Models and Evaluation for Urban Traffic Carrying Capacity

2013 ◽  
Vol 409-410 ◽  
pp. 1258-1261
Author(s):  
Shan Shan Gao ◽  
Zhen Zhou Yuan
Keyword(s):  
Carrying Capacity ◽  
Road Network ◽  
Quantitative Model ◽  
Urban Traffic ◽  
Evaluation Standard ◽  
Utilization Coefficient ◽  
Time Space ◽  
Reduction Coefficient ◽  
The Status ◽  
Integrated Utilization

This paper studies on the status of urban traffic development by analyzing traffic carrying capacity. The concept, characteristics and influencing factors of urban traffic carrying capacity is researched. This paper establishes one quantitative model based on the time-space consumption model, especially taking the reuse coefficient of road resources, reduction coefficient caused by intersections, and integrated utilization coefficient of road network into consideration. And put forward evaluation index which is the level of traffic carrying capacity. Moreover, the evaluation standard and some strategies for improving traffic carrying capacity are provided.

scholarly journals Dynamic Evaluation on the Traffic State of an Urban Gated Community by Opening the Micro-Inter-Road Network

Technologies ◽  
2018 ◽  
Vol 6 (3) ◽  
pp. 71 ◽  
Author(s):  
Lin Dong ◽  
Akira Rinoshika ◽  
Zhixian Tang
Keyword(s):  
Road Network ◽  
Entropy Method ◽  
Urban Traffic ◽  
Traffic Information ◽  
Gated Community ◽  
Entropy Model ◽  
Evaluation Standard ◽  
Traffic System ◽  
Traffic State ◽  
Selection Framework

The opening of a gated community to expand the micro-road network in an urban traffic system is an importance research topic related to urban congestion. To satisfy the demands of opening an early choosing case, this paper proposes a comprehensive selection framework on qualified communities and their appropriate opening times by describing the traffic state at the boundary road network accurately. The traffic entropy model and fuzzy c-means (FCM) method are used in this paper. In the framework, a new opening evaluation entropy model is built using basic theory of the thermodynamic traffic entropy method. The traffic state entropy values of the boundary road network and entropy production are calculated to determinate the opening time. In addition, a specific fuzzy range evaluation standard at a preset gated community is drawn with an FCM algorithm to verify the opening determination. A case study based on the traffic information in a simulated gated community in Shanghai is evaluated and proves that the findings of opening evaluation are in accordance with the actual situation. It is found that the micro-inter-road network of a gated community should be opened as the entropy value reaches 2.5. As the travel time is less than 20 s, the correlation between the opening entropy value and the journey delay time exhibits a good linear correlation, which indicates smooth traffic flow.

scholarly journals A systematic review of potential habitat suitability for the jaguar Panthera onca in central Arizona and New Mexico, USA

Oryx ◽  
2021 ◽  
pp. 1-12
Author(s):  
Eric W. Sanderson ◽  
Kim Fisher ◽  
Rob Peters ◽  
Jon P. Beckmann ◽  
Bryan Bird ◽  
...  
Keyword(s):  
Systematic Review ◽  
New Mexico ◽  
Carrying Capacity ◽  
Panthera Onca ◽  
Mountain Ranges ◽  
Potential Habitat ◽  
The Status ◽  
The Usa ◽  
Mexico Border ◽  
Conservation Plan

Abstract In April 2019, the U.S. Fish and Wildlife Service (USFWS) released its recovery plan for the jaguar Panthera onca after several decades of discussion, litigation and controversy about the status of the species in the USA. The USFWS estimated that potential habitat, south of the Interstate-10 highway in Arizona and New Mexico, had a carrying capacity of c. six jaguars, and so focused its recovery programme on areas south of the USA–Mexico border. Here we present a systematic review of the modelling and assessment efforts over the last 25 years, with a focus on areas north of Interstate-10 in Arizona and New Mexico, outside the recovery unit considered by the USFWS. Despite differences in data inputs, methods, and analytical extent, the nine previous studies found support for potential suitable jaguar habitat in the central mountain ranges of Arizona and New Mexico. Applying slightly modified versions of the USFWS model and recalculating an Arizona-focused model over both states provided additional confirmation. Extending the area of consideration also substantially raised the carrying capacity of habitats in Arizona and New Mexico, from six to 90 or 151 adult jaguars, using the modified USFWS models. This review demonstrates the crucial ways in which choosing the extent of analysis influences the conclusions of a conservation plan. More importantly, it opens a new opportunity for jaguar conservation in North America that could help address threats from habitat losses, climate change and border infrastructure.

