scholarly journals Observations on the Relationship between Crash Frequency and Traffic Flow

Safety ◽  
2021 ◽  
Vol 7 (1) ◽  
pp. 3
Author(s):  
Peter Wagner ◽  
Ragna Hoffmann ◽  
Andreas Leich
Keyword(s):  
Traffic Flow ◽  
Negative Binomial Distribution ◽  
Negative Binomial ◽  
Data Display ◽  
Crash Frequency ◽  
Crash Rates ◽  
Traffic State ◽  
Order Polynomial ◽  
The Relationship ◽  
The City

This work analyzes the relationship between crash frequency N (crashes per hour) and exposure Q (cars per hour) on the macroscopic level of a whole city. As exposure, the traffic flow is used here. Therefore, it analyzes a large crash database of the city of Berlin, Germany, together with a novel traffic flow database. Both data display a strong weekly pattern, and, if taken together, show that the relationship N(Q) is not a linear one. When Q is small, N grows like a second-order polynomial, while at large Q there is a tendency towards saturation, leading to an S-shaped relationship. Although visible in all data from all crashes, the data for the severe crashes display a less prominent saturation. As a by-product, the analysis performed here also demonstrates that the crash frequencies follow a negative binomial distribution, where both parameters of the distribution depend on the hour of the week, and, presumably, on the traffic state in this hour. The work presented in this paper aims at giving the reader a better understanding on how crash rates depend on exposure.

scholarly journals Factors Contributing to the Relationship between Driving Mileage and Crash Frequency of Older Drivers

2019 ◽  
Vol 11 (23) ◽  
pp. 6643 ◽  
Author(s):  
Lee ◽  
Guldmann ◽  
Choi
Keyword(s):  
Negative Binomial ◽  
Age Groups ◽  
Urban Environments ◽  
Vehicle Miles Traveled ◽  
Crash Frequency ◽  
Rural Environments ◽  
Lower Likelihood ◽  
Conditional Autoregressive ◽  
The Relationship ◽  
Binomial Models

As a characteristic of senior drivers aged 65 +, the low-mileage bias has been reported in previous studies. While it is thought to be a well-known phenomenon caused by aging, the characteristics of urban environments create more opportunities for crashes. This calls for investigating the low-mileage bias and scrutinizing whether it has the same impact on other age groups, such as young and middle-aged drivers. We use a crash database from the Ohio Department of Public Safety from 2006 to 2011 and adopt a macro approach using Negative Binomial models and Conditional Autoregressive (CAR) models to deal with a spatial autocorrelation issue. Aside from the low-mileage bias issue, we examine the association between the number of crashes and the built environment and socio-economic and demographic factors. We confirm that the number of crashes is associated with vehicle miles traveled, which suggests that more accumulated driving miles result in a lower likelihood of being involved in a crash. This implies that drivers in the low mileage group are involved in crashes more often, regardless of the driver’s age. The results also confirm that more complex urban environments have a higher number of crashes than rural environments.

scholarly journals Temporal analysis of the relationship between dengue and meteorological variables in the city of Rio de Janeiro, Brazil, 2001-2009

2012 ◽  
Vol 28 (11) ◽  
pp. 2189-2197 ◽  
Author(s):  
Adriana Fagundes Gomes ◽  
Aline Araújo Nobre ◽  
Oswaldo Gonçalves Cruz
Keyword(s):  
Minimum Temperature ◽  
Rio De Janeiro ◽  
Linear Models ◽  
Negative Binomial ◽  
Critical Factor ◽  
Temporal Analysis ◽  
Temporal And Spatial Distribution ◽  
Temperature And Precipitation ◽  
The Relationship ◽  
The City

Dengue, a reemerging disease, is one of the most important viral diseases transmitted by mosquitoes. Climate is considered an important factor in the temporal and spatial distribution of vector-transmitted diseases. This study examined the effect of seasonal factors and the relationship between climatic variables and dengue risk in the city of Rio de Janeiro, Brazil, from 2001 to 2009. Generalized linear models were used, with Poisson and negative binomial distributions. The best fitted model was the one with "minimum temperature" and "precipitation", both lagged by one month, controlled for "year". In that model, a 1°C increase in a month's minimum temperature led to a 45% increase in dengue cases in the following month, while a 10-millimeter rise in precipitation led to a 6% increase in dengue cases in the following month. Dengue transmission involves many factors: although still not fully understood, climate is a critical factor, since it facilitates analysis of the risk of epidemics.

