Traffic Accident Locations Research Articles

An Anthropological Study of People's Attitudes and Beliefs on High Traffic Accident Locations

An Anthropological Study of People's Attitudes and Beliefs on High Traffic Accident Locations

Rute Optimal Keterjangkauan Fasilitas Pelayanan Kesehatan Rumah Sakit terhadap Lokasi Rawan Kecelakaan di Kota Padang

This research aims to; 1) map the distribution of accident locations in Padang Timur Subdistrict. 2) analyze health service facilities to accident-prone points. 3) analyze the optimal route of accident-prone locations to public health facilities. This research method uses quantitative methods and the data used are secondary data and primary data. In getting the results of the distribution pattern of the location point, the researcher uses Averagea Nearest Neighbor while to get the results of the hospital coverage using the Service Area method. The results of this study found that the distribution of areas prone to traffic accidents in East Padang Sub-district in 2022 has a clustered pattern. It is known that the Nearest Neighbor Ratio value is 0.75; the z-score value is -2.17; and the p-value is 0.02. The range of hospitals to the location of traffic accidents on the Padang City Bypass highway has a range of 100 m - 2000 m, from six hospitals in East Padang Subdistrict, there are 15 traffic accidents that are reached and 6 traffic accidents that are not reached by the three hospitals.

Analisis Pola Kecelakaan Lalu Lintas Menggunakan Metode Clustering Studi Kasus Polresta Samarinda

The increase in traffic accidents which cause major consequences, such as injuries and fatalities, can be caused by an increase in population and the need for vehicles in a certain area. It is difficult to predict the time and location of traffic accidents, which are increasing as road length and vehicle movements increase. In the Samarinda Police area, the rapid growth of urbanization and vehicle mobility is a significant challenge in reducing the number of accidents. Statistics show an alarming number of accidents, requiring more effective handling to prevent them from increasing every year. The K-Means clustering algorithm is used in this research to identify accident-prone hours and group road accident data. Six variables including accident rate, number of fatalities, serious injuries, minor injuries, type of accident, and weather were taken from data collected in 2023 by the Samarinda Police Traffic Unit. After data collection, preprocessing and K-Means Clustering stages were carried out using RapidMiner. The results of the analysis help design more effective prevention strategies.

Identifying accident black spots based on the accident spacing distribution

The identification of accident black spots is of great significance for the prevention of traffic accidents. Commonly used accident black spot identification methods divide road sections for the analysis of accident data, the direct result of which is the splitting of accident black spots, which affects the results. This paper is based on three years of traffic accident data from the Beijing–Harbin Expressway, including the time and location of traffic accidents, form of the accident fatalities, severe injuries, slight injuries, and property damage only (PDO). To avoid road division effects, an identification method based on the accident spacing distribution is established by using quality control theory. The results show that the average number of accidents per kilometer by the method proposed in this paper is 42, which is much higher than 10, identified by other identification methods. The method proposed in this paper improves the accuracy of the identification results. This method avoids the problem of road segmentation found in other common methods and can more accurately reflect the spatial distribution of traffic accidents. Thus making the identification of accidents more scientific and accurate. • Reviews and summarizes the identification methods of accident black spots. • Uses the Poisson distribution to avoid the division of road sections. • Introduces the concept of quality control management –3 σ principle provide basis for the method. • Compared with other methods, the accuracy of the method proposed in the paper is higher.

Computing traffic accident high-risk locations using graph analytics

Analysis of the dynamic relationship between traffic accident events and road network topology based on connectivity and graph analytics offers a new approach to identifying, ranking and profiling traffic accident high risk-locations at different levels of space and time granularities. Previous studies on traffic accident hot spots have mostly adopted spatial statistics and Geographic Information Systems (GIS) where spatial point patterns are discovered based only on spatial dependence with no recognition of the temporal dependence of the events. A limitation arises from the fact that the results are either under or over-estimated because of the temporal aggregation of the events to an absolute time point. Furthermore, the existing methods apart from the Network Kernel Density Estimation (NETKDE), consider traffic accident events as events randomly on a 2-D geographic space. However, traffic accident events are network constrained events that happens majorly on the road network space. Therefore, in this paper, we adopt the connectivity of graph on a network space approach that identifies accident high risk-locations based on space-time-varying connectivity between traffic accident events and the road network geometry. A simple but extensible traffic accident space time-varying graph (STVG) model is developed and implemented for this study. Traffic accident high risk-locations are identified and ranked in space and time using time-dependent degree centrality and PageRank centrality graph metrics respectively through time-incremental graph queries. This study offers urban traffic accident analysts with a new and efficient approach to identify, rank and profile accident-prone areas in space and time at different scales.

