scholarly journals Rule Optimization of Self-organization Control of Traffic Signals in Urban Net Based on Hydrodynamic

2018 ◽  
Vol 237 ◽  
pp. 03004
Author(s):  
Fusheng Zhong ◽  
Anlin Wang
Keyword(s):  
Traffic Flow ◽  
Road Network ◽  
Dynamic Change ◽  
Traffic Signals ◽  
Urban Traffic ◽  
Self Organization ◽  
Hydrodynamic Equations ◽  
The Road ◽  
Control Rules ◽  
Rule Optimization

Prior researchers indicate that hydrodynamics models of traffic-flow is lack of description of changing mechanism under urban traffic, and self-organization control system can not explain the dynamic characteristics of urban traffic flow clearly. The aim of the paper is to puts forward an optimized method on control rules that make the united application of hydrodynamics and self-organization system in signal control. The parameter sets of control rules are built from parameter sets of road network which are evolution under hydrodynamic equations such as the length of each lane, phase, queue length and so on .With the aim of the maximum traffic volume at each intersection in the road network, the control rules optimize its parameter sets to adapt to the dynamic change. By means of the computer simulation, the application of signal self-organizing control under hydrodynamic is proved effective in urban traffic.a

Make More Connections: Urban Traffic Flow Forecasting with Spatiotemporal Adaptive Gated Graph Convolution Network

2022 ◽  
Vol 13 (2) ◽  
pp. 1-25
Author(s):  
Bin Lu ◽  
Xiaoying Gan ◽  
Haiming Jin ◽  
Luoyi Fu ◽  
Xinbing Wang ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Road Network ◽  
Large Scale ◽  
Transportation Systems ◽  
Urban Traffic ◽  
Propagation Mechanism ◽  
Urban Road ◽  
The Road ◽  
Traffic Flow Forecasting ◽  
Gating Mechanism

Urban traffic flow forecasting is a critical issue in intelligent transportation systems. Due to the complexity and uncertainty of urban road conditions, how to capture the dynamic spatiotemporal correlation and make accurate predictions is very challenging. In most of existing works, urban road network is often modeled as a fixed graph based on local proximity. However, such modeling is not sufficient to describe the dynamics of the road network and capture the global contextual information. In this paper, we consider constructing the road network as a dynamic weighted graph through attention mechanism. Furthermore, we propose to seek both spatial neighbors and semantic neighbors to make more connections between road nodes. We propose a novel Spatiotemporal Adaptive Gated Graph Convolution Network ( STAG-GCN ) to predict traffic conditions for several time steps ahead. STAG-GCN mainly consists of two major components: (1) multivariate self-attention Temporal Convolution Network ( TCN ) is utilized to capture local and long-range temporal dependencies across recent, daily-periodic and weekly-periodic observations; (2) mix-hop AG-GCN extracts selective spatial and semantic dependencies within multi-layer stacking through adaptive graph gating mechanism and mix-hop propagation mechanism. The output of different components are weighted fused to generate the final prediction results. Extensive experiments on two real-world large scale urban traffic dataset have verified the effectiveness, and the multi-step forecasting performance of our proposed models outperforms the state-of-the-art baselines.

scholarly journals Macroscopic dynamics and the collapse of urban traffic

2018 ◽  
Vol 115 (50) ◽  
pp. 12654-12661 ◽  
Author(s):  
Luis E. Olmos ◽  
Serdar Çolak ◽  
Sajjad Shafiei ◽  
Meead Saberi ◽  
Marta C. González
Keyword(s):  
Travel Time ◽  
Road Network ◽  
Spatial Dynamics ◽  
Urban Traffic ◽  
Nonequilibrium Phase Transition ◽  
Vehicle Miles Traveled ◽  
The Road ◽  
Road Capacity ◽  
Total Vehicle ◽  
The Individual

Stories of mega-jams that last tens of hours or even days appear not only in fiction but also in reality. In this context, it is important to characterize the collapse of the network, defined as the transition from a characteristic travel time to orders of magnitude longer for the same distance traveled. In this multicity study, we unravel this complex phenomenon under various conditions of demand and translate it to the travel time of the individual drivers. First, we start with the current conditions, showing that there is a characteristic time τ that takes a representative group of commuters to arrive at their destinations once their maximum density has been reached. While this time differs from city to city, it can be explained by Γ, defined as the ratio of the vehicle miles traveled to the total vehicle distance the road network can support per hour. Modifying Γ can improve τ and directly inform planning and infrastructure interventions. In this study we focus on measuring the vulnerability of the system by increasing the volume of cars in the network, keeping the road capacity and the empirical spatial dynamics from origins to destinations unchanged. We identify three states of urban traffic, separated by two distinctive transitions. The first one describes the appearance of the first bottlenecks and the second one the collapse of the system. This collapse is marked by a given number of commuters in each city and it is formally characterized by a nonequilibrium phase transition.

