scholarly journals Transportation Network Spatial Analysis to Measure Pedestrian Suitability. The Case of Hilly Cities

2021 ◽  
Vol 1203 (2) ◽  
pp. 022107
Author(s):  
André Nogueira ◽  
Bertha Santos ◽  
Jorge Gonçalves ◽  
Jan Kempa ◽  
Jacek Chmielewski
Keyword(s):  
Population Density ◽  
Public Space ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Transportation Network ◽  
Trip Generation ◽  
Pedestrian Network ◽  
Transport Modes ◽  
Network Spatial Analysis ◽  
Pedestrian Infrastructure

Abstract The current climate and environmental emergency, together with the growing traffic congestion and pollution in urban areas, make mobility and its sustainability a priority in current transport policies. It is essential to change citizen’s behaviour in order to increase the use of less pollutant, economic and egalitarian transport modes, such as walking, combining it with other public transport modes. For this change to happen, it is necessary to provide feasible alternatives to private cars, namely through the offer of high-quality pedestrian infrastructures, adapted to the cities’ specific characteristics and their citizen’s needs. These aspects are particularly important in hilly cities, where traveling by foot requires an additional effort. The present study aims to contribute to the promotion of soft mobility in hilly cities by creating a support instrument to assess the potential of existing pedestrian infrastructures. Three variables are considered in the analysis: trip generation poles, population density and pedestrian network characteristics, with especial consideration of slopes. These variables were processed with spatial and network analysis tools available in Geographic Information Systems (GIS) and combined using a multi-criteria decision analysis to obtain a measure of the pedestrian infrastructure potential. The identification of areas with high pedestrian potential supports the definition of priority intervention programs on the public space and a better allocation of human and financial resources. The proposed instrument was validated through its application to a case study, the hilly city of Covilhã (Portugal). From the results obtained it is possible to conclude that the variable with more impact on the pedestrian infrastructure suitability value is the location of the trip generation poles, influenced by the footpaths’ longitudinal slopes. The instrument also allowed to identify the city’s main expansion areas, corresponding to places presenting a good pedestrian potential and relatively low values of population density.

scholarly journals Variable Arrangements Between Residential and Productive Activities: Conceiving Mixed-Use for Urban Development in Brussels

2021 ◽  
Vol 6 (3) ◽  
pp. 334-349
Author(s):  
Michael Ryckewaert ◽  
Jan Zaman ◽  
Sarah De Boeck
Keyword(s):  
Public Space ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Land Uses ◽  
Economic Activities ◽  
Large Cities ◽  
Functional Relationships ◽  
Shared Spaces ◽  
Mixed Use ◽  
Estate Agency

Mixing productive economic activities with housing is a hot topic in academic and policy discourses on the redevelopment of large cities today. Mixed-use is proposed to reduce adverse effects of modernist planning such as single-use zoning, traffic congestion, and loss of quality in public space. Moreover, productive city discourses plead for the re-integration of industry and manufacturing in the urban tissue. Often, historical examples of successful mixed-use in urban areas serve as a guiding image, with vertical symbiosis appearing as the holy grail of the live-work mix-discourse. This article examines three recent live-work mix projects developed by a public real estate agency in Brussels. We investigate how different spatial layouts shape the links between productive, residential, and other land uses and how potential conflicts between residents and economic actors are mediated. We develop a theoretical framework based on earlier conceptualisations of mixed-use development to analyse the spatial and functional relationships within the projects. We situate them within the housing and productive city policies in Brussels. From this analysis, we conclude that mixed-use should be understood by considering spatial and functional relationships at various scales and by studying the actual spatial layout of shared spaces, logistics and nuisance mitigation. Mixed-use is highly contextual, depending on the characteristics of the area as well as policy goals. The vertical symbiosis between different land uses is but one example of valid mixed-use strategies along with good neighbourship, overlap, and tolerance. As such, future commercial and industrial areas will occur in various degrees of mixity in our cities.

scholarly journals Measuring the Influences and Impacts of Signalized Intersection Delay Reduction on the Fuel Consumption, Operation Cost and Exhaust Emissions

2018 ◽  
Vol 4 (3) ◽  
pp. 552 ◽  
Author(s):  
Shamil Ahmed Flamarz Al-Arkawazi
Keyword(s):  
Fuel Consumption ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Transportation Network ◽  
Urban Expansion ◽  
Exhaust Emissions ◽  
Signalized Intersection ◽  
Delay Reduction ◽  
Air Pollutions ◽  
Operation Cost