Identifying the (Hot Spots) for traffic accidents in Erbil City A study of the problems of the Urban Environment

Identifying the (Hot Spots) for traffic accidents in Erbil City A study of the problems of the Urban Environment

Analisis Pengaruh Pola Asuh Terhadap Kecelakaan Lalu Lintas pada Pelajar SMA Menggunakan Regresi Logistik

Injuries due to traffic accidents were ranked eighth as health problem that caused deaths in several countries. Many traffic accidents occur in Africa and Southeast Asia with mortality rate of 26.6 and 20.7 deaths per 100,000 populations in 2016. East Java Province was ranked second as the location of traffic accidents on Java. Surabaya was ranked fifth as a contributor to the large number of road traffic accidents in East Java. The purpose of this study is to identify the relationship between parents’ authoritarian parenting and the experience of teenage traffic accidents while riding a motorcycle. This research is a cross sectional study and uses two stage random sampling method. From the sampling process, as many as 222 students were obtained as respondents. The instrument used in this study consists of personal data and the Parental Authority Questionnaire (PAQ) to identify parenting style. Data analysis was carried out by logistic regression test with α= 5%. The data collection process was carried out during April-October 2017 in public and private high school in Surabaya. Logistic regression test results showed that there is no significant impact between parenting style and traffic accidents experienced by respondents (authoritarian p = 0.966; OR = 0.967, permissive p = 0.616; OR = 1.556). The conclusion of this study is that traffic accidents are not directly affected by parenting style, but it has role in forming individual characteristics, such as decision making and driving attitudes.

Analisis Pengaruh Pola Asuh Terhadap Kecelakaan Lalu Lintas pada Pelajar SMA Menggunakan Regresi Logistik

Injuries due to traffic accidents were ranked eighth as health problem that caused deaths in several countries. Many traffic accidents occur in Africa and Southeast Asia with mortality rate of 26.6 and 20.7 deaths per 100,000 populations in 2016. East Java Province was ranked second as the location of traffic accidents on Java. Surabaya was ranked fifth as a contributor to the large number of road traffic accidents in East Java. The purpose of this study is to identify the relationship between parents’ authoritarian parenting and the experience of teenage traffic accidents while riding a motorcycle. This research is a cross sectional study and uses two stage random sampling method. From the sampling process, as many as 222 students were obtained as respondents. The instrument used in this study consists of personal data and the Parental Authority Questionnaire (PAQ) to identify parenting style. Data analysis was carried out by logistic regression test with α= 5%. The data collection process was carried out during April-October 2017 in public and private high school in Surabaya. Logistic regression test results showed that there is no significant impact between parenting style and traffic accidents experienced by respondents (authoritarian p = 0.966; OR = 0.967, permissive p = 0.616; OR = 1.556). The conclusion of this study is that traffic accidents are not directly affected by parenting style, but it has role in forming individual characteristics, such as decision making and driving attitudes.

Spatial analysis of traffic accidents near and between road intersections in a directed linear network

Although most of the literature on traffic safety analysis has been developed over areal zones, there is a growing interest in using the specific road structure of the region under investigation, which is known as a linear network in the field of spatial statistics. The use of linear networks entails several technical complications, ranging from the accurate location of traffic accidents to the definition of covariates at a spatial micro-level.Therefore, the primary goal of this study was to display a detailed analysis of a dataset of traffic accidents recorded in Valencia (Spain), which were located into a linear network representing more than 30 km of urban road structure corresponding to one district of the city. A set of traffic-related covariates was constructed at the road segment level for performing the analysis. Several issues and methodological approaches that are inherent to linear networks have been shown and discussed. In particular, the network was defined in a way that allowed the explicit investigation of traffic accidents around road intersections and the consideration of traffic flow directionality.Zero-inflated negative binomial count models accounting for spatial heterogeneity were used. Traffic safety at road intersections was specifically taken into account in the analysis by considering the higher variability and number of zeros that can be observed at these road entities and the differential contribution of the covariates depending on the proximity of a road intersection. To complement the results obtained from the count models fitted, coldspots and hotspots along the network were also detected, with explanatory objectives.The models confirmed that spatial heterogeneity, overdispersion and the close presence of road intersections explain the accident counts observed in the road network analyzed. Hotspot detection revealed that several covariates whose contribution was unclear in the modelling approaches may also be affecting accident counts at the road segment level.

