scholarly journals Risk Factors Affecting Traffic Accidents at Urban Weaving Sections: Evidence from China

2019 ◽  
Vol 16 (9) ◽  
pp. 1542 ◽  
Author(s):  
Xinhua Mao ◽  
Changwei Yuan ◽  
Jiahua Gan ◽  
Shiqing Zhang
Keyword(s):  
Risk Factors ◽  
Traffic Accidents ◽  
Multinomial Logistic Regression ◽  
Weather Condition ◽  
Weather Conditions ◽  
Traffic Density ◽  
Vehicle Speed ◽  
Factors Affecting ◽  
Traffic Characteristics ◽  
Rainy Weather

As a critical configuration of interchanges, the weaving section is inclined to be involved in more traffic accidents, which may bring about severe casualties. To identify the factors associated with traffic accidents at the weaving section, we employed the multinomial logistic regression approach to identify the correlation between six categories of risk factors (drivers’ attributes, weather conditions, traffic characteristics, driving behavior, vehicle types and temporal-spatial distribution) and four types of traffic accidents (rear-end, side wipe, collision with fixtures and rollover) based on 768 accident samples of an observed weaving section from 2016 to 2018. The modeling results show that drivers’ gender and age, weather condition, traffic density, weaving ratio, vehicle speed, lane change behavior, private cars, season, time period, day of week and accident location are important factors affecting traffic accidents at the weaving section, but they have different contributions to the four traffic accident types. The results also show that traffic density of ≥31 vehicle/100 m has the highest risk of causing rear-end accidents, weaving ration of ≥41% has the highest possibility to bring about a side wipe incident, collision with fixtures is the most likely to happen in snowy weather, and rollover is the most likely incident to occur in rainy weather.

scholarly journals Discovering Insightful Rules among Truck Crash Characteristics using Apriori Algorithm

2020 ◽  
Vol 2020 ◽  
pp. 1-16 ◽  
Author(s):  
Jungyeol Hong ◽  
Reuben Tamakloe ◽  
Dongjoo Park
Keyword(s):  
Risk Factors ◽  
Association Rules ◽  
Weather Conditions ◽  
Parametric Models ◽  
Apriori Algorithm ◽  
Drowsy Driving ◽  
Crash Data ◽  
Rainy Weather ◽  
Crash Characteristics ◽  
Strength Of Association

This study aims to discover hidden patterns and potential relationships in risk factors in freight truck crash data. Existing studies mainly used parametric models to analyze the causes of freight vehicle crashes. However, predetermined assumptions and underlying relationships between independent and dependent variables have been cited as its limitations. To overcome these limitations and provide a better understanding of factors that lead to truck crashes on the expressways, we applied the Association Rules Mining (ARM) technique, which is a nonparametric method. ARM quantifies the interrelationships between the antecedents and consequents of truck-involved crashes and provides researchers with the most influential set of factors that leads to crashes. We utilized a freight vehicle-involved crash data consisting of 19,038 crashes that occurred on the Korean expressways from 2008 to 2017 for this investigation. From the data, 90,951 association rules were generated through ARM employing the Apriori algorithm. The lift values estimated by the Apriori algorithm showed the strength of association between risk factors, and based on the estimated lift values, we identified key crash contributory factors that lead to truck-involved crashes at various segment types, under different weather conditions, considering the driver’s age, crash type, driver’s faults, vehicle size, and roadway geometry type. From the generated rules, we demonstrated that overspeeding with medium-weight trucks was highly associated with crashes during the rainy weather, whereas drowsy driving during the evening was correlated with crashes during fine weather. Segment-related crashes were mainly associated with driver’s faults and roadway geometry. Our results present useful insights and suggestions that can be used by transport stakeholders, including policymakers and researchers, to create relevant policies that will help reduce freight truck crashes on the expressways.

scholarly journals Empirical analysis of extreme weather conditions and aviation safety in Nigeria

2016 ◽  
Vol 9 (6) ◽  
pp. 680-690
Author(s):  
C.O. Akanni ◽  
A.M. Hassan ◽  
T.C. Osuji
Keyword(s):  
Traffic Accidents ◽  
Weather Condition ◽  
Secondary Data ◽  
Weather Conditions ◽  
Aviation Safety ◽  
Extreme Weather ◽  
Aviation Industry ◽  
A Value ◽  
Low Visibility ◽  
Safety Accident

