scholarly journals Uncovering the behaviour of road accidents in urban areas

2020 ◽  
Vol 7 (4) ◽  
pp. 191739
Author(s):  
C. Cabrera-Arnau ◽  
R. Prieto Curiel ◽  
S. R. Bishop
Keyword(s):  
Time Series ◽  
Population Size ◽  
Urban Area ◽  
Rural Areas ◽  
Urban Areas ◽  
Road Accident ◽  
Road Accidents ◽  
Accident Data ◽  
The Relationship ◽  
Degrees Of Severity

Different patterns in the incidence of road accidents are revealed when considering areas with increased levels of urbanization. To understand these patterns, road accident data from England and Wales is explored. In particular, the data are used to (i) generate time series for comparison of the incidence of road accidents in urban as opposed to rural areas, (ii) analyse the relationship between the number of road accidents and the population size of a set of urban areas, and (iii) model the likelihood of suffering an accident in an urban area and its dependence with population size. It is observed that minor and serious accidents are more frequent in urban areas, whereas fatal accidents are more likely in rural areas. It is also shown that, generally, the number of accidents in an urban area depends on population size superlinearly, with this superlinear behaviour becoming stronger for lower degrees of severity. Finally, given an accident in an urban area, the probability that the accident is fatal or serious decreases with population size and the probability that it is minor, increases sublinearly. These findings promote the question as to why such behaviours exist, the answer to which will lead to more sustainable urban policies.

scholarly journals Identification of Accident Blackspots on Rural Roads Using Grid Clustering and Principal Component Clustering

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Ling Shen ◽  
Jian Lu ◽  
Man Long ◽  
Tingjun Chen
Keyword(s):  
Rural Areas ◽  
Principal Component ◽  
Road Accident ◽  
Road Accidents ◽  
Segmentation Method ◽  
Rural Roads ◽  
Spatial Unit ◽  
Police Report ◽  
Accident Data ◽  
Grid Based

Identifying road accident blackspots is an effective strategy for reducing accidents. The application of this method in rural areas is different from highway and urban roads as the latter two have complete geographic information. This paper presents (1) a novel segmentation method using grid clustering and K-MEDOIDS to study the spatial patterns of road accidents in rural roads, (2) a clustering methodology using principal component analysis (PCA) and improved K-means to create recognition of road accident blackspots based on segmented results, and (3) using accidents causes in police report to analyze recognition results. The proposed methodology will be illustrated by accident data in Chinese rural area in 2017. A grid-based partition was carried on by using intersection as a basic spatial unit. Appended hazard scores were then added to the segments and using K-means clustering, a result of similar hotspots was completed. The accuracy of the results is verified by the analysis of the cause extracted by Fuzzy C-means algorithm (FCM).

Application of information on road occurrences for the assessment of the social risk of some types of accidents (Zastosowanie informacji o zdarzeniach drogowych do oceny ryzyka społecznego wypadków)

2020 ◽  
Vol 128 ◽  
pp. 37-47
Author(s):  
Anna Borucka ◽  
Małgorzata Grzelak ◽  
Andrzej Świderski ◽  
Arkadiusz Jóźwiak
Keyword(s):  
Relative Risk ◽  
Urban Area ◽  
Urban Areas ◽  
Factor Model ◽  
Road Accident ◽  
Traffic Volume ◽  
Social Risk ◽  
Road Accidents ◽  
Traffic Incidents ◽  
The Social

