Optimizing Road Network Density Considering Automobile Traffic Efficiency: Theoretical Approach

The poverty-stricken counties in China follow a spatial pattern of regional poverty. Examining the influential factors of this spatial pattern can provide an important reference that can guide China in its implementation of a poverty alleviation policy. By applying a geographical detector and using a sample of poverty-stricken counties in China, this study explores the spatial relationship of county distribution with spatial influential factors, including terrain relief, cultivated land quality, water resource abundance, road network density, and the locational index. These poverty-stricken counties are then classified, and the main factors that restrict their economic development are determined. The results highlight that the selected poverty-stricken counties suffer a severe condition in each of the spatial factors mentioned above. Most of these counties are classified under the location index, terrain relief, and road network density constraint types. Each of the aforementioned spatial influential factors has unique controlling mechanisms on the distribution of these poverty-stricken counties. Most of these counties are constrained by two or multiple spatial influential factors, except for some counties located in South and Central China, which are mainly constrained by a single spatial influential factor. Therefore, these single factor-constrained poverty-stricken counties warrant more attention when a developmental policy for poverty alleviation is to be implemented. The various aspects of poverty-stricken counties constrained by multiple factors must be comprehensively considered with a special focus on their development. The differentiated policies must be designed for these poverty-stricken counties on the basis of their spatial influential factors.

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Traffic Signal Synchronization in the Saturated High-Density Grid Road Network

Computational Intelligence and Neuroscience ◽

10.1155/2015/532960 ◽

2015 ◽

Vol 2015 ◽

pp. 1-11 ◽

Cited By ~ 1

Author(s):

Xiaojian Hu ◽

Jian Lu ◽

Wei Wang ◽

Ye Zhirui

Keyword(s):

Traffic Congestion ◽

Queue Length ◽

Road Network ◽

Signalized Intersections ◽

Traffic Signal ◽

High Density ◽

Traffic Flows ◽

Traffic Efficiency ◽

Signal Synchronization ◽

Overall Performance

Most existing traffic signal synchronization strategies do not perform well in the saturated high-density grid road network (HGRN). Traffic congestion often occurs in the saturated HGRN, and the mobility of the network is difficult to restore. In order to alleviate traffic congestion and to improve traffic efficiency in the network, the study proposes a regional traffic signal synchronization strategy, named the long green and long red (LGLR) traffic signal synchronization strategy. The essence of the strategy is to control the formation and dissipation of queues and to maximize the efficiency of traffic flows at signalized intersections in the saturated HGRN. With this strategy, the same signal control timing plan is used at all signalized intersections in the HGRN, and the straight phase of the control timing plan has a long green time and a long red time. Therefore, continuous traffic flows can be maintained when vehicles travel, and traffic congestion can be alleviated when vehicles stop. Using the strategy, the LGLR traffic signal synchronization model is developed, with the objective of minimizing the number of stops. Finally, the simulation is executed to analyze the performance of the model by comparing it to other models, and the superiority of the LGLR model is evident in terms of delay, number of stops, queue length, and overall performance in the saturated HGRN.

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Road Network Pre-partitioning Method with Priority for Congestion Control

Journal of Advances in Mathematics and Computer Science ◽

10.9734/jamcs/2019/v32i230143 ◽

2019 ◽

pp. 1-13

Author(s):

Hao She ◽

Xingsheng Xie

Keyword(s):

Congestion Control ◽

Traffic Congestion ◽

Spectral Clustering ◽

Road Network ◽

Control Area ◽

Urban Traffic ◽

The Road ◽

Traffic Efficiency ◽

Svm Model ◽

Partition Method

Urban traffic congestion seriously affects the traffic efficiency, causing travel delays and resources wasted directly. In this paper, a road network pre-partitioning method with priority for congestion control is proposed to reduce traffic congestion. Traffic flow feature is extracted based on CNN, and the estimated accuracy of intersection reach 95.32% through CNN-SVM model. Subarea congestion coefficient and intersection merger coefficient are defined to expand the control area of congestion coordination. The association and similarity of intersections are considered using spectral clustering for non-congested intersection partitioning. The results show that the congestion priority control partition method reduces a congestion intersection compared to directly using spectral clustering for subarea partition, and reduces the road network congestion coefficient by 0.05 after 30 minutes than directly using spectral clustering, which is an effective subarea partition method.

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Determination of the optimal density of the forest road network

Journal of Forest Science ◽

10.17221/101/2019-jfs ◽

2019 ◽

Vol 65 (No. 11) ◽

pp. 438-444 ◽

Cited By ~ 1

Author(s):

Tihomir Krumov

Keyword(s):

Road Network ◽

Good Condition ◽

National Average ◽

Network Density ◽

Primary Forest ◽

Optimal Density ◽

Forest Road ◽

Financial Difficulties ◽

State Educational

The forest road network is invariably linked to forestry and logging, as it transports logging products and products needed for forestry activities. Constructing and maintaining it in good condition are essential. In view of the economic situation in the country and the financial difficulties faced by forest holdings in the construction and maintenance of the forest road network, it is necessary to determine the optimal hauling distance and the optimal density of the primary forest road network. The analysis of the forest road network in the territory of the State Educational Experimental Forestry Enterprise “Georgi Avramov”, Yundola village, showed that the density of the primary forest road network is several times higher than the national average, namely 20.31 m'·ha–1, yet it does not reach the optimal road network density calculated at the farm, of 30.9 m'·ha–1, at a hauling distance of 323.15 m.<br /><br />

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Traffic efficiency of post-earthquake road network in fault region retrofitted by friction core rubber bearing

