare us to make enlightened decisions in the design process of new road facilities or improving older ones.

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