The improved degree of urban road traffic network: A case study of Xiamen, China

2017 ◽  
Vol 469 ◽  
pp. 256-264 ◽  
Author(s):  
Shiguang Wang ◽  
Lili Zheng ◽  
Dexin Yu
Keyword(s):  
Road Traffic ◽  
Traffic Network ◽  
Urban Road

Empirical analysis of urban road traffic network: A case study in Hangzhou city, China

2019 ◽  
Vol 527 ◽  
pp. 121287 ◽  
Author(s):  
Zhongyuan Ruan ◽  
Congcong Song ◽  
Xu-hua Yang ◽  
Guojiang Shen ◽  
Zhi Liu
Keyword(s):  
Empirical Analysis ◽  
Road Traffic ◽  
Traffic Network ◽  
Urban Road

scholarly journals Should We Expect a Disastrous Fire Accident in an Urban Road Tunnel? Literature Data Review and a Case Study for Selected Tunnels in Poland

2021 ◽  
Vol 13 (11) ◽  
pp. 6172
Author(s):  
Krystian Szewczyński ◽  
Aleksander Król ◽  
Małgorzata Król
Keyword(s):  
Time Horizon ◽  
Road Traffic ◽  
Traffic Intensity ◽  
Road Tunnel ◽  
Urban Road ◽  
Road Tunnels ◽  
High Uncertainty ◽  
Fire Outbreak ◽  
Fire Accident

Urban road tunnels are a reasonable remedy for inconvenience due to congested road traffic. However, they bring specific threats, especially those related to the possibility of fire outbreak. This work is a case study for selected urban road tunnels. Considering tunnel specificity, road traffic intensity, and structure and based on the literature data for vehicle fire probability, the chances of a fire accident were estimated for selected tunnels in Poland. It was shown that low power tunnel fires could be expected in the 10–20-year time horizon. Although such threats cannot be disregarded, tunnel systems are designed to cope with them. The chances of a disastrous fire accident were estimated as well. Such events can occur when an HGV with flammable goods or a tanker are involved. Such accidents are fortunately very rare, but, on the other hand, that is the reason why the available data are scanty and burdened with high uncertainty. Therefore, a discussion on the reliability of the obtained results is also provided.

scholarly journals PATTERN RECOGNITION BASED SPEED FORECASTING METHODOLOGY FOR URBAN TRAFFIC NETWORK

Transport ◽  
2018 ◽  
Vol 33 (4) ◽  
pp. 959-970 ◽  
Author(s):  
Tamás Tettamanti ◽  
Alfréd Csikós ◽  
Krisztián Balázs Kis ◽  
Zsolt János Viharos ◽  
István Varga
Keyword(s):  
Neural Network ◽  
Input Data ◽  
Road Traffic ◽  
Urban Traffic ◽  
Traffic Network ◽  
Data Handling ◽  
Urban Road ◽  
Traffic Sensors ◽  
Network Training ◽  
Artificial Neural Network Ann

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.

Determination of key nodes in urban road traffic network

2014 ◽  
Author(s):  
Zhao Tian ◽  
Limin Jia ◽  
Honghui Dong ◽  
Zundong Zhang ◽  
Yanfang Yang ◽  
...  
Keyword(s):  
Road Traffic ◽  
Traffic Network ◽  
Urban Road ◽  
Key Nodes

scholarly journals Golden Ratio Genetic Algorithm Based Approach for Modelling and Analysis of the Capacity Expansion of Urban Road Traffic Network

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Lun Zhang ◽  
Meng Zhang ◽  
Wenchen Yang ◽  
Decun Dong
Keyword(s):  
Genetic Algorithm ◽  
Road Network ◽  
Road Traffic ◽  
Golden Ratio ◽  
Hybrid Genetic Algorithm ◽  
Capacity Expansion ◽  
Network Capacity ◽  
Traffic Network ◽  
Effective Measure ◽  
Urban Road

This paper presents the modelling and analysis of the capacity expansion of urban road traffic network (ICURTN). Thebilevel programming model is first employed to model the ICURTN, in which the utility of the entire network is maximized with the optimal utility of travelers’ route choice. Then, an improved hybrid genetic algorithm integrated with golden ratio (HGAGR) is developed to enhance the local search of simple genetic algorithms, and the proposed capacity expansion model is solved by the combination of the HGAGR and the Frank-Wolfe algorithm. Taking the traditional one-way network and bidirectional network as the study case, three numerical calculations are conducted to validate the presented model and algorithm, and the primary influencing factors on extended capacity model are analyzed. The calculation results indicate that capacity expansion of road network is an effective measure to enlarge the capacity of urban road network, especially on the condition of limited construction budget; the average computation time of the HGAGR is 122 seconds, which meets the real-time demand in the evaluation of the road network capacity.

scholarly journals Urban road traffic flow control under incidental congestion as a function of accident duration

Open Physics ◽  
2018 ◽  
Vol 16 (1) ◽  
pp. 1085-1093
Author(s):  
Yang Xu ◽  
Duojia Zhang ◽  
Ahmad Jalal Khan Chowdhury
Keyword(s):  
Flow Control ◽  
Traffic Flow ◽  
Traffic Congestion ◽  
Road Traffic ◽  
Abrupt Increase ◽  
Urban Road ◽  
Catastrophe Model ◽  
Traffic Capacity ◽  
Control Scheme

Abstract An abrupt increase in urban road traffic flow caused by incidental congestion is considered. The residual traffic capacity varies in different lanes after an accident, and the influence of accident duration on traffic flow is taken into account. The swallowtail catastrophe model was built based on catastrophe theory. The critical state of traffic congestion under incidental congestion was analyzed using this model, and a traffic flow control scheme is proposed with the goal of maximizing the traffic capacity. Finally, the operational state of traffic flow under different scenarios is analyzed through case study and the feasibility of the model is validated.

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