Estimation of severe crash frequency using two surrogates
(2022) In Master's Theses in Mathematical Sciences MASM02 20221Mathematical Statistics
- Abstract
- This thesis is concerned with the estimation of crash frequency based on the bivariate modeling of surrogate measures of safety (SMoS), which serve as indicators for traffic risk. Using the SMoS, any traffic conflict between two road users can be described by their proximity together with their hypothetical consequence. We quantify traffic conflicts of different severity as random vector of proximity SMoS and consequential SMoS, and define the traffic risk as the probability measure over the random vector of SMoS pair. We use EVT both in its bivariate context and in approximating the marginal distribution of proximity SMoS, which is combined with copula, to compute the probability of severe collision. The 10-year frequencies of severe... (More)
- This thesis is concerned with the estimation of crash frequency based on the bivariate modeling of surrogate measures of safety (SMoS), which serve as indicators for traffic risk. Using the SMoS, any traffic conflict between two road users can be described by their proximity together with their hypothetical consequence. We quantify traffic conflicts of different severity as random vector of proximity SMoS and consequential SMoS, and define the traffic risk as the probability measure over the random vector of SMoS pair. We use EVT both in its bivariate context and in approximating the marginal distribution of proximity SMoS, which is combined with copula, to compute the probability of severe collision. The 10-year frequencies of severe collision are also computed based on the fitted models. From a methodological point of view, the copula approach with EV margin is more favorable than bivariate EV models, as collisions of lower severity can also be computed. From an implementation point of view, the bivariate EV model is more favorable, as the assumptions on the marginal distribution are defined by the model. The new approach that combines EV distributions and copula is found to have the most accurate estimated crash frequency given that the police report was used a reference, for our data set. (Less)
- Popular Abstract (Swedish)
- Syftet med komplicerad vägplanering minskning av olyckor. Massa pengar och tid behövs om nya vägkonstruktioner skulle byggas. Fråga som förbryllar oss går är: Hur effektiva är vara förändraningar gjört till väg? Vårt problemmet, summanfatta i huvudsak, är en "trade-off" mellan budget och risk av olyckor. Den sämest fall är att förändraingar gör inga skillnader, vilket menar att budget är förlorad samtidigt med absolut noll förbättrningar. Det beror på huvudsakligen två aspekter: antlingen körare bytar sin beteeanden att anpassa nya design, eller vi har identiferat felaktiga risk.
För att bli av med subjektivitet hänvisar vi till "Crash Modification Factor" (CMF) vilken står för minskning/ökning i antalet olyckor efter genomförande av... (More) - Syftet med komplicerad vägplanering minskning av olyckor. Massa pengar och tid behövs om nya vägkonstruktioner skulle byggas. Fråga som förbryllar oss går är: Hur effektiva är vara förändraningar gjört till väg? Vårt problemmet, summanfatta i huvudsak, är en "trade-off" mellan budget och risk av olyckor. Den sämest fall är att förändraingar gör inga skillnader, vilket menar att budget är förlorad samtidigt med absolut noll förbättrningar. Det beror på huvudsakligen två aspekter: antlingen körare bytar sin beteeanden att anpassa nya design, eller vi har identiferat felaktiga risk.
För att bli av med subjektivitet hänvisar vi till "Crash Modification Factor" (CMF) vilken står för minskning/ökning i antalet olyckor efter genomförande av nya design. Principen är CMF bör minska minst 10 procent. Innan vi bestämmer oss, studerar vi CMF i likeande platser där nya design finns redan. Om CMF uppfyllar inte kraven, kanske drar vi slutsätten att sådant nya design är inte nödvändiga. Men beräkning av antalet olyckor är svårt, eftersom olyckor är extremt ovanliga evenemangar. I uppsatsen beräknade vi sannolikheter av allvarliga olyckor, vilka kan kalibrera i modeller för antalet olyckor. Vi även användade en enkel modell som antar konstant trafikflöde och hittade tillfredsställande resultat. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/9089608
- author
- Chen, Zhankun LU
- supervisor
- organization
- course
- MASM02 20221
- year
- 2022
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- Multivariate Extreme Value distributions, Copula, Extreme Value Theory, Crash frequency, Surrogate Meausre of Safety, Road safety
- publication/series
- Master's Theses in Mathematical Sciences
- report number
- LUNFMS-3110-2022
- ISSN
- 1404-6342
- other publication id
- 2022:E47
- language
- English
- id
- 9089608
- date added to LUP
- 2022-08-15 17:48:27
- date last changed
- 2022-08-15 18:15:17
@misc{9089608,
abstract = {{This thesis is concerned with the estimation of crash frequency based on the bivariate modeling of surrogate measures of safety (SMoS), which serve as indicators for traffic risk. Using the SMoS, any traffic conflict between two road users can be described by their proximity together with their hypothetical consequence. We quantify traffic conflicts of different severity as random vector of proximity SMoS and consequential SMoS, and define the traffic risk as the probability measure over the random vector of SMoS pair. We use EVT both in its bivariate context and in approximating the marginal distribution of proximity SMoS, which is combined with copula, to compute the probability of severe collision. The 10-year frequencies of severe collision are also computed based on the fitted models. From a methodological point of view, the copula approach with EV margin is more favorable than bivariate EV models, as collisions of lower severity can also be computed. From an implementation point of view, the bivariate EV model is more favorable, as the assumptions on the marginal distribution are defined by the model. The new approach that combines EV distributions and copula is found to have the most accurate estimated crash frequency given that the police report was used a reference, for our data set.}},
author = {{Chen, Zhankun}},
issn = {{1404-6342}},
language = {{eng}},
note = {{Student Paper}},
series = {{Master's Theses in Mathematical Sciences}},
title = {{Estimation of severe crash frequency using two surrogates}},
year = {{2022}},
}