scholarly journals Determination of Reserves for Reducing Delays and Increasing the Capacity of the Street-Road Network in Gomel as a Factor of Reducing Losses in Traffic

2021 ◽  
pp. 65-72
Author(s):  
D. P. Khodoskin
Keyword(s):  
Road Network ◽  
Urban Traffic ◽  
Economic Losses ◽  
Value Assessment ◽  
Large Cities ◽  
The Road ◽  
Car Traffic ◽  
Traffic Capacity ◽  
Real Objects ◽  
Time Expenditures

Purpose. Often, the existing level of traffic capacity of road network facilities in large cities is insufficient. This is often due to the fact that urban growth is significantly ahead of the reconstruction and renovation of the corresponding infrastructure. As a result, traffic delays of various kinds occur on city roads, accompanied, first of all, by economic losses. Therefore, the search for reserves to reduce various types of losses associated with insufficient traffic capacity of the road network when organizing urban traffic is the purpose of this work. Methodology To determine the reserves for increasing the traffic capacity of the road network and reducing various kinds of delays, the method of deterministic analysis was used, the method for calculating the cycle according to F. Webster, based on the use of phase coefficients and time lost in the cycle (as the sum of transient intervals), the method for measuring the intensity of car traffic in the traffic flow, as well as the methodology for calculating economic losses arising from delays in the movement of vehicles. Findings. A study of delays and time expenditures and the corresponding economic losses that occur at typical objects of the city's street-road network (regulated intersections) has been carried out. The reserves of their reduction, and as a consequence, the increase in the capacity of both individual sections and the city's road network as a whole, have been determined. Originality. The use of this method on real objects of the road network allows developing the scientific interpretation of the methods used and expanding the scope of their application. Practical value. Assessment of emerging problems of traffic capacity and associated losses (including economic ones) makes it possible to determine the most promising ways to determine the traffic capacity reserves and, as a result, reduce economic losses.

scholarly journals SCALE-FREE NETWORK THEORY IN STUDYING THE STRUCTURE OF THE ROAD NETWORK IN POLAND

2014 ◽  
Vol 26 (3) ◽  
pp. 235-242 ◽  
Author(s):  
Katarzyna KOCUR-BERA
Keyword(s):  
Statistical Analysis ◽  
Traffic Flow ◽  
Network Theory ◽  
Road Network ◽  
Scale Free Network ◽  
Scale Free ◽  
The Road ◽  
Normal Character ◽  
Free Network ◽  
The Relationship

This paper discusses the issue of statistical analysis of traffic flow in different regions of Poland. Such analysis allows us to identify “valuable (sensitive) areas” whose damage or blockage may provoke considerable disturbances or even a stoppage of traffic flow in the examined road network. The results of the studies indicate that the road network in Poland has the properties of a scale-free network. The distribution of the examined variables does not have a normal character, whereas the relationship between the number of nodes and the number of connections is a power-law feature. 

Taxi Global Positioning System Data in Urban Road Network: A Methodology to Identify Key Road Clusters Based on Travel Speed–Traffic Volume Correlation

2021 ◽  
pp. 036119812110366
Author(s):  
Yi Li ◽  
Weifeng Li ◽  
Qing Yu ◽  
Han Yang
Keyword(s):  
Traffic Congestion ◽  
Road Network ◽  
Travel Speed ◽  
Detection Algorithm ◽  
Traffic Volume ◽  
Urban Traffic ◽  
Mitigation Strategies ◽  
Operating Characteristics ◽  
The Road ◽  
Road Segments