With the rapid urban expansion and economic development, vehicle fuel dissipation and exhaust emissions have been identified as major energy wastage and urban air pollutions in Kalar City and Iraqi Kurdistan Region in general. Traffic congestion is a growing problem in Kalar City and other urban areas. As it increases, the delay at the transportation network will increase. Any increase of the delay in the transportation network will reflect negatively by increasing the delay at the signalized intersections. Therefore, a study on delay and its relation to fuel consumption, operation cost and emissions at signalized intersection are necessary. This paper, studies the influences and impacts of signalized intersection delay reduction on the fuel consumption, operation cost, and exhaust emissions. A simulation is carried out to evaluate the existing conditions of selected intersections by estimating the intersection delay, operation cost, and emissions. The simulation results show that fuel consumption, operation cost, and emissions are high and directly proportional to the intersection delay. To reduce intersection delay, a signal timing optimization is carried out to the selected intersections. The optimization results show that the delay reduction has a significant influence and impacts in reducing; fuel wastage, operation cost, and exhaust emissions.

Smart Driving System for Improving Traffic Flow

2017 ◽  
Vol 7 (7) ◽  
pp. 236
Author(s):  
Rajesh Kumar Gupta ◽  
L. N. Padhy ◽  
Sanjay Kumar Padhi
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Adaptive Cruise Control ◽  
Human Perception ◽  
Cruise Control ◽  
Driving System ◽  
V2v Communication ◽  
Traffic Conditions ◽  
Cooperative Adaptive Cruise Control

Traffic congestion on road networks is one of the most significant problems that is faced in almost all urban areas. Driving under traffic congestion compels frequent idling, acceleration, and braking, which increase energy consumption and wear and tear on vehicles. By efficiently maneuvering vehicles, traffic flow can be improved. An Adaptive Cruise Control (ACC) system in a car automatically detects its leading vehicle and adjusts the headway by using both the throttle and the brake. Conventional ACC systems are not suitable in congested traffic conditions due to their response delay.  For this purpose, development of smart technologies that contribute to improved traffic flow, throughput and safety is needed. In today’s traffic, to achieve the safe inter-vehicle distance, improve safety, avoid congestion and the limited human perception of traffic conditions and human reaction characteristics constrains should be analyzed. In addition, erroneous human driving conditions may generate shockwaves in addition which causes traffic flow instabilities. In this paper to achieve inter-vehicle distance and improved throughput, we consider Cooperative Adaptive Cruise Control (CACC) system. CACC is then implemented in Smart Driving System. For better Performance, wireless communication is used to exchange Information of individual vehicle. By introducing vehicle to vehicle (V2V) communication and vehicle to roadside infrastructure (V2R) communications, the vehicle gets information not only from its previous and following vehicle but also from the vehicles in front of the previous Vehicle and following vehicle. This enables a vehicle to follow its predecessor at a closer distance under tighter control.

scholarly journals Correlating elements content in mosses collected in 2015 across Germany with spatially associated characteristics of sampling sites and their surroundings

2019 ◽  
Vol 31 (1) ◽  
Author(s):  
Stefan Nickel ◽  
Winfried Schröder
Keyword(s):  
Land Use ◽  
Population Density ◽  
Atmospheric Deposition ◽  
Vegetation Structure ◽  
Urban Areas ◽  
Explanatory Power ◽  
Spatial Density ◽  
Area Index ◽  
Explanatory Variables ◽  
Tree Layer

Abstract Background The aim of the study was a statistical evaluation of the statistical relevance of potentially explanatory variables (atmospheric deposition, meteorology, geology, soil, topography, sampling, vegetation structure, land-use density, population density, potential emission sources) correlated with the content of 12 heavy metals and nitrogen in mosses collected from 400 sites across Germany in 2015. Beyond correlation analysis, regression analysis was performed using two methods: random forest regression and multiple linear regression in connection with commonality analysis. Results The strongest predictor for the content of Cd, Cu, Ni, Pb, Zn and N in mosses was the sampled species. In 2015, the atmospheric deposition showed a lower predictive power compared to earlier campaigns. The mean precipitation (2013–2015) is a significant factor influencing the content of Cd, Pb and Zn in moss samples. Altitude (Cu, Hg and Ni) and slope (Cd) are the strongest topographical predictors. With regard to 14 vegetation structure measures studied, the distance to adjacent tree stands is the strongest predictor (Cd, Cu, Hg, Zn, N), followed by the tree layer height (Cd, Hg, Pb, N), the leaf area index (Cd, N, Zn), and finally the coverage of the tree layer (Ni, Cd, Hg). For forests, the spatial density in radii 100–300 km predominates as significant predictors for Cu, Hg, Ni and N. For the urban areas, there are element-specific different radii between 25 and 300 km (Cd, Cu, Ni, Pb, N) and for agricultural areas usually radii between 50 and 300 km, in which the respective land use is correlated with the element contents. The population density in the 50 and 100 km radius is a variable with high explanatory power for all elements except Hg and N. Conclusions For Europe-wide analyses, the population density and the proportion of different land-use classes up to 300 km around the moss sampling sites are recommended.