Every year, in the Pomeranian Voivodeship, around 2 600 road accidents occur, resulting in about 140 death casualties and a further 3200 injuries. For many years there has been a noticeable decrease in the number of traffic incidents in the study area, but the number of fatalities is still high. Therefore, it is crucial to research to determine the causes of the above phenomenon continually. The article aimed to assess the social risk of road accidents based on a two-factor model. Traffic events occurring in built-up and undeveloped areas, depending on the date of their occurrence, were analyzed. The number of accidents and participating vehicles related to the average daily traffic volume was adopted as the measure. The analysis showed that regardless of the area, most events occur on Fridays. Besides, the highest volume of traffic is also recorded on these days of the week. As a result of the conducted research, it was found that March and April are the months with the highest social risk regarding road accidents, both in urban and extra-urban areas. Finally, the relative risk of road accidents in built-up and undeveloped areas was compared. On this basis, it was found that the risk of participation in a road accident in the urban zone is over six times greater than the risk of an event occurring in the extra-urban area (even though urban roads represent only 22% of all road infrastructure in the Pomeranian Voivodeship). Każdego roku na terenie województwa pomorskiego rocznie dochodzi do około 2600 wy-padków drogowych w wyniku, których śmierć ponosi ok 140 osób a kolejnych 3 200 zosta-je rannych. Od wielu lat zauważalny jest spadek liczby zdarzeń komunikacyjnych na bada-nym obszarze, niemniej jednak liczba ofiar śmiertelnych wciąż jest na wysokim poziomie. Dlatego ważnym jest ciągłe pro-wadzenie badań mających na celu ustalenie przyczyn po-wyższego zjawiska. Celem artykułu była ocena ryzyka społecznego powstawania wypadków drogowych przeprowadzona w oparciu o model dwuczynnikowy. Analizie poddano zdarze-nia komunikacyjne mające miejsce na terenie zabudowanym i niezabudowanym w zależ-ności od daty ich powstania. Za miarę przyjęto liczbę wypadków oraz pojazdów w nich uczestniczących w odniesieniu do średniodobowego natężenia ruchu na drogach. Analiza wykazała, że niezależnie od obszaru, najwięcej zdarzeń ma miejsce w piątki. Ponadto, w te dni tygodnia odnotowuje się również największe natężenie ruchu. W wyniku przeprowa-dzonych badań stwierdzono, że marzec i kwiecień są miesiącami o największym ryzyku społecznym dotyczą-cym wypadków drogowych, zarówno w obszarze miejskim i pozamiejskim. Ostatecznie dokonano porównania ryzyka względnego powstawania wy-padków drogowych w terenie zabudowanym i nie-zabudowanym. Na tej podstawie stwier-dzono, że ryzyko uczestnictwa w wypadku drogowym w strefie miejskiej jest przeszło sze-ściokrotnie większe od ryzyka powstania zdarzenia w strefie pozamiejskiej (pomimo, że drogi miejskie stanowią wyłącznie 22% całej infrastruktury drogowej na terenie wojewódz-twa pomorskiego).

scholarly journals Cost-efficient factors in local public spending: Detecting relationships between local environments, population size and urban area category

2021 ◽  
pp. 239980832110038
Author(s):  
Hiroki Baba ◽  
Yasushi Asami
Keyword(s):  
Population Size ◽  
Urban Area ◽  
Urban Areas ◽  
Local Governments ◽  
Statistical Significance ◽  
Population Decline ◽  
Public Spending ◽  
Local Environment ◽  
Environment Factors ◽  
Major Factors

This study examines regional differences in local environment factors to better understand the sustainability of local governments indexed by per capita public spending. Under the condition of heterogeneous population size, we examine how factor characteristics differ depending on the spatial context represented by the urban area category. By employing a Cobb–Douglas cost function with congestion effects on public service provision, the estimated factors enable us to articulate major factors and differences in cost-efficiency between urban area categories. We found that statistical significance and even the signatures of local environment factors differ depending on the urban employment area category. Regarding factors such as the ratios of employees in secondary and tertiary industries, these did not tend to be statistically significant in small-sized urban areas, while small-sized cities in large-sized urban areas were likely to gain confidence intervals. Moreover, we did not observe any statistical significance for the ratio of elderly people due to the balance of spending between national and local governments. These findings could contribute to sustainable management of cities in the advent of population decline.

Relating Household Consumption Expenditures to Road Traffic Fatalities: A Rural–Urban Study

2021 ◽  
pp. 036119812110332
Author(s):  
Ruchika Agarwala ◽  
Vinod Vasudevan
Keyword(s):  
Developing Countries ◽  
Traffic Safety ◽  
Rural Areas ◽  
Urban Areas ◽  
Household Consumption ◽  
Household Expenditure ◽  
Traffic Fatality ◽  
Rural And Urban Areas ◽  
Rural And Urban ◽  
The Relationship

Research shows that traffic fatality risk is generally higher in rural areas than in urban areas. In developing countries, vehicle ownership and investments in public transportation typically increase with economic growth. These two factors together increase the vehicle population, which in turn affects traffic safety. This paper presents a study focused on the relationship of various factors—including household consumption expenditure data—with traffic fatality in rural and urban areas and thereby aims to fill some of the gaps in the literature. One such gap is the impacts of personal and non-personal modes of travel on traffic safety in rural versus urban areas in developing countries which remains unexplored. An exhaustive panel data modeling approach is adopted. One important finding of this study is that evidence exists of a contrasting relationship between household expenditure and traffic fatality in rural and urban areas. The relationship between household expenditure and traffic fatality is observed to be positive in rural areas and a negative in urban areas. Increases in most expenditure variables, such as fuel, non-personal modes of travel, and two-wheeler expenditures, are found to be associated with an increase in traffic fatality in rural areas.

