scholarly journals Prediction of motorcyclist traffic crashes in Cartagena (Colombia): development of a safety performance function

2021 ◽  
Author(s):  
Holman Ospina-Mateus ◽  
Leonardo Augusto Quintana Jiménez ◽  
Francisco J. Lopez-Valdes ◽  
Shib Sankar Sana
Keyword(s):  
Road Safety ◽  
Traffic Accidents ◽  
Negative Binomial ◽  
Road Traffic ◽  
Negative Binomial Regression ◽  
Safety Performance ◽  
Traffic Crashes ◽  
Performance Function ◽  
Safety Performance Function ◽  
Significant Factors

Motorcyclists account for more than 380,000 deaths annually worldwide from road traffic accidents. Motorcyclists are the most vulnerable road users worldwide to road safety (28% of global fatalities), together with cyclists and pedestrians. Approximately 80% of deaths are from low- or middle-income countries. Colombia has a rate of 9.7 deaths per 100,000 inhabitants, which places it 10th in the world. Motorcycles in Colombia correspond to 57% of the fleet and generate an average of 51% of fatalities per year. This study aims to identify significant factors of the environment, traffic volume, and infrastructure to predict the number of accidents per year focused only on motorcyclists. The prediction model used a negative binomial regression for the definition of a Safety Performance Function (SPF) for motorcyclists. In the second stage, Bayes' empirical approach is implemented to identify motorcycle crash-prone road sections. The study is applied in Cartagena, one of the capital cities with more traffic crashes and motorcyclists dedicated to informal transportation (motorcycle taxi riders) in Colombia. The data of 2,884 motorcycle crashes between 2016 and 2017 are analyzed. The proposed model identifies that crashes of motorcyclists per kilometer have significant factors such as the average volume of daily motorcyclist traffic, the number of accesses (intersections) per kilometer, commercial areas, and the type of road and it identifies 55 critical accident-prone sections. The research evidences coherent and consistent results with previous studies and requires effective countermeasures for the benefit of road safety for motorcyclists.

scholarly journals Expressway Traffic Accidents Involving Human Injuries and Fatalities in Ethiopia: Negative Binomial Regression Model

2021 ◽  
Author(s):  
Yesuf Abdela Mustefa ◽  
Addis Belayhun
Keyword(s):  
Regression Model ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Negative Binomial ◽  
Road Traffic ◽  
Weather Condition ◽  
Negative Binomial Regression ◽  
Negative Binomial Regression Model ◽  
Level Of Education ◽  
Binomial Regression

Abstract Background: Road traffic accident is a major public health as well as economic challenge that rated the eighth leading cause of death. The severity became higher in developing countries. Ethiopian is among the most confronted countries in the world. We utilized the Ethiopian Toll Roads Enterprise data to provide insights and model significant determinants of accidents involving injuries and fatalities. Besides utilizing recent dataset, we applied the most appropriate but forwent statistical model. Moreover, we examined the significance of the effects of drivers’ age and gender that have not been the cases in the literatures.Methods: We made descriptive insights available on the basis of graphs from integrated traffic accident and flow datasets. We tested for the presence of over-dispersion in a total of 1824 observations of accident data recorded from September, 2014 to December, 2019 for inferential analysis. Finally, we modeled the effects of significant variables on the number of injuries using the negative binomial regression model. Results: we found that the number of injuries in accidents were significantly determined by type of vehicles, ownership status of vehicles, accident time weather condition, driver-vehicle relationship, drivers’ level of education, and drivers’ age.Conclusions: Heavy trucks were more likely to cause more number of injuries than medium or small vehicles. Hot and windy weather conditions were associated with higher probability of the number of injuries. The likelihood of the number of injuries were lower when drivers are owner of the vehicle; drivers level of education is above secondary school; and the age of the driver is between 18 and 23 years old. Moreover, due concern needs to be given for traffic road rules.

scholarly journals Characteristics of Road Traffic Accident Cases Reported in a Tertiary Military Hospital

2020 ◽  
Vol 15 (2) ◽  
pp. 213-217
Author(s):  
Md Moshiur Rahman ◽  
Farzana Zafreen ◽  
Abu Noman Mohammed Mosleh Uddin
Keyword(s):  
Cause Of Death ◽  
Road Safety ◽  
Road Traffic Accident ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Military Hospital ◽  
Road Traffic Accidents ◽  
Traffic Crashes ◽  
Road Traffic Crashes

