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.

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 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.

Safety Evaluation of Geometric Design Criteria for Spacing of Entrance–Exit Ramp Sequence and Use of Auxiliary Lanes

2012 ◽  
Vol 2309 (1) ◽  
pp. 12-20 ◽  
Author(s):  
Thanh Q. Le ◽  
Richard J. Porter
Keyword(s):  
Negative Binomial ◽  
Safety Data ◽  
Safety Evaluation ◽  
Negative Binomial Regression ◽  
Geometric Design ◽  
Design Criteria ◽  
Book Design ◽  
Traffic Characteristics ◽  
Auxiliary Lanes ◽  
The Relationship

Geometric design decisions regarding interchange and ramp spacing on freeways have traditionally taken a nominal approach to safety. This approach oversimplifies driver behavior and complex interactions between roadway geometrics, traffic operations, and safety and tends to promote a one-size-fits-all approach to evaluating design alternatives. The objective of this paper was to quantify the relationship between ramp spacing and freeway safety. Data for this study included freeway geometric features, traffic characteristics, and crash counts for 404 freeway segments in California and Washington State. A negative binomial regression modeling approach was used to explore the relationship between ramp spacing and safety. Results indicated that expected crash frequency increased as ramp spacing decreased. The expected proportion of crashes resulting in a fatality or injury appeared to decrease as ramp spacing decreased. The presence of an auxiliary lane was associated with a lower expected frequency of crashes for any given ramp spacing; the safety benefits of providing an auxiliary lane diminished as ramp spacing increased. The model results related to ramp spacing and the presence of an auxiliary lane were transformed into crash modification factors and validated through comparisons with an independent research study on weaving areas in Texas. The safety findings were generally consistent with current Green Book design criteria related to ramp spacing and the presence of an auxiliary lane. The ability to quantify the expected impact on safety of ramp spacing associated with new or modified interchanges will assist transportation agencies in making well-informed assessments of the overall benefits, impacts, and costs of freeway access decisions.

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):  
Traffic Accidents ◽  
Negative Binomial ◽  
Weather Condition ◽  
Negative Binomial Regression ◽  
Weather Conditions ◽  
Negative Binomial Regression Model ◽  
Level Of Education ◽  
Binomial Regression ◽  
Windy Weather ◽  
And Gender

Abstract Objective The purpose of this study is to provide insights and to model significant determinants of accidents involving injuries and fatalities using Ethiopian Toll Roads Enterprise data. Besides, we utilized recent dataset recorded from September, 2014 to December, 2019. 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. 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. 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 Effect of Transportation Parameters on Traffic Accident in Urban Areas Comparison study of ANFIS With Statistical Analysis

2021 ◽  
Vol 11 (2) ◽  
pp. 129-134
Author(s):  
Ghassan M. Suleiman ◽  
Mohammad K. Younes ◽  
Murat Ergun ◽  
Khaled Al Omari
Keyword(s):  
Urban Areas ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Negative Binomial ◽  
Fuzzy Inference ◽  
Negative Binomial Regression ◽  
Anfis Model ◽  
Inference System ◽  
Neuro Fuzzy ◽  
Binomial Regression

Traffic accidents present a serious problem for both developed and developing countries and have become an urgent matter to tackle in all large metropolitan areas. This study aims to perform a deep comprehensive analysis of the traffic accidents issue in Istanbul, one of the world’s most populous cities. The accidents were classified and its intensities were presented on Istanbul map using a GIS tool. Furthermore, the performance of Negative Binomial Regression analysis and Adaptive Neuro-Fuzzy Inference System (ANFIS) model was assessed. Data collection of independent variables included distribution of trips, percentage of street parking, rate of car ownership, street density and population density. Trips were divided into three categories, passenger car, minibus and bus trips. The results showed that four legs intersection got the highest proportion of accidents among the other types with (40%). It also demonstrated that increasing both the percentage of bus trips and the percentage of street parking will decrease the traffic accident rate. Furthermore, the implementation of ANFIS model increased the accuracy of forecasts and reduced errors more than the regression model.

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.