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 Environment carrying capacity and willingness to pay for bird-watching ecotourism in Kerandangan Natural Park, Lombok, Indonesia

2020 ◽  
Vol 21 (5) ◽  
Author(s):  
I Wayan Suana ◽  
Hilman Ahyadi ◽  
Gito Hadiprayitno ◽  
Saleh Amin ◽  
Lalu Achmad Tan Tilar Wangsajati Sukmaring Kalih ◽  
...  
Keyword(s):  
Willingness To Pay ◽  
Carrying Capacity ◽  
Contingent Valuation Method ◽  
Secondary Data ◽  
Observation Point ◽  
Valuation Method ◽  
Natural Park ◽  
Bird Watching ◽  
Guest House ◽  
The Status

Abstract. Suana IW, Ahyadi H, Hadiprayitno G, Amin S, Kalih LATTWS, Sudaryanto FX. 2020. Environment carrying capacity and willingness to pay for bird-watching ecotourism in Kerandangan Natural Park, Lombok, Indonesia. Biodiversitas 21: 2266-2274.  Five trails of interest to bird-watchers and an observation point by the guest house of Kerandangan Natural Park (KNP) have potential to be developed as bird-watching ecotourism packages. In order to develop sustainable bird-watching ecotourism in KNP, we analyzed the environment carrying capacity and willingness to pay (WTP) for bird-watching ecotourism packages. All of the trails and an observation point in KNP were explored to determine the width and length of the trails, the visit time, as well as the soil texture and slope along the trails. Interviews with KNP managers and secondary data from Meteorology, Climatology and Geophysics Council (BMKG)-Climatology Station Class I-West Lombok were also used to determine the status of biophysical habitats. The environment carrying capacity was calculated by combining the physical carrying capacity, real carrying capacity, and effective carrying capacity. The results show that environment carrying capacity of bird-watching ecotourism packages in KNP was higher than the actual visitation levels. It indicates that opportunity to develop and increase the number of visitors is considerable. WTP was determined by Contingent Valuation Method (CVM) with payment card approach. Through the brochure, 150 respondents were given information on bird-watching ecotourism packages, then are offered three options, and only allowed to choose one that can be paid. Data were collected by the incidental sampling method. The results show that the visitors are willing to pay for bird-watching ecotourism packages, with mean WTP of US$ 20.7 per visitor. It implies that they are willing to shoulder the financial support for management and conservation of birds and their habitat in KNP. The findings provide important information for KNP managers for planning and marketing bird-watching ecotourism in KNP.

scholarly journals Impact of a Growing Population on Natural Resources: The Challenge for Environmental Management

1997 ◽  
Vol 3 (1) ◽  
pp. 105-131 ◽  
Author(s):  
David Pimentel ◽  
X. Huang ◽  
A. Codova ◽  
M. Pimentel
Keyword(s):  
Environmental Management ◽  
Natural Resources ◽  
Carrying Capacity ◽  
Living Conditions ◽  
Environmental Resources ◽  
The Future ◽  
The Status ◽  
The Many ◽  
Growing Population

The food situation worldwide is becoming critical. At present, more than 2 billion humans are malnourished and experience unhealthy living conditions (FAO, 1992a,b; Neisheim, 1993; McMichael, 1993; Maberly, 1994; Bouis, 1995). The number of humans who also are diseased is the largest number ever, and about 40,000 children die each day from disease and malnutrition (Kutzner, 1991; Tribe, 1994).  The many problems that are now evident emphasize the urgent need to reassess the status of environmental resources. Based on the evidence, definitive plans must be developed to improve environmental management now and for the future. Of major importance is the limiting and slow reduction of human numbers to better balance the carrying capacity of the earth's natural resources. 

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.

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