The frequency of delay, diversion and outright cancellation occasioned by poor weather has affected the Nigerian aviation industry and serious safety implication.This study therefore examines the influence of weather conditions on aviation safety in Nigeria. Secondary data basically from Nigeria Meteorological Agency such as information on thunderstorm, fog occurrence and rainfall from 2004 to 2013 and data obtained from Federal Airport Authority of Nigeria on air accident induced by extreme weather within the same period were analysed using Multiple Regression Analysis. Results show that low visibility as a result of fog occurrence causes four (4) air traffic accidents more than other weather conditions and that Lagos experienced two (2) air accidents more than other airports during the period under study.  So also the value of R2 shows a value of 77.8% which implies that there is variation in the dependent variable (Airport Operation) which can be predicted by independent variables (Weather conditions). The F-statistic value of 62.892 is also found to be statistically significant at 5% (p<0.05) which shows that weather condition has significant influence on aviation safety. Baseline studies on flight operation, government intervention in aviation industry, maintenance culture were recommended.Keywords: Fog, Thunderstorm, Rainfall, Safety, Accident

Factors Affecting the Impression of Vehicle Speed Gained from a Video Recording

1995 ◽  
Vol 81 (2) ◽  
pp. 472-474
Author(s):  
Stuart Lines ◽  
John Searle
Keyword(s):  
Traffic Accidents ◽  
Marked Effect ◽  
Focal Length ◽  
Video Recording ◽  
Vehicle Speed ◽  
Factors Affecting ◽  
Camera Lens ◽  
Accident Scene

During court hearings arising from traffic accidents, videotaped recordings are often used to give a ‘drive through’ view of the accident scene. A panel of 24 subjects evaluated the impression of speed created by such recordings. Focal length of the camera lens has a marked effect.

scholarly journals Estimation of Crash Severity on Mountainous Freeways in Chongqing

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Yunwei Meng
Keyword(s):  
Traffic Safety ◽  
Traffic Accidents ◽  
Weather Conditions ◽  
Crash Severity ◽  
Driving Experience ◽  
Factors Affecting ◽  
The Past ◽  
Accident Severity ◽  
Partial Proportional Odds Model ◽  
The Times

Mountainous freeways always suffer from accidents due to special terrain, weather conditions, driving environment, and so on. Based on the records of 898 accidents that occurred on mountainous freeways in Chongqing during the past 6 years, the partial proportional odds model is used to identify the factors affecting the accident severity. The time of the accident, season, involvement of trucks, accident characteristics, speeding, maximum driving experience of involved drivers, and weather and road conditions are found to be important for the levels of accident severity. Zero to 6 a.m. and 19 to 24 p.m. are the times prone to serious traffic accidents. The probability of serious traffic accidents in summer and autumn is greater than that in spring and winter. Once a truck is involved in an accident, the consequence is often more severe. Turnover and speeding will result in a grave accident. When there is an experienced driver, the probability of serious traffic accidents is low. The fog is extremely unfavorable weather conditions. The probability of serious accident happening in the downgrade, ramp, curve, bridge, and tunnel sections is greater than the others. The results aim to provide valuable reference for traffic safety on mountainous freeways.

scholarly journals Prevalence and associated factors of motorcycle accident injuries in public Hospitals of Southern Ethiopia.

2019 ◽  
Author(s):  
Fikru Tadesse ◽  
Shewangizaw Mekonnen ◽  
Wondwosen T/Selassie ◽  
Gemechu Kediro ◽  
Negeso Gobena ◽  
...  
Keyword(s):  
Associated Factors ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Steep Descent ◽  
Weather Conditions ◽  
Public Hospitals ◽  
Southern Ethiopia ◽  
Motorcycle Accident ◽  
Rainy Weather ◽  
Accident Injuries

Abstract Objective The objective of this study was to assess the prevalence and associated factors of motorcycle accident injuries in hospitals of Sothern Ethiopia, 2018/2019.Result Of the total 423 road traffic injury, motorcycles were involved in 213 (50.4%) of the road traffic accidents. The presence of poor road conditions like loose gravel, steep descent, and rough road was responsible for 44.6% of motorcycle accident injury. The odds of motorcycle accident injuries were 50% and 52% less likely to occur during sunny and foggy weather conditions respectively compared to rainy weather conditions.

scholarly journals Presentation of Analytical Methods for Better Decision Making about the Most Important Factor Influencing Rural Accidents

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Seyed Mohsen Hosseinian ◽  
Vahid Najafi Moghaddam Gilani ◽  
Hossein Tahmasbi Amoli ◽  
Mohammad Nikookar ◽  
Alireza Orouei
Keyword(s):  
Environmental Factor ◽  
Traffic Accidents ◽  
Surface Condition ◽  
Weather Condition ◽  
Rural Roads ◽  
Factors Affecting ◽  
Vehicle Accidents ◽  
Effective Factor ◽  
The People ◽  
Five Factors

