Refinement Methodology for Modeling of Urban Road Traffic Networks

2011 ◽  
Vol 186 ◽  
pp. 520-524 ◽  
Author(s):  
Hao Yue

This paper proposes a modular frame based on hybrid Petri nets for modeling the signalized urban traffic network for control purpose. A kind of level of detail modeling methodology is used. After an aggregate model of the urban traffic network system is defined, the key elements such as traffic lights and intersections, which describe the typical feature of the traffic network in the aggregate model, are refined to introduce detail models. The proposed model of the intersection describes the turning direction of each traffic flow explicitly and takes into account the conflicts among the traffic flows. Furthermore, the time factor is considered in the system model. As a result, the total model obtained can not only reflect the logical relationship among the traffic flows, but also describe and calculate the physical characteristics of the vehicles such as the location, velocity, and passing time interval. Consequently, the performance index can be calculated with less effort for a given traffic timing plan and different timing plans can be compared in order that an optimal or suboptimal traffic control plan may be chosen. Finally, the implementation issues of the methodology are discussed.

2016 ◽  
Vol 6 (1) ◽  
pp. 4-16 ◽  
Author(s):  
Bokui Chen ◽  
David Z. W. Wang ◽  
Yachun Gao ◽  
Kai Zhang ◽  
Lixin Miao ◽  
...  

2021 ◽  
Vol 116 (1) ◽  
pp. 299-304
Author(s):  
Assel Aliyadynovna Sailau

The number of vehicles on the roads of Almaty, Kazakhstan is growing from year to year. This brings about an increasing intensity and density of traffic flows in the streets which leads to congestion, decreasing speed of the traffic flow, increasing environmental pollution caused by car emissions, and which can potentially lead to the road traffic accidents (RTA), including fatalities. While the number of injuries grows up mainly due to drivers’ non-compliance with the speed limit, the environmental pollution is caused by longer traffic jams. Therefore, to reduce the level of road traffic injuries and emissions into the environment it is necessary to ensure the uniform movement of traffic flows in cities. Currently, one of the effective ways to do it is the use of transport telematics systems, in particular, control systems for road signs, road boards and traffic lights. The paper presents an analysis of existing systems and methods of traffic light regulation. The  analyses of the systems and methods are based on the use of homogeneous data, that is the data on standard parameters of traffic flows. The need in collecting and analyzing additional semi-structured data on the factors that have a significant impact on the traffic flows parameters in cities is shown as well. The work is dedicated to solving the problem of analysis and forecast of traffic flows in the city of Almaty, Kazakhstan. GPS data on the location of individual vehicles is used as the initial data for solving this problem. By projecting the obtained information onto the graph of the city's transport network, as well as using additional filtering, it is possible to obtain an estimate of individual parameters of traffic flows. These parameters are used for short-term forecast of the changes in the city's transport network.


Transport ◽  
2018 ◽  
Vol 33 (4) ◽  
pp. 959-970 ◽  
Author(s):  
Tamás Tettamanti ◽  
Alfréd Csikós ◽  
Krisztián Balázs Kis ◽  
Zsolt János Viharos ◽  
István Varga

A full methodology of short-term traffic prediction is proposed for urban road traffic network via Artificial Neural Network (ANN). The goal of the forecasting is to provide speed estimation forward by 5, 15 and 30 min. Unlike similar research results in this field, the investigated method aims to predict traffic speed for signalized urban road links and not for highway or arterial roads. The methodology contains an efficient feature selection algorithm in order to determine the appropriate input parameters required for neural network training. As another contribution of the paper, a built-in incomplete data handling is provided as input data (originating from traffic sensors or Floating Car Data (FCD)) might be absent or biased in practice. Therefore, input data handling can assure a robust operation of speed forecasting also in case of missing data. The proposed algorithm is trained, tested and analysed in a test network built-up in a microscopic traffic simulator by using daily course of real-world traffic.


2013 ◽  
Vol 5 (5) ◽  
pp. 572-577 ◽  
Author(s):  
A. Stepanchuk ◽  
A. Bieliatynskyi ◽  
A. Pylypenko

The article considers the basic concepts concerningthe possibility of increasing the efficiency and capacity of theroad traffic network in the cities of Ukraine. The paper alsoanalyzes some of the measures to improve road traffic managementthrough the further development of an automated trafficcontrol system.


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