Introduction: Road traffic accidents (RTA) are the eighth leading cause of death globally, and the leading cause of death in Bangladesh. The road safety situation in Bangladesh has been deteriorating with increasing number of road accident deaths, largely as direct consequences of rapid growth in population, motorization, urbanization and lack of investment in road safety. Objectives: To describe the injury characteristics of road traffic accidents cases that reported at Combined Military Hospital (CMH), Dhaka. Materials and Methods: This descriptive cross-sectional hospital based study was conducted on all the RTA cases reported to medical inspection room CMH, Dhaka from 01 March to 30 June 2010. A total of 126 RTA victims irrespective of age and sex were included, data were collected by face to face interview using a pre-tested questionnaire. Results: A total of 126 road traffic accident victims both sexes were studied. The majority of the study subjects were men 103 (81.7%) and most of them were in 31-40 years group (27%), Muslims (98.41%) were the majority. In our study regarding educational qualification of RTA victims most of them were SSC qualified (44’4%) and primary level (15.1%). Military services holder (45.2%) was the majority of road traffic crash victims. Bus/Minibus (32.5%) was responsible for the majority of road traffic crashes and motor vehicle passengers (42.9%) were main victims. Laceration & cut injury were (38.1%) and multiple injury (18.3%) were the most common injury. Main roads (49.2%) were the commonest site of the accidents.  Regarding place of occurrence main roads 62 (49.2%) was the most common site and noon 41 (32.5%) was the most common time of occurrence of accidents. Conclusion: Road traffic crashes constitute a major public health problem in our setting and contribute significantly to unacceptably high morbidity and mortality. Urgent preventive measures targeting at reducing the occurrence of road traffic crashes is necessary to reduce the morbidity and mortality resulting from these injuries. Early recognition and prompt treatment of road traffic injuries is essential for optimal patient outcome. JAFMC Bangladesh. Vol 15, No 2 (December) 2019: 213-217

scholarly journals Network Screening Methods to Identify Roadway Sites for Safety Investigation: An Examination of Some Critical Issues

2021 ◽  
Author(s):  
Brent Gotts
Keyword(s):  
Traffic Accidents ◽  
Negative Binomial ◽  
Low Cost ◽  
Safety Data ◽  
Negative Binomial Regression ◽  
Economic Losses ◽  
Screening Methods ◽  
Safety Performance Function ◽  
Network Screening ◽  
Critical Issues

Traffic accidents are responsible for about 3,000 deaths and $25 billion in economic losses annually in Canada. One way for transportation authorities to improve safety is to identify potentially hazardous roadway elements through network screening. The process of network screening is a low-cost statistical analysis of highway safety data, which yields a ranked list of sites to be investigated in detail. Critical issues of two network screening methods are investigated in this thesis. The first method is a peak-searching algorithm for screening roadway segments, with attention focused on threshold values of a key user-selected variable, namely the coefficient of variation. The second method examined is a method of screening for high proportions of specific accident types. For this method, parameter estimation techniques are compared, and the effect of the 'critical proportion,' a key user-selected variable in the method, on site rankings is investigated. In addition to the two network screening methods, an investigation is carried out into some aspects of safety performance function calibrated using negative binomial regression. Specific attention is given to how the negative binomial dispension parameter changes over the range of some independent variables.

scholarly journals Analysis of the Impact of Ride-Hailing Services on Motor Vehicles Crashes in Madrid

2021 ◽  
Vol 13 (11) ◽  
pp. 5855
Author(s):  
María Flor ◽  
Armando Ortuño ◽  
Begoña Guirao ◽  
Jairo Casares
Keyword(s):  
Road Safety ◽  
Traffic Accidents ◽  
Negative Binomial ◽  
Positive Impact ◽  
Negative Binomial Regression ◽  
The United States ◽  
Motor Vehicles ◽  
Digital Platforms ◽  
The Sustainable Development ◽  
The Impact

In most cities, discretionary passenger transport by car is predominantly supplied by taxi services. These services face competition from new digital platforms (UBER, Cabify, etc.) that connect users with the services offered by authorized drivers with a license for rented vehicles with drivers (VTC). However, very little is known about the impacts that these services produce in cities where they operate. So far, most studies on this issue have focused on cities of the United States of America, and they broadly found a positive impact in terms of road safety. Road safety has become one of the priority focuses for ensuring social welfare, to the point of being integrated into the Sustainable Development Goals as a primary value to achieve sustainable, safe and responsible mobility. Within this context, the objective of this paper is to analyze the impact of ride-hailing platforms on the frequency of traffic accidents with at least one fatally or seriously injured person in the municipality of Madrid from 2014 to 2018. To do this, a regression analysis has been carried out using a random effects negative binomial regression (RENB). The results of the model show that Uber and Cabify services are associated with a decrease in fatal and serious accidents in Madrid.

scholarly journals Design Criteria for Improving Safety Performance of Rural Intersections

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
S. A. Biancardo ◽  
F. Russo ◽  
W. Zhang ◽  
R. Veropalumbo
Keyword(s):  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Safety Performance ◽  
Fine Tuning ◽  
Local Context ◽  
Crash Risk ◽  
Negative Binomial Regression Model ◽  
Skew Angle ◽  
Safety Performance Function ◽  
The One

This paper, on the one hand, aims to identify significant crash risk factors at unsignalized three-leg intersections connecting rural two-lane two-way roads and minor roads with a STOP control on the approaches (3ST) and, on the other, to make adjustments to the Highway Safety Manual (HSM) procedure, fine-tuning its Safety Performance Function (SPF) based on observation of the local context. Over an 8-year period of study, a total of 240 crashes on 35 3ST intersections were observed, with no geometric-infrastructure adjustments or changes in the Annual Average Daily Traffic (AADT) and surrounding context noted at the intersections investigated. To obtain reliable results, the study period was divided into two groups: (a) 5 years to calibrate a new SPF, and (b) the remaining 3, not included in the first dataset, were used to validate the results. A negative binomial regression model was adopted to calibrate the new SPF. It was found that the AADT on the major and minor roads, the intersection skew angle, the co-occurrence of left and right-turn lanes on the major roads, and lighting seriously affect the crash scenario.