Spatial analysis of driving accidents leading to deaths related to motorcyclists in Tehran

PurposeTraffic accidents are one of the main causes of death and disability, causing annual deaths of 1.23 million and tens of millions injured people worldwide. Meanwhile, a significant proportion of the deaths and injuries caused by traffic accidents occur among motorcyclists. According to the world health organization's 2015 report, about 25% of deaths from traffic accidents occur in motorists. In Iran, a significant proportion of deaths and injuries result from traffic accidents among motorcyclists, especially in passages within the cities. According to traffic police, about 25% of deaths and 50% of injuries in traffic accidents of Tehran are reported among motorcyclists. Therefore, due to the importance of this issue, the spatial factors influencing the incidence of motorcycle-related accidents in Tehran were investigated using the geographic information system. MethodsThe present work was a cross-sectional and descriptive analysis study. The data necessary for the study were extracted from Tehran traffic police as well as municipality databases. Zoning maps were used to display the distribution of events. In the analytical investigation, Moran index was used to determine the distribution pattern of the events, while Getis-Ord G * statistics were applied to analyze hot spots. To investigate the role of regional and environmental factors in the frequency of traffic accidents related to motorcyclists in geographic units (Tehran 22 districts), Poisson regression and negative binomial models were used. The geographically weighted regression (GWR) model was used to analyze the relationship between environmental factors and the location of these events. Statistical analyses were performed using SPSS, STATA, ARC-GIS and GWR software. ResultsThe southern and eastern margins of Tehran are the most vulnerable areas in terms of deaths related to traffic accidents of motorcyclists. Highways are considered the location of most traffic accidents which lead to death of motorcyclists. Getis-Ord General G * (p < 0.04) indicates that the distribution of high-risk points is statistically significant. The final model showed that in Tehran, the association of different variables including demographic characteristics, pathways network and type of land use with the number of accidents in geographic units was statistically significant. The spatial distribution of traffic accidents leading to deaths of motorcyclists in the center of Tehran varies considerably with changes in population density, length of highways, volume of traffic, and land use in different parts. ConclusionMost of the traffic accidents leading to deaths of motorcyclists occur in highways. Various environmental variables play a role in determining the distribution pattern of these types of events. Through proper traffic management, controlling environmental risk factors and training people the safety of motorcyclists in Tehran can be improved.

IMPLEMENTASI ALGORITMA FLOYD WARSHALL PADA APLIKASI PENGADUAN MASYARAKAT BERBASIS ANDROID

Public complaints are complaints from the public, Government Agencies or other parties verbally or in writing containing information, complaints, dissatisfaction or irregularities in the performance of the National Police that require further handling and settlement. In conducting complaints, the community usually uses short messages (sms) or telephone so that the community must have a personal contact number of the police member who can be contacted. To make it easier for the public to make complaints, a complaint application is needed to find out the policeman to be contacted. Application that will be developed based on preliminary research that took place at Kuningan Police Station. Mobile-based applications that are needed a lot in searching for police and the location of traffic accidents and providing a description of pastoral events. The application that is created only shows the location of the accident in Kuningan Regency. In finding the nearest route, it will be displayed in the form of maps. The police can choose directions from the details of the complaint, then the system will display the results in the form of a route on maps. In this application there is also a service to find out the location of the community by using GPS technology. And the author uses the Floyd Warshall algorithm to determine the nearest police station and determine the route from the location of the police station to the scene. As well as in storing data in this application the author uses MySQL or phpMyAdmin as a web server in storing event data and police data, notifications and reports concerned with the complaint application. And in the development of this application is based on client-server.Keywords: Floyd Warshall Algorithm, GPS, Kuningan Regency, Mobile, MySQL, Police station, phpMyAdmin, Web Server, Community

Application of a Geographic Information System to Analyze Traffic Accidents Using Nantou County, Taiwan, as an Example

A geographic information system (GIS) is a commonly used method for analyzing traffic accidents. Through a GIS, data regarding traffic accidents can be presented visually, and traffic accident locations can be analyzed. By identifying locations where traffic accidents frequently occur and highway sections with high accident rates, traffic authorities can adopt preventive measures and enforce traffic regulations to reduce the frequency of traffic accidents, deaths, injuries, and financial losses. The present study analyzed tourist traffic accidents in Nantou County, one of the most popular tourist areas in Taiwan for domestic and international travelers, and tabulated statistical data that were subsequently input into a GIS database to determine dangerous locations and areas where traffic accidents are prone to occur. First, administrative regions in Nantou County were identified and kernel density estimation and repeatability analysis were performed to determine locations with high accident rates. The results showed that in Nantou County, traffic accidents often occur between 12:00 and 18:00 at intersections and on sloped roads and windy roads. The most dangerous locations were Provincial Highway 21 (areas around Sun Moon Lake) and Provincial Highway 14A (areas with access to Qingjing and Hehuanshan). The results of this study could serve as a reference for traffic authorities to develop measures for preventing and regulating traffic accidents.