The relationship between IgA activity against 4th-stage larvae and density-dependent effects on the number of 4th-stage larvae ofTeladorsagia circumcinctain naturally infected sheep

Parasitology ◽  
2004 ◽  
Vol 129 (3) ◽  
pp. 363-369 ◽  
Author(s):  
M. J. STEAR ◽  
K. BAIRDEN ◽  
G. T. INNOCENT ◽  
S. MITCHELL ◽  
S. STRAIN ◽  
...  
Keyword(s):  
Negative Binomial Distribution ◽  
Binomial Distribution ◽  
Negative Binomial ◽  
Infection Intensity ◽  
Intensity Of Infection ◽  
Mean Intensity ◽  
Teladorsagia Circumcincta ◽  
The Mean ◽  
Low Levels ◽  
The Relationship

The number ofTeladorsagia circumcincta4th-stage larvae in naturally infected lambs from a single farm varied among lambs and among different years. Within each year the distribution of 4th-stage larvae among lambs was similar to that expected from a negative binomial distribution. The ratio of 4th-stage larvae to adultT. circumcinctawas low in two years with a low mean intensity of infection but high in two years with a higher mean intensity of infection. The negative binomial distribution is defined by the mean and byk, a parameter that measures dispersion;kwas low when mean infection intensity was low but higher when mean infection intensity was high. Askis an inverse index of overdispersion this indicated that the distribution of 4th-stage larvae was more overdispersed at low levels of infection. In a combined analysis, the number of adultT. circumcinctaand the plasma IgA activity against 4th-stage larvae were both associated with increased numbers of 4th-stage larvae. There was a statistical interaction between the number of adults and IgA activity that moderated their combined effect.

scholarly journals Spatial Pattern of Strawberry Powdery Mildew (Podosphaera aphanis) and Airborne Inoculum

Plant Disease ◽  
2014 ◽  
Vol 98 (1) ◽  
pp. 43-54 ◽  
Author(s):  
H. Van der Heyden ◽  
M. Lefebvre ◽  
L. Roberge ◽  
L. Brodeur ◽  
O. Carisse
Keyword(s):  
Powdery Mildew ◽  
Power Law ◽  
Negative Binomial Distribution ◽  
Binomial Distribution ◽  
Negative Binomial ◽  
Disease Incidence ◽  
Data Sets ◽  
Incidence Data ◽  
Airborne Inoculum ◽  
The Relationship

The relationship between strawberry powdery mildew and airborne conidium concentration (ACC) of Podosphaera aphanis was studied using data collected from 2006 to 2009 in 15 fields, and spatial pattern was described using 2 years of airborne inoculum and disease incidence data collected in fields planted with the June-bearing strawberry (Fragaria × ananassa) cultivar Jewel. Disease incidence, expressed as the proportion of diseased leaflets, and ACC were monitored in fields divided into 3 × 8 grids containing 24 100 m2 quadrats. Variance-to-mean ratio, index of dispersion, negative binomial distribution, Poisson distribution, and binomial and beta-binomial distributions were used to characterize the level of spatial heterogeneity. The relationship between percent leaf area diseased and daily ACC was linear, while the relationship between ACC and disease incidence followed an exponential growth curve. The V/M ratios were significantly greater than 1 for 100 and 96% of the sampling dates for ACC sampled at 0.35 m from the ground (ACC0.35m) and for ACC sampled at 1.0 m from the ground (ACC1.0m), respectively. For disease incidence, the index of dispersion D was significantly greater than 1 for 79% of the sampling dates. The negative binomial distribution fitted 86% of the data sets for both ACC1.0m and ACC0.35m. For disease incidence data, the beta-binomial distribution provided a good fit of 75% of the data sets. Taylor's power law indicated that, for ACC at both sampling heights, heterogeneity increased with increasing mean ACC, whereas the binary form of the power law suggested that heterogeneity was not dependent on the mean for disease incidence. When the spatial location of each sampling location was taken into account, Spatial Analysis by Distance Indices showed low aggregation indices for both ACCs and disease incidence, and weak association between ACC and disease incidence. Based on these analyses, it was found that the distribution of strawberry powdery mildew was weakly aggregated. Although a higher level of heterogeneity was observed for airborne inoculum, the heterogeneity was low with no distinct foci, suggesting that epidemics are induced by well-distributed inoculum. This low level of heterogeneity allows mean airborne inoculum concentration to be estimated using only one sampler per field with an overall accuracy of at least 0.841. The results obtained in this study could be used to develop a sampling scheme that will improve strawberry powdery mildew risk estimation.