Network Screening Methods to Identify Roadway Sites for Safety Investigation: An Examination of Some Critical Issues

2021 ◽  
Author(s):  
Brent Gotts
Keyword(s):  
Traffic Accidents ◽  
Negative Binomial ◽  
Low Cost ◽  
Safety Data ◽  
Negative Binomial Regression ◽  
Economic Losses ◽  
Screening Methods ◽  
Safety Performance Function ◽  
Network Screening ◽  
Critical Issues

Traffic accidents are responsible for about 3,000 deaths and $25 billion in economic losses annually in Canada. One way for transportation authorities to improve safety is to identify potentially hazardous roadway elements through network screening. The process of network screening is a low-cost statistical analysis of highway safety data, which yields a ranked list of sites to be investigated in detail. Critical issues of two network screening methods are investigated in this thesis. The first method is a peak-searching algorithm for screening roadway segments, with attention focused on threshold values of a key user-selected variable, namely the coefficient of variation. The second method examined is a method of screening for high proportions of specific accident types. For this method, parameter estimation techniques are compared, and the effect of the 'critical proportion,' a key user-selected variable in the method, on site rankings is investigated. In addition to the two network screening methods, an investigation is carried out into some aspects of safety performance function calibrated using negative binomial regression. Specific attention is given to how the negative binomial dispension parameter changes over the range of some independent variables.

scholarly journals Expressway Traffic Accidents Involving Human Injuries and Fatalities in Ethiopia: Negative Binomial Regression Model

2021 ◽  
Author(s):  
Yesuf Abdela Mustefa ◽  
Addis Belayhun
Keyword(s):  
Regression Model ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Negative Binomial ◽  
Road Traffic ◽  
Weather Condition ◽  
Negative Binomial Regression ◽  
Negative Binomial Regression Model ◽  
Level Of Education ◽  
Binomial Regression

Abstract Background: Road traffic accident is a major public health as well as economic challenge that rated the eighth leading cause of death. The severity became higher in developing countries. Ethiopian is among the most confronted countries in the world. We utilized the Ethiopian Toll Roads Enterprise data to provide insights and model significant determinants of accidents involving injuries and fatalities. Besides utilizing recent dataset, we applied the most appropriate but forwent statistical model. Moreover, we examined the significance of the effects of drivers’ age and gender that have not been the cases in the literatures.Methods: We made descriptive insights available on the basis of graphs from integrated traffic accident and flow datasets. We tested for the presence of over-dispersion in a total of 1824 observations of accident data recorded from September, 2014 to December, 2019 for inferential analysis. Finally, we modeled the effects of significant variables on the number of injuries using the negative binomial regression model. Results: we found that the number of injuries in accidents were significantly determined by type of vehicles, ownership status of vehicles, accident time weather condition, driver-vehicle relationship, drivers’ level of education, and drivers’ age.Conclusions: Heavy trucks were more likely to cause more number of injuries than medium or small vehicles. Hot and windy weather conditions were associated with higher probability of the number of injuries. The likelihood of the number of injuries were lower when drivers are owner of the vehicle; drivers level of education is above secondary school; and the age of the driver is between 18 and 23 years old. Moreover, due concern needs to be given for traffic road rules.

Status of Road Safety in the Region of the Americas

2019 ◽  
Keyword(s):  
Dominican Republic ◽  
Road Safety ◽  
Best Practice ◽  
Safety Management ◽  
Road Traffic ◽  
Sustainable Development Goal ◽  
Traffic Crashes ◽  
Road Traffic Crashes ◽  
The Sustainable Development ◽  
Child Restraint

In the three years since the last road safety report was issued, the number of road traffic deaths has continued to increase throughout the Americas, reaching 154,997 deaths in 2016 (latest year of available data). However, the death rate from road traffic crashes has remained stable (15.6 per 100,000 population in 2016 as compared to 15.9 per 100,000 population in 2013). Data presented in this report show that aspects of road safety management, legislation, and post-crash care have improved in some countries. However, the improvements have been modest and it is clear that the Sustainable Development Goal (SDG) target 3.6, to halve road traffic deaths by 2020, will not be achieved... Since 2014, more countries in the Region have implemented road safety legislation. Two additional countries, the Dominican Republic and Uruguay, established laws on drink-driving based on best practice, bringing the total to eight countries. Ecuador implemented legislation on helmet use (resulting in a total of seven countries), Dominican Republic implemented legislation on seat-belts (19 countries in total), while Chile implemented child restraint laws (two countries in total). However, no new speed laws have been enacted in the Region. Overall, four countries (Chile, Dominican Republic, Ecuador, and Uruguay) have amended their laws regarding one or more road safety risk factors to bring them in line with best practice. Despite these legislative developments, enforcement remains a major challenge in most countries...

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