The development of road databases and analysis of traffic accident-prone section (blacksite) based on Geographic Information System (GIS)

Historical data on traffic accidents can provide information on blacksite areas. This can aid in the approach for reducing the number of traffic accidents. Therefore, this research aims to develop database of traffic accidents by the implementation of Quantum Geographic Information System (QGIS) and its interface uses ArcView GIS. We found that there are 69 roads which are identified as the location of traffic accidents. Of these, there are 15 roads as blacksite. The most vulnerable road is the Timor Raya road which has an accident rate (APW) of 813.2 and a UCL value of 71.55. This database provides comprehensive information on geometric conditions of the road, accident data and blacksite, and also features road photographs and cross-sectional road drawings.

Contributing Factors of Traffic Accident and Their Possible Countermeasures in Debre Berhan Town, Ethiopia

Transportation is responsible for the development of civilizations from very old times. However road traffic accident is in a state of rise and recognized as a major socio-economic concern facing Ethiopia as the country. So, this study was conducted with an objective of assessing the traffic safety issue of Debre Berhan town on main highway which serves for the town and cross country traffic. The study followed a methodology of visual investigation of traffic accident location; and speed, traffic volume and traffic accident data collection. According to the data analysis, traffic accident in Debre Berhan was in increasing trend year to year with major accident characteristics of overturning followed by pedestrian accident. In addition, the primary causes of traffic accident in the town are investigated as speeding followed by failure to give way for pedestrian. Minibus and medium bus were responsible for more than 50% of all traffic accident recorded from all categories of vehicles. Around 50% of traffic accidents were contributed from age group of 18 – 30 years that need a primary concern; and the rates of accident on farmers are in alarming rate respect to other victims. Finally, appropriate engineering measures, police enforcement, training and education are recommended to solve the safety problems of the town. The main engineering measures for different location proposed include painted rumple strip to alarm the driver; speed limit sign provision; alternative pedestrian route; restrict parking on some locations that narrow the road and restrict passing; and others. The police enforcement may include on controlling of speeding and assuring the effectiveness of traffic law. A focus on training for young drivers seeking driving license was another recommendation in reduction of traffic accident. In addition, traffic safety education is recommended for students, public workers and farmers for significant reduction of traffic accident.

Statistical Anatomy of Traffic Accidents in Northern Cyprus

In this study, statistical features of traffic accidents in Northern Cyprus (TRNC) especially for the last decade were examined. Such that, risk factors (causes) of traffic accident and their demographic reflections were identified by evaluating official statistics. The main findings of this study are these: Fast driving as the most important cause of traffic accidents; Straight road as the chief location of severe traffic accidents; Inverse relationship between the severe traffic accidents and driver's licenses period (experience); and Inverse relationship between the severe traffic accidents and the age of accused persons.

Options to use rectification program to evaluate degree of conformance of vehicle deformations in multiple damage

The paper deals with the demonstrations of the rectification program usage options in order to evaluate a degree of conformance of vehicle deformations in its multiple damage so as to settle insurance events. It briefly explains the purpose of the rectification program used in the expert analysis of traffic accidents in order to process the photo documentation of a traffic accident location. Furthermore, it clarifies the reason to assess the degree of conformance of vehicle deformations in case of repeated insurance events associated with one vehicle and a common method to evaluate them for the needs of forensic evidence. Subsequently, it demonstrates a method of using the PC Rect rectification program in order to objectively evaluate the degree of conformance of vehicle deformations that developed due to repeated insurance events. In conclusion, an evaluation of the assets of the demonstrated process for the needs of its further usage in technical assessment of the issue in question is carried out.