Combined Crash Frequency–Crash Severity Evaluation of Geometric Design Decisions

2015 ◽  
Vol 2521 (1) ◽  
pp. 54-63 ◽  
Author(s):  
M. Scott Shea ◽  
Thanh Q. Le ◽  
Richard J. Porter
Keyword(s):  
Regression Models ◽  
Negative Binomial ◽  
High Sensitivity ◽  
Negative Binomial Regression ◽  
Crash Severity ◽  
Crash Frequency ◽  
Design Decisions ◽  
Crash Data ◽  
Safety Performance Function ◽  
Traffic Characteristics

This paper quantified the effects of freeway ramp spacing and auxiliary lane presence on crash frequency and crash severity. Crash frequencies were predicted with a safety performance function, and crash severities were estimated with what was termed a “severity distribution function.” The paper then demonstrated how to combine quantitative knowledge related to the effects of ramp spacing and auxiliary lane presence on both crash frequency and severity into a framework for assessing the overall crash cost for different ramp configurations. Geometric features, traffic characteristics, and crash data were collected for 404 freeway segments in California and Washington State. Negative binomial regression models and multinomial logit regression models were used to estimate the effects of ramp spacing and auxiliary lane presence on expected crash frequencies and crash severities, respectively. Results showed that expected multiple-vehicle crash frequency increased as ramp spacing decreased. Meanwhile, there was a decrease in the proportion of severe crashes (fatal, incapacitating injury) with a decrease in ramp spacing, even though the overall frequency of these severe crashes remained relatively unchanged. Providing an auxiliary lane was expected to decrease crash frequency, although this reduction appeared to be primarily in crashes that were less severe (possible injury and property damage only). The findings appeared to effectively capture the complex relationships between geometric designs and operations and the high sensitivity between speed and crash severity. The paper provided quantitative tools for making informed freeway and interchange design decisions where ramp spacing and auxiliary lanes were considerations.

scholarly journals Field Efficacy of Larvivorous Fish and Pyriproxyfen Combined with Community Engagement on Dengue Vectors in Cambodia: A Randomized Controlled Trial

2021 ◽  
Author(s):  
John Christian Hustedt ◽  
Dyna Doum ◽  
Vanney Keo ◽  
Sokha Ly ◽  
BunLeng Sam ◽  
...  
Keyword(s):  
Vector Control ◽  
Adult Female ◽  
Negative Binomial ◽  
Low Cost ◽  
Controlled Trial ◽  
Negative Binomial Regression ◽  
Primary Analysis ◽  
Larvivorous Fish ◽  
Randomized Controlled ◽  
The Impact

Evidence on the effectiveness of low-cost, sustainable biological vector control tools for Aedes mosquitoes is limited. Therefore, the purpose of this trial was to estimate the impact of guppy fish in combination with the larvicide pyriproxyfen (PPF) (Sumilarv® 2MR) and communication for behavioral impact (COMBI) activities to reduce entomological indices in Cambodia. In this cluster randomized, controlled superiority trial, 30 clusters comprised of one or more villages each was allocated in a 1:1:1 ratio to receive either 1) all three interventions (guppies, PPF, and COMBI), 2) two interventions (guppies and COMBI), or 3) control (standard vector control). Entomological surveys among 40 randomly selected households per cluster were carried out quarterly. The primary outcome was the population abundance of adult female Aedes mosquitoes trapped using adult resting collections. In the primary analysis, adult female Aedes abundance and mosquito infection rates was aggregated over follow-up time points to give a single rate per cluster. These data were analyzed by negative binomial regression, yielding abundance ratios (ARs). The number of Aedes females was reduced roughly by half compared with the control in both the guppy, PPF, and COMBI arm (AR = 0.54; 95% CI, 0.34–0.85; P = 0.0073); and the guppy and COMBI arm (AR = 0.49; 95% CI, 0.31–0.77; P = 0.0021). The effectiveness demonstrated and extremely low cost of including fish rearing in community-based health structures suggest they should be considered as a vector control tool as long as the benefits outweigh any potential environmental concerns. Sumilarv® 2MR was also highly accepted and preferred over current vector control tools used in Cambodia.

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