scholarly journals Traffic flow dynamics on road network fragments using two-dimensional mathematical models

2016 ◽  
pp. 1-20 ◽  
Author(s):  
Marina Alexandrovna Trapeznikova ◽  
Antonina Alexandrovna Chechina ◽  
Natalia Gennadievna Churbanova
Keyword(s):  
Mathematical Models ◽  
Traffic Flow ◽  
Road Network ◽  
Flow Dynamics ◽  
Two Dimensional

Continuum modeling of cooperative traffic flow dynamics

2009 ◽  
Vol 388 (13) ◽  
pp. 2705-2716 ◽  
Author(s):  
D. Ngoduy ◽  
S.P. Hoogendoorn ◽  
R. Liu
Keyword(s):  
Traffic Flow ◽  
Flow Dynamics ◽  
Continuum Modeling

ANALYSIS OF THE INFLUENCE OF LANE CHANGING ON TRAFFIC-FLOW DYNAMICS BASED ON THE CELLULAR AUTOMATON MODEL

2011 ◽  
Vol 22 (03) ◽  
pp. 271-281 ◽  
Author(s):  
SHINJI KUKIDA ◽  
JUN TANIMOTO ◽  
AYA HAGISHIMA
Keyword(s):  
Boundary Condition ◽  
Cellular Automaton ◽  
Numerical Simulations ◽  
Traffic Flow ◽  
Flow Dynamics ◽  
Open Boundary ◽  
Open Boundary Condition ◽  
Lane Changing ◽  
Basic Characteristics ◽  
Conventional Models

Many cellular automaton models (CA models) have been applied to analyze traffic flow. When analyzing multilane traffic flow, it is important how we define lane-changing rules. However, conventional models have used simple lane-changing rules that are dependent only on the distance from neighboring vehicles. We propose a new lane-changing rule considering velocity differences with neighboring vehicles; in addition, we embed the rules into a variant of the Nagel–Schreckenberg (NaSch) model, called the S-NFS model, by considering an open boundary condition. Using numerical simulations, we clarify the basic characteristics resulting from different assumptions with respect to lane changing.

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 Enhancing Freeway Safety through Intervening in Traffic Flow Dynamics Based on Variable Speed Limit Control

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Jinming You ◽  
Shouen Fang ◽  
Lanfang Zhang ◽  
John Taplin ◽  
Jingqiu Guo
Keyword(s):  
Real Time ◽  
Traffic Flow ◽  
New Technologies ◽  
Flow Dynamics ◽  
Crash Risk ◽  
Speed Limit ◽  
Variable Speed ◽  
Variable Speed Limit ◽  
Traffic Conditions ◽  
Safety Research

New technologies and traffic data sources provide great potential to extend advanced strategies in freeway safety research. The High Definition Monitoring System (HDMS) data contribute comprehensive and precise individual vehicle information. This paper proposes an innovative Variable Speed Limit (VSL) based approach to manage crash risks by intervening in traffic flow dynamics on freeways using HDMS data. We first conducted an empirical analysis on real-time crash risk estimation using a binary logistic regression model. Then, intensive microscopic simulations based on AIMSUN were carried out to explore the effects of various intervention strategies with respect to a 3-lane freeway stretch in China. Different speed limits with distinct compliance rates under specified traffic conditions have been simulated. By taking into account the trade-off between safety benefits and delay in travel time, the speed limit strategies were optimized under various traffic conditions and the model with gradient feedback produces more satisfactory performance in controlling real-time crash risks. Last, the results were integrated into lane management strategies. This research can provide new ideas and methods to reveal the freeway crash risk evolution and active traffic management.

scholarly journals Mathematical models as practical tool for road fatalities forecasts on road network in regions

2018 ◽  
Vol 231 ◽  
pp. 01018 ◽  
Author(s):  
Joanna Wachnicka
Keyword(s):  
Mathematical Models ◽  
Traffic Safety ◽  
Road Safety ◽  
Regression Models ◽  
Road Network ◽  
Statistical Data ◽  
Safety Management ◽  
National Data ◽  
Local Characteristics ◽  
Practical Tool

The analysis of national data on the number of deaths showed that in Poland from 2010 to 2016 it was possible to reduce the number of fatalities by about 22%. The tendency of changes in the number of fatalities, however, is not homogeneous. When data of individual voivodships is analyzed, the situation is different. The largest reduction in fatalities in the analyzed period of time concerned voivodship Świętokrzyskie, where there was more than 45% drop in the number of fatalities. The following voivodships: Łódzkie, Lubelskie and Podkarpackie recorded a decrease in over 30% of fatalities. Unfortunately, at the end of the classification there were four voivodships with a fall below 8%, and what is disturbing voivodship Lubuskie recorded a nearly 5% increase in the number of fatalities. The current traffic safety management at the level of voivodships is often the implementation of central recommendations, which, as results from the analysis of statistical data, are not equally effective in every province. Therefore, models for forecasting changes in road safety are required. Taking into account local characteristics and implemented actions can be used to manage security more effectively at the regional level. This paper presents examples of the use of mathematical models to predict the number of fatalities in individual voivodships depending on the adopted action scenarios. Regression models were developed, taking into account demographic, infrastructural, economic and automotive factors. It turned out that in individual voivodships, various factors affect the level of road safety on roads differently. Therefore, an individual approach to each voivodship is important in order to reliably forecast the level of security.

Two-dimensional reactive flow dynamics in cellular detonation waves

Shock Waves ◽  
1999 ◽  
Vol 9 (1) ◽  
pp. 11-17 ◽  
Author(s):  
V.N. Gamezo ◽  
D. Desbordes ◽  
E.S. Oran
Keyword(s):  
Flow Dynamics ◽  
Reactive Flow ◽  
Detonation Waves ◽  
Two Dimensional ◽  
Cellular Detonation
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