Developing speed-related safety performance indicators from floating car data
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F44994575%3A_____%2F23%3A10003644" target="_blank" >RIV/44994575:_____/23:10003644 - isvavai.cz</a>
Result on the web
<a href="https://ietresearch.onlinelibrary.wiley.com/doi/full/10.1049/itr2.12281" target="_blank" >https://ietresearch.onlinelibrary.wiley.com/doi/full/10.1049/itr2.12281</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1049/itr2.12281" target="_blank" >10.1049/itr2.12281</a>
Alternative languages
Result language
angličtina
Original language name
Developing speed-related safety performance indicators from floating car data
Original language description
In the road traffic safety domain there is a need for using proactive (non-crash-based) indicators, known as safety performance indicators (SPIs). Traffic speed based on big data (floating car data [FCD]) could help develop network-wide SPIs, but related knowledge and experience are insufficient so far. The authors attempted to fill this gap by using nationwide Italian FCD to develop speed-related SPIs and validating their relationship to crashes to see their potential explanatory value. The authors calculated the coefficient of variance (CV), congestion index (CI), and the number of incidents as candidate SPIs. For validation, the authors used linear correlation, crash frequency model, and ranking consistency. Incidents turned out to be the best SPI, especially for motorways.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20104 - Transport engineering
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
IET INTELLIGENT TRANSPORT SYSTEMS
ISSN
1751-9578
e-ISSN
1751-9578
Volume of the periodical
17
Issue of the periodical within the volume
3
Country of publishing house
US - UNITED STATES
Number of pages
9
Pages from-to
553-561
UT code for WoS article
000863674000001
EID of the result in the Scopus database
2-s2.0-85139126300