scholarly journals THE CRASH INTENSITY EVALUATION USING GENERAL CENTRALITY CRITERIONS AND A GEOGRAPHICALLY WEIGHTED REGRESSION

2017 ◽  
Vol XLII-4/W4 ◽  
pp. 367-371
Author(s):  
M. Ghadiriyan Arani ◽  
P. Pahlavani ◽  
M. Effati ◽  
F. Noori Alamooti
Keyword(s):  
Geographically Weighted Regression ◽  
Road Traffic ◽  
Hybrid Approach ◽  
Dual Graph ◽  
The United States ◽  
Clustering Coefficient ◽  
Gaussian Kernel ◽  
Weighted Regression ◽  
Road Traffic Crashes ◽  
The Road

Today, one of the social problems influencing on the lives of many people is the road traffic crashes especially the highway ones. In this regard, this paper focuses on highway of capital and the most populous city in the U.S. state of Georgia and the ninth largest metropolitan area in the United States namely Atlanta. Geographically weighted regression and general centrality criteria are the aspects of traffic used for this article. In the first step, in order to estimate of crash intensity, it is needed to extract the dual graph from the status of streets and highways to use general centrality criteria. With the help of the graph produced, the criteria are: Degree, Pageranks, Random walk, Eccentricity, Closeness, Betweenness, Clustering coefficient, Eigenvector, and Straightness. The intensity of crash point is counted for every highway by dividing the number of crashes in that highway to the total number of crashes. Intensity of crash point is calculated for each highway. Then, criteria and crash point were normalized and the correlation between them was calculated to determine the criteria that are not dependent on each other. The proposed hybrid approach is a good way to regression issues because these effective measures result to a more desirable output. R<sup>2</sup> values for geographically weighted regression using the Gaussian kernel was 0.539 and also 0.684 was obtained using a triple-core cube. The results showed that the triple-core cube kernel is better for modeling the crash intensity.

Pedestrian Safety and the Built Environment

2015 ◽  
Vol 30 (4) ◽  
pp. 377-392 ◽  
Author(s):  
Philip Stoker ◽  
Andrea Garfinkel-Castro ◽  
Meleckidzedeck Khayesi ◽  
Wilson Odero ◽  
Martin N. Mwangi ◽  
...  
Keyword(s):  
Built Environment ◽  
Road Traffic ◽  
Pedestrian Safety ◽  
Road Traffic Injury ◽  
Built Environments ◽  
Traffic Crashes ◽  
Road Traffic Crashes ◽  
Urban And Regional Planning ◽  
The Road ◽  
Traffic Injury

Urban and regional planning has a contribution to make toward improving pedestrian safety, particularly in view of the fact that about 273,000 pedestrians were killed in road traffic crashes in 2010. The road is a built environments that should enhance safety and security for pedestrians, but this ideal is not always the case. This article presents an overview of the evidence on the risks that pedestrians face in the built environment. This article shows that design of the roadway and development of different land uses can either increase or reduce pedestrian road traffic injury. Planners need to design or modify the built environment to minimize risk for pedestrians.

scholarly journals An Assessment on the Locational Pattern of Petrol Filling Stations along Lasu-Isheri Road Corridor

2020 ◽  
Vol 6 (2) ◽  
pp. 6-29
Author(s):  
Esther O. Akinsulire ◽  
Samson O. Fadare
Keyword(s):  
Road Traffic ◽  
Traffic Volume ◽  
Primary Data ◽  
Positioning System ◽  
Z Score ◽  
Traffic Crashes ◽  
Road Traffic Crashes ◽  
The Road ◽  
Lagos State ◽  
On The Road

