Modelling the driving speed on expressway ramps based on floating car data

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F22%3A73614893" target="_blank" >RIV/61989592:15310/22:73614893 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/44994575:_____/22:N0000046

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S0263224122002676" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0263224122002676</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.measurement.2022.110995" target="_blank" >10.1016/j.measurement.2022.110995</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Modelling the driving speed on expressway ramps based on floating car data

Popis výsledku v původním jazyce

Driving speed is one of the key concepts and risk factors in transportation research. The insights into operational and safety aspects of driving can be provided by floating car data (FCD), collecting information about speed, position and time by vehicles themselves. FCD are often recorded at high frequency, representing a continuous phenomenon. As such, convenient approach can be functional data analysis (FDA). Speed trajectories are investigated, identifying sections with rapid changes of speed and sections where drives in central and auxiliary lanes cannot be distinguished in terms of their speed. The effect of curvature and auxiliary lanes on driving speed was shown by functional regression models. Significant influence of road shape on speed was found for ramps with complex shape. The accuracy of regression models was assessed by RMSE, NRMSE, and precision of estimators by point-wise confidence intervals. The analysis was performed on an expressway interchange in Brno, Czech Republic.

Název v anglickém jazyce

Modelling the driving speed on expressway ramps based on floating car data

Popis výsledku anglicky

Driving speed is one of the key concepts and risk factors in transportation research. The insights into operational and safety aspects of driving can be provided by floating car data (FCD), collecting information about speed, position and time by vehicles themselves. FCD are often recorded at high frequency, representing a continuous phenomenon. As such, convenient approach can be functional data analysis (FDA). Speed trajectories are investigated, identifying sections with rapid changes of speed and sections where drives in central and auxiliary lanes cannot be distinguished in terms of their speed. The effect of curvature and auxiliary lanes on driving speed was shown by functional regression models. Significant influence of road shape on speed was found for ramps with complex shape. The accuracy of regression models was assessed by RMSE, NRMSE, and precision of estimators by point-wise confidence intervals. The analysis was performed on an expressway interchange in Brno, Czech Republic.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10103 - Statistics and probability

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

MEASUREMENT

ISSN

0263-2241

e-ISSN

1873-412X

Svazek periodika

195

Číslo periodika v rámci svazku

MAY

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

16

Strana od-do

"110995-1"-"110995-16"

Kód UT WoS článku

000793611500001

EID výsledku v databázi Scopus

2-s2.0-85128193433