Due to population growth and the increasing number of vehicles on rural roads, traffic accidents have become one of the most important problems in the transportation system, which greatly affects the social and economic situation of the people. The main purpose of this study was to apply the analytical method to investigate the factors affecting the severity of traffic accidents on rural roads of Guilan, Iran, in order to determine the most effective factor in the occurrence of these accidents. At first, the frequency analysis was used to evaluate the variables and their frequency, then the Friedman test (FT) was applied to prioritize the factors, and the exploratory factor analysis (EFA) was used to determine the most effective factor in the occurrence of vehicle accidents in Guilan rural roads. Based on the FT, weather condition was the most important factor effective in these accidents. According to the results of the EFA, five factors were identified as the main factors involved in accidents in which the first factor contributing to accidents was the environmental factor, including weather condition and road surface condition. This indicates that concurrent result of the FT and the EFA, weather condition as an environmental factor, was identified as the most important factor affecting vehicle accidents on rural roads of Guilan. Finally, safety strategies were proposed to increase safety and reduce accidents along these roads.

scholarly journals Analisis Titik Rawan Kecelakaan di Jalan Kertanegara Kabupaten Malang

CANTILEVER ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 27-35
Author(s):  
Rifky Aldila Primasworo ◽  
Andy Kristafi Arifianto
Keyword(s):  
Traffic Accidents ◽  
Black Spot ◽  
Service Level ◽  
Road Accident ◽  
Warning Signs ◽  
Traffic Density ◽  
Vehicle Speed ◽  
Z Score ◽  
Traffic Light ◽  
Traffic Sign

Kertanegara is one of the roads in Malang Regency. The location of Kartanegara Road is considered to be one of the locations prone to accidents due to the lack of traffic infrastructures such as signs and road markings. The road is also an alternative highway that connects Malang Regency to Batu City. The data obtained shows that traffic accidents amounted to 43 of all types of traffic violations from 2016-2018. In 2016, 2017, and 2018, the number of accident victims was 18 accidents, 9 accidents, and 16 accidents. The purpose of this study is to determine the characteristics of Kertanegara road, accident-prone points, and solutions used to reduce the number of accidents. The analytical method used is the analysis of road characteristics, Z-Score, and Cusum analysis. The results obtained that service level of  Kertanegara road is 0.61 where the flow is stable, the traffic density is moderate. Based on the analysis of the determination of accident-prone points, the result of Kartanegara road segment, Malang Regency, has a Z-Score for segment I of 0.25 and segment II of 0.17 which is included in the accident-prone criteria because it has a positive Z-Score. Kartanegara Road has also been identified as a black spot because it has a positive cusum value, including the Cusum segment I values of 7.00 and segment II of 13.3. The solution is to provide a traffic sign in the form of a traffic light at the intersection of Police Karangploso road and the intersection of Sentana road, providing management officer traffic flow in Simpang Nuril road and providing warning signs that are prone to accidents and vehicle speed limit at the Crossroads Kauman I and intersection Nuril road.

scholarly journals Study on Traffic Conflict Prediction Model of Closed Lanes on the Outside of Expressway

Symmetry ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 926
Author(s):  
Huimin Ge ◽  
Mingyue Huang ◽  
Ying Lu ◽  
Yousen Yang
Keyword(s):  
Prediction Model ◽  
Traffic Accidents ◽  
Negative Binomial ◽  
Absolute Error ◽  
Vehicle Speed ◽  
Time To Collision ◽  
Traffic Characteristics ◽  
Traffic Conflicts ◽  
Traffic Conflict ◽  
Conflict Prediction

Due to the randomness and weak symmetry of traffic accidents occurring in the expressway maintenance operation area, it is difficult to use the number of traffic accidents to evaluate the safety of maintenance operation areas. In this paper, the traffic characteristics and traffic conflicts of the maintenance operation area with the lane closed on the outside of the two-way four-lane expressway are studied. By using the statistical method, the distribution of vehicle speed and time headway in different areas of the maintenance operation area are analyzed, and the queuing characteristics of vehicles in the upstream transition zone of the expressway are determined. Based on improved time to collision (TTC) model, the traffic conflict severity of expressway maintenance operation area is divided. The negative binomial distribution is used to establish a traffic conflict prediction model for the enclosed maintenance area of the outer lane of the expressway, and the validity of the traffic conflict prediction model is verified based on the average absolute error percentage (MAPE). The research results show that: when the 0 < TTC < 1.3 s, the traffic conflict is serious conflict; when 1.3 s < TTC, the traffic conflict is non-serious conflict. Furthermore, the traffic conflict prediction model has high accuracy, the MAPE of the warning area and the upstream transition area are 10.8% and 5.0%, respectively.

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