scholarly journals Effects of static bottlenecks on traffic flow in urban road network

2020 ◽  
Vol 12 (3) ◽  
pp. 1-15
Author(s):  
John N.P. Mahona ◽  
Cuthbert F. Mhilu ◽  
Joseph Kihedu ◽  
Hannibal Bwire

Existing traffic flow models do not consider the effects of road static bottlenecks on traffic flow. In this paper, a modified macroscopic continuum  model for traffic flow on urban road network with static bottlenecks is presented. The model takes into account the fluctuations of traffic flow considering static bottlenecks during the morning peak period. The model results show that existence of static road bottlenecks with various configurations cause traffic flow instabilities. This phenomenon lead into stop-and-go traffic flow conditions under the moderate density and reduction of the traffic system’s efficiency. Furthermore, results show that an increase in traffic density is accompanied by a significant decrease of speed which adversely influences performance of roadway and decrease the traffic system’s efficiency and thus resulting to the occurrence of congestions. The methodological aspects of the study and results will enable traffic engineers and planners to assess and improve existing urbanroad networks. Keywords: Traffic flow, Bottlenecks, stability, Stop-and-go traffic, System’s efficiency, Congestion.

2003 ◽  
Vol 1852 (1) ◽  
pp. 231-238 ◽  
Author(s):  
C. M. J. Tampère ◽  
B. van Arem ◽  
S. P. Hoogendoorn

A modeling technique is presented that analytically bridges the gap between microscopic behavior of individual drivers and the macroscopic dynamics of traffic flow. The basis of this approach is the (gas-) kinetic or mesoscopic modeling principle that considers the dynamics of traffic density and generalizations thereof as a probability density function of vehicles in different driving states. In contrast to traditional kinetic models, deceleration of individual vehicles due to slower traffic is treated as a continuous adaptive process rather than a discrete event. An analytic procedure is proposed to aggregate arbitrarily refined individual driver behavior to a macroscopic expected acceleration or deceleration of flow as a whole that can be used in macroscopic differential equations for traffic flow. The procedure implicitly accounts for the anisotropy of information flow in traffic, for anticipation behavior of drivers, and for the finite space requirement of vehicles, as long as these properties have been specified at the level of individual driver behavior. The procedure is illustrated for a simple car-following model with overtaking opportunity. The results show that the procedure yields micro-based aggregate traffic flow models that capture the essential properties of traffic dynamics. The techniques presented can contribute to the development of traffic flow models with driver behavior and driver psychology as important explanatory factors of congestion formation and propagation. Moreover, the approach allows building macroscopic traffic flow equations from future traffic flows for which no empirical speed–flow–density relations are available yet.


Kybernetes ◽  
2014 ◽  
Vol 43 (5) ◽  
pp. 750-763 ◽  
Author(s):  
Zhiyun Zou ◽  
Jinlong Wu ◽  
Jianzhi Gao ◽  
Xuecai Xu

Purpose – By aiming at defending cascade failures effectively, the purpose of this paper is to present a strategy of inserting modular topologies into urban road network through reducing the burdens of critical components with too much traffic flow. Design/methodology/approach – Each module is considered as a small-world random network, which is inserted into the initial Barabási-Albert scale-free network. Based on the user-equilibrium assignment, the strategy searches for remote nodes with low betweeness and flow in the network, and sets these nodes to be connected with the modular topologies. In this sense, the inserted modules are supposed to attach to the nodes with lower intensity of shorter path, and avoid bringing more impact to the nodes with higher betweeness and traffic flow. By using efficiency as the measurement of cascading failures, the performance of the networks generated through the strategy is tested. Findings – The results show that the performance of the strategy is sensitive to the average degree of the inserted modular, and the modular size with a better effect on reducing the size of cascading failures or delaying the time of breakdown, while the other factors (e.g. the rewired probability) present few differences among various values. Meanwhile, it is found that the importance-based attachment mechanism has a better effect on preventing the cascading failures, especially delaying the step time of the larger reduction. Practical implications – The strategy aims at alleviating the burdens in critical components to prevent the cascading failures of the network, and provides practical guidance on the decision of the urban road network evolving process. Originality/value – An effective strategy for cascade defense in urban road network is proposed in this paper.


2021 ◽  
Vol 261 ◽  
pp. 03026
Author(s):  
Yi Yu ◽  
Hui Gong ◽  
Xianglun Mo

Based on the floating vehicle data, this paper analyzes the equilibrium of urban road network traffic flow. This can guide traffic flow distribution and provide reliable basis for traffic control. This paper starts with the quantitative analysis of the traffic network equilibrium, on the basis of verifying the validity of the floating car data, divides the urban road network into regions, and constructs an analysis model of the traffic flow equilibrium of the urban road network. The urban road traffic distribution model is constructed in accordance with the number of road traffic segments. On this basis, gini coefficient index is introduced to judge the road network flow balance, which is used to analyze the balance of each sub-region. By means of traffic guidance, signal control and other traffic control means, the traffic flow in each sub-area is balanced, and the traffic flow in the whole road network becomes balanced.


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