Application of Extreme Value Theory to Crash Data Analysis

2017 ◽  
Author(s):  
Lan Xu ◽  
Guy Nusholtz
Keyword(s):  
Data Analysis ◽  
Extreme Value Theory ◽  
Value Theory ◽  
Extreme Value ◽  
Crash Data ◽  
Crash Data Analysis

Application of Extreme Value Theory for Before-After Road Safety Analysis

2019 ◽  
Vol 2673 (4) ◽  
pp. 1001-1010 ◽  
Author(s):  
Lai Zheng ◽  
Tarek Sayed
Keyword(s):  
Extreme Value Theory ◽  
Safety Analysis ◽  
Value Theory ◽  
Extreme Value ◽  
Data Traffic ◽  
Crash Data ◽  
Safety Improvement ◽  
Traffic Conflicts ◽  
Traffic Conflict ◽  
Generalized Pareto Distributions

Because of well-recognized quality and quantity problems associated with historical crash data, traffic conflict techniques have been increasingly used in before-after safety analysis in recent years. This study proposes using an extreme value theory (EVT) approach to conduct traffic conflict-based before-after analysis. The capability of providing confident estimation of extreme events by the EVT approach drives the before-after analysis to shift from normal traffic conflicts to more serious conflicts, which are relatively rare but have more in common with actual crashes. The approach is applied to evaluate the safety effects of converting channelized right-turn lanes into smart channels, based on traffic conflicts defined by time to collision (TTC) and collected from three treatment intersections and one control intersection in the city of Penticton, British Columbia. Odds ratios and treatment effects are calculated from extreme-serious conflicts, the frequencies of which are estimated from the generalized Pareto distributions of traffic conflicts with TTC⩽0.5 s. The results show approximately 34% reduction in total extreme-serious conflicts (i.e., combining merging conflicts and rear-end conflicts), indicating overall a remarkable safety improvement following the smart channel treatment. This finding is consistent with the analysis result based on traffic conflicts with TTC⩽3.0 s. It is also found that the reduction in extreme-serious merging conflicts is small and insignificant. This is caused by the phenomenon that TTC values of merging conflicts become smaller after the treatment, and it is possibly because drivers become more aggressive with the better view of approaching cross-street traffic provided by the smart channel.

scholarly journals Topics in data analysis using R in extreme value theory

2013 ◽  
Vol 10 (1) ◽  
Author(s):  
Helena Penalva ◽  
Manuela Neves
Keyword(s):  
Applied Sciences ◽  
Data Analysis ◽  
Open Source Software ◽  
Extreme Value Theory ◽  
Extreme Values ◽  
Value Theory ◽  
Extreme Value ◽  
Extreme Value Statistics ◽  
Data Sets ◽  
Statistics Of Extremes

The statistical Extreme Value Theory has grown gradually from the beginning of the 20th century. Its unquestionable importance in applications was definitely recognized after Gumbel's book in 1958, Statistics of Extremes. Nowadays there is a wide number of applied sciences where extreme value statistics are largely used. So, accurately modeling extreme events has become more and more important and the analysis requires tools that must be simple to use but also should consider complex statistical models in order to produce valid inferences. To deal with accurate, friendly, free and open-source software is of great value for practitioners and researchers. This paper presents a review of the main steps for initializing a data analysis of extreme values in R environment. Some well documented packages are briefly described and two data sets will be considered for illustrating the use of some functions.

scholarly journals Methodology of the Extreme Value Theory Application for Data Analysis

2016 ◽  
Vol 0 (1) ◽  
pp. 47
Author(s):  
Михайло Захарович Згуровський ◽  
Петро Іванович Бідюк ◽  
Світлана Віталіївна Трухан
Keyword(s):  
Data Analysis ◽  
Extreme Value Theory ◽  
Value Theory ◽  
Extreme Value ◽  
Theory Application
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