Impact of Congestion and Traffic Flow on Crash Frequency and Severity: Application of Smartphone-Collected GPS Travel Data

2017 ◽  
Vol 2659 (1) ◽  
pp. 43-54 ◽  
Author(s):  
Joshua Stipancic ◽  
Luis Miranda-Moreno ◽  
Nicolas Saunier
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Quebec City ◽  
Crash Severity ◽  
Crash Frequency ◽  
Crash Data ◽  
Instrumented Vehicles ◽  
Minor Injuries ◽  
The Impact ◽  
The Relationship

Mobility and safety are the two greatest priorities within any transportation system. Ideally, traffic flow enhancement and crash reductions could occur simultaneously, although their relationship is likely complex. The impact of traffic congestion and flow on road safety requires more empirical evidence to determine the direction and magnitude of the relationship. The study of this relationship is an ideal application for instrumented vehicles and surrogate safety measures (SSMs). The purpose of this paper is to correlate quantitative measures of congestion and flow derived from smartphone-collected GPS data with collision frequency and severity at the network scale. GPS travel data were collected in Quebec City, Quebec, Canada, and the sample for this study contained data for more than 4,000 drivers and 20,000 trips. The extracted SSMs, the congestion index (CI), average speed ( V), and the coefficient of variation of speed (CVS) were compared with crash data collected over an 11-year period from 2000 to 2010 with the use of Spearman’s correlation coefficient and pairwise Kolmogorov–Smirnov tests. The correlations with crash frequency were weak to moderate. CI was shown to be positively correlated with crash frequency, and the relationship to crash severity was found to be nonmonotonous. Higher congestion levels were related to crashes with major injuries, whereas low congestion levels were related to crashes with minor injuries and fatalities. Surprisingly, V was found to be negatively correlated with crash frequency and had no conclusive statistical relationship to crash severity. CVS was positively correlated with crash frequency and statistically related to increased crash severity. Future work will focus on the development of a network screening model that incorporates these SSMs.

scholarly journals Urban Intersections and Traffic Safety in the City of San Antonio

2019 ◽  
Vol 271 ◽  
pp. 06003
Author(s):  
Qasim Adegbite ◽  
Khondoker Billah ◽  
Hatim Sharif ◽  
Samer Dessouky
Keyword(s):  
Traffic Safety ◽  
Traffic Control ◽  
San Antonio ◽  
Binary Logistic Regression ◽  
Crash Severity ◽  
Binary Logistic Regression Model ◽  
Crash Frequency ◽  
Crash Rates ◽  
Traffic Control System ◽  
The City

Intersections are high-risk locations on roadways and often experience high incidence of crashes. Better understanding of the factors contributing to crashes and deaths at intersections is crucial. This study analyzed the factors related to crash incidence and crash severity at intersections in San Antonio for crashes from 2013 to 2017 and identified hotspot locations based on crash frequency and crash rates. Binary logistic regression model was considered for the analysis using crash severity as the response variable. Factors found to be significantly associated with the severity of intersection crashes include age of driver, day of the week, month, road alignment, and traffic control system. The crashes occurred predominantly in the highdensity center of the city (downtown area). Overall, the identification of risk factors and their impact on crash severity would be helpful for road safety policymakers to develop proactive mitigation plans to reduce the frequency and severity of intersection crashes.

