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Lane‐changing and freeway capacity: A Bayesian inference stochastic model
Author(s) -
Sala Marcel,
Soriguera Francesc
Publication year - 2020
Publication title -
computer‐aided civil and infrastructure engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.773
H-Index - 82
eISSN - 1467-8667
pISSN - 1093-9687
DOI - 10.1111/mice.12529
Subject(s) - bayesian probability , bayesian inference , computer science , probability density function , reduction (mathematics) , inference , function (biology) , stochastic modelling , transport engineering , mathematics , engineering , statistics , artificial intelligence , geometry , evolutionary biology , biology
This article presents a new stochastic computational model for determining freeway capacity reduction as a result of lane‐changing activity. The probability density function for the maximum flow that can be sustained on a freeway for a given lane‐changing level is obtained. The results can be used to support freeway management strategies aiming to mitigate the negative consequences of lane‐changing in freeway capacity. A pilot test using empirical data obtained from the B‐23 freeway accessing the city of Barcelona proves the validity of the modeling approach.