Urban traffic congestion is one of the urban diseases that needs to be solved urgently. Research has already found that a few road segments can significantly influence the overall operation of the road network. Traditional congestion mitigation strategies mainly focus on the topological structure and the transport performance of each single key road segment. However, the propagation characteristics of congestion indicate that the interaction between road segments and the correlation between travel speed and traffic volume should also be considered. The definition is proposed for “key road cluster” as a group of road segments with strong correlation and spatial compactness. A methodology is proposed to identify key road clusters in the network and understand the operating characteristics of key road clusters. Considering the correlation between travel speed and traffic volume, a unidirectional-weighted correlation network is constructed. The community detection algorithm is applied to partition road segments into key road clusters. Three indexes are used to evaluate and describe the characteristic of these road clusters, including sensitivity, importance, and IS. A case study is carried out using taxi GPS data of Shanghai, China, from May 1 to 17, 2019. A total of 44 key road clusters are identified in the road network. According to their spatial distribution patterns, these key road clusters can be classified into three types—along with network skeletons, around transportation hubs, and near bridges. The methodology unveils the mechanism of congestion formation and propagation, which can offer significant support for traffic management.

scholarly journals UNDERSTANDING URBAN TRAFFIC FLOW CHARACTERISTICS FROM THE NETWORK CENTRALITY PERSPECTIVE AT DIFFERENT GRANULARITIES

2016 ◽  
Vol XLI-B2 ◽  
pp. 263-268 ◽  
Author(s):  
P. X. Zhao ◽  
S. M. Zhao
Keyword(s):  
Traffic Flow ◽  
Flow Characteristics ◽  
Research Unit ◽  
Urban Traffic ◽  
Network Centrality ◽  
Trajectory Data ◽  
The Road ◽  
Analysis Process ◽  
Intersection Line ◽  
Taxi Trajectory

In this study, we analyze urban traffic flow using taxi trajectory data to understand the characteristics of traffic flow from the network centrality perspective at point (intersection), line (road), and area (community) granularities. The entire analysis process comprises three steps. The first step utilizes the taxi trajectory data to evaluate traffic flow at different granularities. Second, the centrality indices are calculated based on research units at different granularities. Third, correlation analysis between the centrality indices and corresponding urban traffic flow is performed. Experimental results indicate that urbaxperimental results indicate that urbaxperimental results indicate that urban traffic flow is relatively influenced by the road network structure. However, urban traffic flow also depends on the research unit size. Traditional centralities and traffic flow exhibit a low correlation at point granularity but exhibit a high correlation at line and area granularities. Furthermore, the conclusions of this study reflect the universality of the modifiable areal unit problem.

A MODEL FOR THE STUDY OF TRAFFIC FLOW ON THE UKRAINIAN CITIES ROAD NETWORK

2019 ◽  
pp. 30-33
Author(s):  
Liydmila Nagrebelna
Keyword(s):  
Traffic Flow ◽  
Road Network ◽  
Operating Conditions ◽  
Negative Effects ◽  
Efficient Operation ◽  
Urban Road ◽  
The Road ◽  
Effective Functioning ◽  
Organization And Management ◽  
The City

The problems of efficient functioning of the city road network are outlined. The method by which it is possible to improve the functioning of the street-road network of Ukrainian cities is presented. Improving the efficiency of the urban road network is to use all the resources of this network to create the necessary languages for its reliable and efficient operation and reduce the negative effects of motorization. It is proved that in order to ensure the effective functioning of the road network it is necessary to carry out a set of measures for the organization and management of traffic. The purpose of this article is to identify factors that affect the deterioration of operating conditions; identify the conditions for the effective functioning of the road network; the choice of a model for the effective functioning of the street-road network of Ukrainian cities is grounded. Because the management impact on traffic flow can be estimated on the basis of the developed models. Keywords: road network, efficient operation, methods, conditions.

Organization of non-traffic jam traffic at an intersection when cycle time and roadway width are limited

2020 ◽  
Keyword(s):  
Traffic Flow ◽  
Road Safety ◽  
Traffic Management ◽  
Road Network ◽  
Traffic Light ◽  
Maximum Capacity ◽  
Traffic Jam ◽  
The Road ◽  
Traffic Management System ◽  
Stop Line

In General, two problems need to be solved in the traffic management system: road safety and capacity. In this paper, it is proposed to use a calculated way to optimize the cycle of a traffic light object in order to ensure the maximum capacity of the node of the road network. The calculation method is based to determining the optimal ratio of the number of lanes intended for vehicle traffic and the duration of a cycle of the traffic light object. Keywords capacity, street and road network, traffic flow, stop line, width of the roadway

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