Structures ◽

10.1016/j.istruc.2021.04.030 ◽

2021 ◽

Vol 33 ◽

pp. 54-67

Author(s):

Qiang Lian ◽

Wancheng Yuan ◽

Juanya Yu ◽

Xinzhi Dang

Keyword(s):

Road Network ◽

Traffic Efficiency ◽

Rubber Bearing ◽

Fault Region

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The Influence of Transport Link Density on Conductivity If Junctions and/or Links Are Blocked

Mathematics ◽

10.3390/math9111278 ◽

2021 ◽

Vol 9 (11) ◽

pp. 1278

Author(s):

Anton Aleshkin

Keyword(s):

Percolation Threshold ◽

Road Network ◽

Random Network ◽

Road Transport ◽

Transport Network ◽

Network Density ◽

Network Algorithms ◽

The Road ◽

Link Density ◽

Percolation Thresholds

This paper examines some approaches to modeling and managing traffic flows in modern megapolises and proposes using the methods and approaches of the percolation theory. The author sets the task of determining the properties of the transport network (percolation threshold) when designing such networks, based on the calculation of network parameters (average number of connections per crossroads, road network density). Particular attention is paid to the planarity and nonplanarity of the road transport network. Algorithms for building a planar random network (for modeling purposes) and calculating the percolation thresholds in the resulting network model are proposed. The article analyzes the resulting percolation thresholds for road networks with different relationship densities per crossroad and analyzes the effect of network density on the percolation threshold for these structures. This dependence is specified mathematically, which allows predicting the qualitative characteristics of road network structures (percolation thresholds) in their design. The conclusion shows how the change in the planar characteristics of the road network (with adding interchanges to it) can improve its quality characteristics, i.e., its overall capacity.

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The impacts of road traffic on urban air quality in Jinan based GWR and remote sensing

Scientific Reports ◽

10.1038/s41598-021-94159-8 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Qi Wang ◽

Haixia Feng ◽

Haiying Feng ◽

Yue Yu ◽

Jian Li ◽

...

Keyword(s):

Air Quality ◽

Road Network ◽

Road Traffic ◽

Intersection Number ◽

Urban Air Quality ◽

Network Density ◽

Urban Air ◽

Strong Positive Correlation ◽

The Road ◽

Bus Network

AbstractTraffic congestion and smog are hot topics in recent years. This study analyzes the impacts of road traffic characteristic parameters on urban air quality quantitatively based on aerosol optical thickness (AOD) and geographical weighted regression (GWR) models, including the road network density, road area occupancy, intersection number, and bus network density as main factors. There are some major research findings. Firstly, there exists a strong positive correlation between the peak congestion delay index (PCDI) and air quality, the correlation has R2 values of up to 0.4962 (R 0.70). Secondly, GWR refines the local spatial changes in the AOD and the road parameters, and the correlation R2 based GWR model all above 0.6. The correlation between AOD and the road area occupancy was the highest, and the correlations with the bus network density and the intersections number were higher than that with the road network density. Thus, bus route planning, bus emission reduction, road network planning, and signal timing (at intersections) have a greater impact on air quality than other policy, especially in areas with traffic jams. The results of this study could provide theoretical support for traffic planning and traffic control, and is promising in practice.

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Correlation of forest road network density and the production of forest assortments in Serbia in the period 1991-2000

Glasnik Sumarskog fakulteta ◽

10.2298/gsf0387187s ◽

2003 ◽

pp. 187-195

Author(s):

Bogdan Stefanovic ◽

Nenad Rankovic

Keyword(s):

Road Network ◽

Forest Products ◽

Network Density ◽

Total Production ◽

Forest Road ◽

Round Wood

The dependence of the scope of production of the definite forest products (total felling volume, round wood, cordwood, felling waste, waste percentage) in Serbia was analyzed for the period 1991-2000, in relation to the changes of forest road network density. It was concluded that, with the change of forest road network density, the total felling volume, round wood and cordwood decreases, while the quantity of felling waste and its percentage in the total production are not in correlation. This is opposite to the expected which points to the paradox in these relations in the study period.

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Spatial and Temporal Distribution Analysis of Traffic Accidents Using GIS-Based Data in Harbin

Journal of Advanced Transportation ◽

10.1155/2021/9207500 ◽

2021 ◽

Vol 2021 ◽

pp. 1-10

Author(s):

Meina Wang ◽

Jing Yi ◽

Xirui Chen ◽

Wenhui Zhang ◽

Tiangang Qiang

Keyword(s):

Traffic Safety ◽

Road Network ◽

Traffic Accidents ◽

Road Traffic ◽

Network Density ◽

Road Traffic Accidents ◽

Urban Centers ◽

Accident Severity ◽

Accident Data ◽

Density Analysis

Road traffic safety is a social issue of widespread concern. It is important for traffic managers to understand the distribution patterns of road traffic accidents. To this end, this study examines the spatial and temporal patterns of road traffic accidents from both accident frequency and accident severity perspectives. Road traffic accident data from 2016 to 2018 in Harbin, China, were used for the analysis. First, the spatial localization of accidents was completed using geocoding, and the localized accident data were classified by season. Then, density analysis was performed both with and without considering road network density. The results of the density analysis showed that when road network density was considered, accidents were mainly distributed in urban centers, while accidents were more dispersed when road network density was not considered. Third, a cluster analysis considering accident severity found that low-severity accident clusters occurred mostly in urban centers. High-severity accident clusters were mostly present in suburban areas. Finally, the results of these two methods are shown by using the comap technique. Areas of the city with a high frequency and severity of crashes in each season were identified. This study will help traffic management to have a more visual and intuitive understanding of the urban traffic safety situation and to take targeted measures to improve it accordingly.

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