scholarly journals Effectiveness of Government Policies in Controlling COVID-19 in India

2020 ◽  
pp. 002073142098374
Author(s):  
Ashutosh Pandey ◽  
Nitin Kishore Saxena
Keyword(s):  
Population Density ◽  
Rural Areas ◽  
Rural Population ◽  
Urban Areas ◽  
Urban Population ◽  
Demographic Factors ◽  
Poverty Rate ◽  
Government Policies ◽  
Cumulative Number ◽  
Population Number

The purpose of this study is to find the demographic factors associated with the spread of COVID-19 and to suggest a measure for identifying the effectiveness of government policies in controlling COVID-19. The study hypothesizes that the cumulative number of confirmed COVID-19 patients depends on the urban population, rural population, number of persons older than 50, population density, and poverty rate. A log-linear model is used to test the stated hypothesis, with the cumulative number of confirmed COVID-19 patients up to period [Formula: see text] as a dependent variable and demographic factors as an independent variable. The policy effectiveness indicator is calculated by taking the difference of the COVID rank of the [Formula: see text]th state based on the predicted model and the actual COVID rank of the [Formula: see text]th state[Formula: see text]Our study finds that the urban population significantly impacts the spread of COVID-19. On the other hand, demographic factors such as rural population, density, and age structure do not impact the spread of COVID-19 significantly. Thus, people residing in urban areas face a significant threat of COVID-19 as compared to people in rural areas.

scholarly journals Constrained Urban Airspace Design for Large-Scale Drone-Based Delivery Traffic

Aerospace ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 38
Author(s):  
Malik Doole ◽  
Joost Ellerbroek ◽  
Victor L. Knoop ◽  
Jacco M. Hoekstra
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Large Scale ◽  
Cost Savings ◽  
Future Research ◽  
Fast Time ◽  
Potential Cost ◽  
Horizontal Structure ◽  
Traffic Demand ◽  
Demand Patterns

Large-scale adoption of drone-based delivery in urban areas promise societal benefits with respect to emissions and on-ground traffic congestion, as well as potential cost savings for drone-based logistic companies. However, for this to materialise, the ability of accommodating high volumes of drone traffic in an urban airspace is one of the biggest challenges. For unconstrained airspace, it has been shown that traffic alignment and segmentation can be used to mitigate conflict probability. The current study investigates the application of these principles to a highly constrained airspace. We propose two urban airspace concepts, applying road-based analogies of two-way and one-way streets by imposing horizontal structure. Both of the airspace concepts employ heading-altitude rules to vertically segment cruising traffic according to their travel direction. These airspace configurations also feature transition altitudes to accommodate turning flights that need to decrease the flight speed in order to make safe turns at intersections. While using fast-time simulation experiments, the performance of these airspace concepts is compared and evaluated for multiple traffic demand densities in terms of safety, stability, and efficiency. The results reveal that an effective way to structure drone traffic in a constrained urban area is to have vertically segmented altitude layers with respect to travel direction as well as horizontal constraints imposed to the flow of traffic. The study also makes recommendations for areas of future research, which are aimed at supporting dynamic traffic demand patterns.

scholarly journals Population Density or Populations Size. Which Factor Determines Urban Traffic Congestion?

2021 ◽  
Vol 13 (8) ◽  
pp. 4280
Author(s):  
Yu Sang Chang ◽  
Sung Jun Jo ◽  
Yoo-Taek Lee ◽  
Yoonji Lee
Keyword(s):  
Population Density ◽  
Population Size ◽  
Traffic Congestion ◽  
Critical Role ◽  
Small Population ◽  
High Density ◽  
Urban Traffic ◽  
Contradictory Result ◽  
Low Density

A large number of articles have documented that as population density of cities increases, car use declines and public transit use rises. These articles had a significant impact of promoting high-density compact urban development to mitigate traffic congestion. Another approach followed by other researchers used the urban scaling model to indicate that traffic congestion increases as population size of cities increases, thus generating a possible contradictory result. Therefore, this study examines the role of both density and population size on traffic congestion in 164 global cities by the use of Stochastic Impacts by Regression on Population, Affluence and Technology model. We divide 164 cities into the two subgroups of 66 low density cities and 98 high density cities for analysis. The findings from the subgroups analysis indicated a clear-cut difference on the critical role of density in low-density cities and the exclusive role of population size in high-density cities. Furthermore, using threshold regression model, 164 cities are divided into the two regions of large and small population cities to determine population scale advantage of traffic congestion. Our findings highlight the importance of including analysis of subgroups based on density and/or population size in future studies of traffic congestion.