This study aimed at assessing the location and spatial distribution of petrol filling stations along LASU/Isheri Road, Ojo, Lagos state. The objectives are to map out all the petrol filling stations in along Lasu/Isheri road; to examine the volume of traffic along the road corridor; to determine the contribution of petrol filling stations to the traffic volume on the road, and to ascertain the road traffic challenges that are caused by the petrol filling stations (PFS). Geographical Positioning System (GPS) was employed to collect primary data; also, questionnaires and traffic count sheets were employed. The study found that the PFS along the road corridor is clustered with a Z-score of -7.34 and NNI of 0.440285. Also, the maximum peak hour volume was estimated to be 4198.6 pcu/hr. The PFS along the corridor are seen to contribute significantly to the traffic volume on the corridor. Finally, the dominant traffic challenges along the corridor include traffic gridlock which sometimes results into road traffic crashes which are triggered by the concentration of PFS in the study area, the proximity of PFS to a road intersection, overflow of the queue into the roadway, and to a minimal extent parking of tankers along the roadway and lack of setback. This study suggests strategies that can be adopted for locating PFS to ensure the free flow of traffic along the road corridor where they are located.

scholarly journals Practice Analysis of Road Traffic Crashes Accident of a City in China

2012 ◽  
Vol 5 ◽  
pp. 105-110
Author(s):  
Li Wei Hu ◽  
Jian Xiong
Keyword(s):  
Traffic Safety ◽  
Road Traffic ◽  
Crash Severity ◽  
Crash Analysis ◽  
Expected Number ◽  
Traffic Crashes ◽  
Road Traffic Crashes ◽  
Road Crashes ◽  
The Road ◽  
Types Of Information

Many studies focused on the development of crash analysis approaches have resulted in aggregate practices and experiences to quantify the safety effects of human, geometric, traffic and environmental factors on the expected number of deaths, injuries, and/or property damage crashes at specific locations. Traffic crashes on roads are a major cause of road crashes in the metropolitan area of Xi’an. In an attempt to identify causes and consequences, reported traffic crashes for six years in Xi’an were analyzed using a sample of 2038 reports. The main types of information from such reports were extracted, coded, and statistically analyzed. Important results were obtained from frequency analyses as well as multiple contributory factors related to traffic crashes, including crash severity, time and location of occurrence, geometry of the road, AADT and v/c. This paper presents the results of such analyses and provides some recommendations to improve traffic safety and further studies to analyze potential crash locations.

scholarly journals PROVIDING THE FIRE RISK MAP IN FOREST AREA USING A GEOGRAPHICALLY WEIGHTED REGRESSION MODEL WITH GAUSSIN KERNEL AND MODIS IMAGES, A CASE STUDY: GOLESTAN PROVINCE

2017 ◽  
Vol XLII-4/W4 ◽  
pp. 477-481
Author(s):  
A. Shah-Heydari pour ◽  
P. Pahlavani ◽  
B. Bigdeli
Keyword(s):  
Regression Model ◽  
Least Squares ◽  
Geographically Weighted Regression ◽  
Fire Risk ◽  
Ordinary Least Squares ◽  
Gaussian Kernel ◽  
Weighted Regression ◽  
Slope Aspect ◽  
Risk Map ◽  
Geographically Weighted Regression Model

According to the industrialization of cities and the apparent increase in pollutants and greenhouse gases, the importance of forests as the natural lungs of the earth is felt more than ever to clean these pollutants. Annually, a large part of the forests is destroyed due to the lack of timely action during the fire. Knowledge about areas with a high-risk of fire and equipping these areas by constructing access routes and allocating the fire-fighting equipment can help to eliminate the destruction of the forest. In this research, the fire risk of region was forecasted and the risk map of that was provided using MODIS images by applying geographically weighted regression model with Gaussian kernel and ordinary least squares over the effective parameters in forest fire including distance from residential areas, distance from the river, distance from the road, height, slope, aspect, soil type, land use, average temperature, wind speed, and rainfall. After the evaluation, it was found that the geographically weighted regression model with Gaussian kernel forecasted 93.4% of the all fire points properly, however the ordinary least squares method could forecast properly only 66% of the fire points.

Sign in / Sign up

Export Citation Format

Share Document