Modeling of BRT System Travel Time Prediction Using AVL Data and ANN Approach
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F21%3A43966581" target="_blank" >RIV/49777513:23520/21:43966581 - isvavai.cz</a>
Result on the web
<a href="http://www.istiee.unict.it/sites/default/files/files/ET_2021_84_6.pdf" target="_blank" >http://www.istiee.unict.it/sites/default/files/files/ET_2021_84_6.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.48295/ET.2021.84.6" target="_blank" >10.48295/ET.2021.84.6</a>
Alternative languages
Result language
angličtina
Original language name
Modeling of BRT System Travel Time Prediction Using AVL Data and ANN Approach
Original language description
Improving the quality of public transportation systems and encouraging passengers to use them are effective solutions for reducing transportation problems in metropolitan. Prediction of travel time and providing information to passengers are significant factors in this process. In this research not only the travel time components in Bus Rapid Transit (BRT) system were investigated but also an Artificial Neural Network (ANN) model and a regression model for travel time prediction were presented. To enhance this aim, data was collected by AVL data and field observation and after investigating the primary independent variables, the significant ones were determined using statistical analysis, then ANN development was done. Moreover, linear regression method was used for this purpose. The results prove that although both models have high level of prediction accuracy, ANN model outperform the regression model and the accuracy for the route sections with no signalized intersections is higher than the others.
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
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
European Transport / Trasporti Europei
ISSN
1825-3997
e-ISSN
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Volume of the periodical
84
Issue of the periodical within the volume
6
Country of publishing house
IT - ITALY
Number of pages
16
Pages from-to
1-16
UT code for WoS article
000743358400001
EID of the result in the Scopus database
2-s2.0-85123735748