scholarly journals META-HEURISTIC APPROACH FOR HIGH-DEMAND FACILITY LOCATIONS CONSIDERING TRAFFIC CONGESTION AND GREENHOUSE GAS EMISSION

2016 ◽  
Vol 24 (4) ◽  
pp. 233-244 ◽  
Author(s):  
Taesung HWANG ◽  
Minho LEE ◽  
Chungwon LEE ◽  
Seungmo KANG
Keyword(s):  
Greenhouse Gas ◽  
Facility Location ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Greenhouse Gas Emission ◽  
Memetic Algorithms ◽  
Distribution Centers ◽  
Ghg Emission ◽  
High Demand ◽  
Facility Locations

Large facilities in urban areas, such as storage facilities, distribution centers, schools, department stores, or public service centers, typically generate high volumes of accessing traffic, causing congestion and becoming major sources of greenhouse gas (GHG) emission. In conventional facility-location models, only facility construction costs and fixed transportation costs connecting customers and facilities are included, without consideration of traffic congestion and the subsequent GHG emission costs. This study proposes methods to find high-demand facility locations with incorporation of the traffic congestion and GHG emission costs incurred by both existing roadway traffic and facility users into the total cost. Tabu search and memetic algorithms were developed and tested with a conventional genetic algorithm in a variety of networks to solve the proposed mathematical model. A case study to determine the total number and locations of community service centers under multiple scenarios in Incheon City is then presented. The results demonstrate that the proposed approach can significantly reduce both the transportation and GHG emission costs compared to the conventional facility-location model. This effort will be useful for decision makers and transportation planners in the analysis of network-wise impacts of traffic congestion and vehicle emission when deciding the locations of high demand facilities in urban areas.

scholarly journals Planning the Urban Waterfront Transformation, from Infrastructures to Public Space Design in a Sea-Level Rise Scenario: The European Union Prize for Contemporary Architecture Case

Water ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 218
Author(s):  
Francesca Dal Cin ◽  
Fransje Hooimeijer ◽  
Maria Matos Silva
Keyword(s):  
Public Space ◽  
Sea Level ◽  
Urban Areas ◽  
Morphological Characteristics ◽  
Public Spaces ◽  
The European Union ◽  
Space Design ◽  
Urban Waterfront ◽  
Mies Van Der Rohe ◽  
The Impact

Future sea-level rises on the urban waterfront of coastal and riverbanks cities will not be uniform. The impact of floods is exacerbated by population density in nearshore urban areas, and combined with land conversion and urbanization, the vulnerability of coastal towns and public spaces in particular is significantly increased. The empirical analysis of a selected number of waterfront projects, namely the winners of the Mies Van Der Rohe Prize, highlighted the different morphological characteristics of public spaces, in relation to the approximation to the water body: near the shoreline, in and on water. The critical reading of selected architectures related to water is open to multiple insights, allowing to shift the design attention from the building to the public space on the waterfronts. The survey makes it possible to delineate contemporary features and lay the framework for urban development in coastal or riverside areas.

scholarly journals Measuring Walkability with GIS—Methods Overview and New Approach Proposal

2021 ◽  
Vol 13 (4) ◽  
pp. 1883
Author(s):  
Agnieszka Telega ◽  
Ivan Telega ◽  
Agnieszka Bieda
Keyword(s):  
Spatial Data ◽  
Urban Areas ◽  
Modern World ◽  
Single Family ◽  
New Approach ◽  
Parks And Recreation ◽  
Gis Tools ◽  
Point Data ◽  
Pedestrian Infrastructure ◽  
Gis Methods

Cities occupy only about 3% of the Earth’s surface area, but half of the global population lives in them. The high population density in urban areas requires special actions to make these areas develop sustainably. One of the greatest challenges of the modern world is to organize urban spaces in a way to make them attractive, safe and friendly to people living in cities. This can be managed with the help of a number of indicators, one of which is walkability. Of course, the most complete analyses are based on spatial data, and the easiest way to implement them is using GIS tools. Therefore, the goal of the paper is to present a new approach for measuring walkability, which is based on density maps of specific urban functions and networks of generally accessible pavements and paths. The method is implemented using open-source data. Density values are interpolated from point data (urban objects featuring specific functions) and polygons (pedestrian infrastructure) using Kernel Density and Line Density tools in GIS. The obtained values allow the calculation of a synthetic indicator taking into account the access by means of pedestrian infrastructure to public transport stops, parks and recreation areas, various attractions, shops and services. The proposed method was applied to calculate the walkability for Kraków (the second largest city in Poland). The greatest value of walkability was obtained for the Main Square (central part of the Old Town). The least accessible to pedestrians are, on the other hand, areas located on the outskirts of the city, which are intended for extensive industrial areas, single-family housing or large green areas.

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