네트워크 기반 공간 점 패턴 분석을 이용한 교통사고 발생 군집성 분석

본 연구에서는 교통사고 발생위치에 대해 기존의 평면 기반이 아닌 네트워크 기반 공간 점 패턴 분석을 통해 보다 정확한 교통사고 위험도 평가를 목적으로 하고 있다. 서울특별시 교통사고 발생 건수 총 41,662건 중 교통사고 발생이 빈번한 강남구에서 발생한 교통사고 3,536건에 대해 네트워크 기반 K, F, G 함수를 이용하여 공간 점 패턴 분석을 통해 공간적 군집성을 파악하였으며 기존의 평면공간분석 결과와 비교하였다. 분석을 위한 자료는 사고지점을 나타내는 경/위도, 자동차 유형, 성별, 나이, 사고유형, 도로종류, 기상상태, 사망자수, 중상자수 등 총 31개의 변수에 대한 정보가 포함되어 있다. 결과적으로 K, G, F 함수별 모두 군집성 판별에서는 평면과 네트워크 공간 패턴 분석에서 동일한 결과를 제공하지만, 네트워크 기반 공간 패턴 분석의 정확도가 높은 것으로 확인되었다. 본 연구에서 제안한 네트워크 기반 분석을 통해 교통사고 발생위치에 대한 공간 군집성 분석 결과를 이용하여 교통사고 발생 경향을 파악하고 문제점을 해결하는데 활용할 수 있을 것으로 판단된다.The purpose of this study is to compare planar and network spatial analysis of traffic accidents for Gangnam-gu, Seoul. Total 41,662 traffic accident data collected from all over Seoul metropolitan area in 2010. This data includes information on a total 31 variables such as the location of the accident, the type of car, accident and road, weather condition, number of dead and injured, sex and age. Spatial clustering is analyzed by spatial point pattern analysis using K, G and F function based on linear network for 3,536 traffic accidents in Gangnam-gu. The results of the analysis of planar and network spatial pattern in K, G and F function are the same, but the difference of AIC value is smaller in network spatial pattern analysis. Our results are expected that the use of the network spatial point pattern analysis results can be used as a more accurate and correct information providing method to identify the trend of traffic accidents and solve the problems of the location of traffic accidents in the future.

Second-order analysis of point patterns on a network using any distance metric

The analysis of clustering and correlation between points on a linear network, such as traffic accident locations on a street network, depends crucially on how we measure the distance between points. Standard practice is to measure distance by the length of the shortest path. However, this may be inappropriate and even fallacious in some applications. Alternative distance metrics include Euclidean, least-cost, and resistance distances. This paper develops a general framework for the second-order analysis of point patterns on a linear network, using a broad class of distance metrics on the network. We examine the model assumptions that are implicit in choosing a particular distance metric; define appropriate analogues of the K-function and pair correlation function; develop estimators of these characteristics; and study their statistical performance. The methods are tested on several datasets, including a demonstration that different conclusions can be reached using different choices of metric.

“Stationary” point processes are uncommon on linear networks

Statistical methodology for analysing patterns of points on a network of lines, such as road traffic accident locations, often assumes that the underlying point process is “stationary” or “correlation‐stationary.” However, such processes appear to be rare. In this paper, popular procedures for constructing a point process are adapted to linear networks: many of the resulting models are no longer stationary when distance is measured by the shortest path in the network. This undermines the rationale for popular statistical methods such as the K‐function and pair correlation function. Alternative strategies are proposed, such as replacing the shortest‐path distance by another metric on the network. Copyright © 2017 John Wiley &amp; Sons, Ltd.

Extracting accurate location information from a highly inaccurate traffic accident dataset: A methodology based on a string matching technique

The objective of this research was to develop a model for validating traffic accident locations that would be applicable worldwide, regardless of linguistic or cultural differences. In order to achieve this, a Volunteered Geographic Information (VGI) dataset was used, the OpenStreetMap (OSM) project. To test the developed model, a total of 8550 accidents with fatal or non-fatal injuries that occurred in the City of Zagreb from 2010 to 2014 were evaluated. Traffic accident data was collected using the pen-and-paper method while the traffic accident locations were determined using Global Positioning System (GPS) receivers embedded within police vehicles. This form of data entry invariably introduces errors in both geometric and contextual attributes. To fully counteract these errors, the developed model consists of two key concepts: the Jaro–Winkler string matching technique and the Inverse Distance Weighting method. Over 66% of traffic accident locations were validated, which is an increase of 15% when compared to the classical approach. The model outlined in this paper shows a significant improvement in estimating the correct location of traffic accidents. This in turn results in a drastic decrease in resources needed to estimate the quality of accident locations.