Open AccessUsing the robust statistics for travel time estimation on highways
Author(s) -
Pirc Jure,
Turk Goran,
Žura Marijan
Publication year - 2015
Publication title -
iet intelligent transport systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.579
H-Index - 45
eISSN - 1751-9578
pISSN - 1751-956X
DOI - 10.1049/iet-its.2014.0123
Subject(s) - travel time , estimation , computer science , identification (biology) , intelligent transportation system , license , travel behavior , matching (statistics) , transport engineering , statistics , engineering , mathematics , botany , biology , operating system , systems engineering
Highway operators around the world are using automated vehicle identification (AVI)‐based techniques as a technological input for travel time estimation on highways. Various AVI technologies provide various travel time measurement samples: some of them are able to identify only personal cars (e.g. tolling tags), while others provide mixed samples of all vehicle classes (e.g. license plate matching). As the adequate information on travel times should concern the personal cars, the influence of heavy vehicles (HVs) should be eliminated from the samples, which is not feasible with the use of existing travel time estimation algorithms. It was observed that also during congestion travel times of personal cars and HVs remain dispersed. The motivation for the present study was to introduce an algorithm that would be able to exclude the influence of slower HVs in travel time estimation for technologies, providing mixed samples of travel time measurements. This was achieved by the use of robust statistics. The results of the study could be used by all highway agencies and operators who are encountering problems with unreasonably extended estimations of travel times because of the presence of slow HVs in the traffic flow.