scholarly journals The seasonal variability of the amount of global solar radiation reaching the ground in urban and rural areas on the example of Warsaw and Belsk

2016 ◽  
Vol 20 (4) ◽  
pp. 29-37
Author(s):  
Kinga Nelken ◽  
Kamil Leziak
Keyword(s):  
Solar Radiation ◽  
Urban Area ◽  
Rural Area ◽  
Rural Areas ◽  
Meteorological Data ◽  
Global Solar Radiation ◽  
Urban Station ◽  
Reverse Relationship ◽  
Urban And Rural Areas ◽  
The Relationship

AbstractThe aim of this paper is to determine the contemporary differences in the inflow of global solar radiation in Warsaw (urban station) and Belsk (rural station). The meteorological data used comprised daily sums of global solar radiation (in MJ•m−2) and the duration of sunshine (in hours) for the period 2008 2014. On clear days in spring and summer, the rural area receives more solar radiation in comparison to the urban area, whereas in autumn a reverse relationship occurs. On cloudy days in all seasons, the rural area receives more solar radiation than the urban area, and the relationship is the strongest in winter. Differences between urban and rural areas on cloudy days are smaller than those observed on clear days.

scholarly journals Rise-Up mist-netting (RUM): a mobile protocol for trapping wary territorial birds

2021 ◽  
Vol 61 ◽  
pp. e20216110
Author(s):  
Paulo Sérgio Amorim ◽  
Mariana Fonseca Rossi ◽  
André de Camargo Guaraldo
Keyword(s):  
Urban Area ◽  
Rural Areas ◽  
Urban Areas ◽  
General Public ◽  
Bird Species ◽  
Breeding Period ◽  
The Novel ◽  
Limited Space ◽  
Trapping Methods ◽  
Visual Impacts

Many bird species avoid traditional traps such as mist nets, thus alternative trapping methods are often needed. The Rufous Hornero (Furnariidae: Furnarius rufus) is one such species that was captured so far using conventional mist netting in rural areas or using nest-targeted traps, which risk nest damage and abandonment. Here we describe the novel rise-up mist-netting (RUM) protocol and its catchability for the wary and territorial Rufous Hornero in an urban area. The RUM trap allowed us quickly capturing 40 Rufous Hornero individuals even in paved parking lots and streets during the bird’s breeding period. The RUM is an active and targeted protocol that demands a single and quickly trainable field assistant. Therefore, it should also enable the capture of many understudied territorial but wary species. Moreover, it has enough mobility to fit studies in urban areas, and whenever researchers may deal with limited space and, at the same time, should reduce negative visual impacts to the general public of birds’ capturing and banding procedures.

scholarly journals Machine Learning Approaches to Traffic Accident Analysis and Hotspot Prediction

Computers ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 157
Author(s):  
Daniel Santos ◽  
José Saias ◽  
Paulo Quaresma ◽  
Vítor Beires Nogueira
Keyword(s):  
Machine Learning ◽  
Predictive Model ◽  
Road Accident ◽  
Influential Factors ◽  
Supervised Machine Learning ◽  
Machine Learning Techniques ◽  
Economic Losses ◽  
Learning Approaches ◽  
Road Accidents ◽  
Accident Data

Traffic accidents are one of the most important concerns of the world, since they result in numerous casualties, injuries, and fatalities each year, as well as significant economic losses. There are many factors that are responsible for causing road accidents. If these factors can be better understood and predicted, it might be possible to take measures to mitigate the damages and its severity. The purpose of this work is to identify these factors using accident data from 2016 to 2019 from the district of Setúbal, Portugal. This work aims at developing models that can select a set of influential factors that may be used to classify the severity of an accident, supporting an analysis on the accident data. In addition, this study also proposes a predictive model for future road accidents based on past data. Various machine learning approaches are used to create these models. Supervised machine learning methods such as decision trees (DT), random forests (RF), logistic regression (LR), and naive Bayes (NB) are used, as well as unsupervised machine learning techniques including DBSCAN and hierarchical clustering. Results show that a rule-based model using the C5.0 algorithm is capable of accurately detecting the most relevant factors describing a road accident severity. Further, the results of the predictive model suggests the RF model could be a useful tool for forecasting accident hotspots.