Case Study using Probe Vehicle Speeds to Assess Roadway Safety in Georgia

2020 ◽  
Vol 2674 (11) ◽  
pp. 554-562
Author(s):  
David J. Ederer ◽  
Michael O. Rodgers ◽  
Michael P. Hunter ◽  
Kari E. Watkins
Keyword(s):  
Performance Monitoring ◽  
Negative Binomial ◽  
Performance Metrics ◽  
Large Body ◽  
Vehicle Speed ◽  
Crash Frequency ◽  
Data Set ◽  
Probe Vehicle ◽  
Performance Metric ◽  
The Relationship

Speed is a primary risk factor for road crashes and injuries. Previous research has attempted to ascertain the relationship between individual vehicle speeds, aggregated speeds, and crash frequency on roadways. Although there is a large body of research linking vehicle speeds to safety outcomes, there is not a widely applied performance metric for safety based on regularly reported speeds. With the increasingly widespread availability of probe vehicle speed data, there is an opportunity to develop network-level safety performance metrics. This analysis examined the relationship between percentile speeds and crashes on a principal arterial in Metropolitan Atlanta. This study used data from the National Performance Metric Research Data Set (NPMRDS), the Georgia Electronic Accident Reporting System, and the Highway Performance Monitoring System. Negative binomial regression models were used to analyze the relationship between speed percentiles, and speed differences to crash frequency on roadway sections. Results suggested that differences in speed percentiles, a measure of speed dispersion, are related to the frequency of crashes. Based on the models, the difference in the 85th percentile and median speed is proposed as a performance metric. This difference is easily measured using NPMRDS probe vehicle speeds, and provides a practical performance metric for assessing safety on roadways.

Exploring the relationship between the length of stay and various determinants at one of the best European destinations

2021 ◽  
pp. 146735842110135
Author(s):  
Elvira Vieira ◽  
Ana Pinto Borges ◽  
Paula Rodrigues
Keyword(s):  
Length Of Stay ◽  
Regression Models ◽  
Negative Binomial ◽  
Economic Factors ◽  
Tourist Destination ◽  
Emotional Factor ◽  
Emotional Factors ◽  
The Relationship ◽  
The City ◽  
Practical Implications

Studies scrutinizing the tangible and intangible factors regarding the length of stay (LOS) in a destination are rare. The emotional factors have not always been integrated into this analysis. We have contributed to fill this gap in the literature considering the degree of happiness with the tourist destination. We used a sample of 1253 tourists and three regression models were estimated (OLS regression model, a Weibull survival model and a zero-truncated negative binomial) to study the LOS. We verified that the emotional factor related with happiness affects the LOS. Furthermore, regarding the managerial/practical implications it is important to highlight that the tourists who intend to visit the city have gastronomic and wine experiences, and, through their contact with the cultural heritage of the city, they will stay for a longer period of time. In addition to economic factors, as expenditures, there are also emotional and experiential aspects that influence LOS and these have to be included in the communication of a tourist destination. The attributes of a destination are not enough to influence the LOS. The destination must also be a set of experiences that will increase the happiness of the tourist with the destination.

Effect of Roadside Features on Single-Vehicle Roadway Departure Crashes on Rural Two-Lane Roads

2012 ◽  
Vol 2309 (1) ◽  
pp. 21-29 ◽  
Author(s):  
Yichuan Peng ◽  
Srinivas Reddy Geedipally ◽  
Dominique Lord
Keyword(s):  
Negative Binomial ◽  
Motor Vehicle ◽  
Large Body ◽  
Crash Frequency ◽  
Side Slope ◽  
Single Vehicle ◽  
Lateral Clearance ◽  
Slope Condition ◽  
The Impact ◽  
The Relationship

One of the most important tasks in traffic safety is investigating the relationship between motor vehicle crashes and the geometric characteristics of roadways. A large body of previous work provides meaningful results on the impact of geometric design on crash frequency. However, little attention has been paid to the relationship between roadway departure crashes and relevant roadside features such as lateral clearance, side slope condition, and driveway density. The lack of roadside data for use in estimating rigorous statistical models has been a major obstacle to roadside safety research for many years. This study investigated the relationship between single-vehicle roadway departure crashes and roadside features. Two types of models were developed: a negative binomial model of crash frequency and a multinomial logit model of crash severity. The study used field data collected in four districts in Texas. The results showed that shoulder width, lateral clearance, and side slope condition had a significant effect on roadway departure crashes. Crash frequency and severity increased when lateral clearance or shoulder width decreased and when the side slope condition became worse. Driveway density was not found to have a significant influence on crash frequency or severity.

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