Gender and sexual minorities

2019 ◽  
pp. 258-268
Author(s):  
Richard Bradlow ◽  
Neha Singh ◽  
Suraj Beloskar ◽  
Gurvinder Kalra
Keyword(s):  
Mental Health ◽  
Urban Area ◽  
Rural Areas ◽  
Urban Areas ◽  
Living Environment ◽  
Substantial Impact ◽  
Urban Settings ◽  
Rural And Urban Areas ◽  
Rural And Urban ◽  
Push And Pull

A person’s living environment can have substantial impact on his/her mental health due to a range of factors related to the environment. It has often been argued that urban settings are a hotpot of sociocultural evolutions that attract individuals from the gender and sexual minority (GSM) groups. This has led to migration from rural to urban areas and also from one urban area to another urban area. Various push and pull factors in both the rural and urban areas help GSM individuals decide in which direction to move. While rural areas present with challenges such as social isolation within a homophobic/transphobic environment, urban areas also have their own unique set of challenges for the GSM population. In this chapter, we focus on various factors in both rural and urban settings that impact on the mental health of GSM population.

scholarly journals People’s perception and awareness on air pollution in rural and urban areas of Mymensingh Sadar upazila

2018 ◽  
Vol 29 (1) ◽  
pp. 22-32
Author(s):  
R Sarker ◽  
M Yeasmin ◽  
MA Rahman ◽  
MA Islam
Keyword(s):  
Air Pollution ◽  
Family Size ◽  
Significant Relationship ◽  
Rural Areas ◽  
Urban Areas ◽  
Correlation Coefficients ◽  
Educational Qualification ◽  
Independent Variables ◽  
Rural And Urban Areas ◽  
The Relationship

The present study was conducted to investigate peoples’ perception level and awareness of air pollution in some selected areas of Mymensingh sadar upazila. The relationship of independent variables (age, educational qualification, family size, residence and communication exposure) with the peoples’ perception level and awareness of air pollution (dependent variable) was done to understand the objectives of the study. Six Hundreds (600) respondents were selected randomly from six study sites under Mymensingh sadar upazila for collecting data during the period of Jan 2016-April, 2017. Pearson’s product-moment correlation coefficients were computed to examine the relationship between the concerned variables. The findings revealed that about half (46.67 percent) of the peoples had medium perception and awareness, 31.67 percent had low and 21.67 percent had high perception and awareness about air pollution. In rural areas, 43.33 percent respondents had low, 50.00 percent had medium and only 6.67 percent had high perception and awareness of air pollution. In urban areas, 20.00 percent respondents had low, 43.33 percent had medium and 36.67 percent had high perception and awareness of air pollution. Majority of the respondents (93.33 percent) were lacking of proper awareness of air pollution in rural areas while 63.33 percent in urban areas. Out of five independent variables, three variables such as educational qualification, residence and communication exposure had positive and significant relationship, age had negative and significant relationship and family size had no relationship with their perception and awareness of air pollution.Progressive Agriculture 29 (1): 22-32, 2018

scholarly journals Like Mother, like Son: Physical Activity, Commuting, and Associated Demographic Factors

2020 ◽  
Vol 12 (14) ◽  
pp. 5631 ◽  
Author(s):  
Caroline Brand ◽  
Cézane Priscila Reuter ◽  
Arieli Fernandes Dias ◽  
Jorge Mota ◽  
Michael Duncan ◽  
...  
Keyword(s):  
Physical Activity ◽  
Rural Areas ◽  
Urban Areas ◽  
Skin Color ◽  
Demographic Factors ◽  
Active Commuting ◽  
Cross Sectional ◽  
The Relationship ◽  
Living Area

A mother’s healthy conduct may lead to the healthy conduct of their children. Thus, this study aimed to verify the role of demographic factors in the relationship between mothers’ physical activity (PA) and commuting to work with children and adolescent’s PA and commuting to school. This cross-sectional study comprised 1421 children and adolescents aged 6 to 17 years and 1421 mothers, from Brazil. PA, commuting, socioeconomic status (SES), skin color/ethnicity, and living area were evaluated by questionnaire. Logistic binary regression models were used. Results indicated that mothers’ PA and commuting were associated with children and adolescent’s PA and commuting to school in crude and adjusted models. Considering the role of the demographic factors, an association was only observed for girls in the relationship between mother’s PA with children’s PA. In adolescents, an association was observed in both high/low SES, boys/girls, and rural/urban areas. Regarding children and adolescent active commuting to school, there was an association with mothers commuting. All demographic factors were strongly associated, except for rural areas. Therefore, mothers’ PA as well as commuting to work are associated with children and adolescent’s PA and commuting to school. Sex, living area, and SES are the related demographic factors.

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