Assessment of Conversational Chatbots for Driving Support Applications
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21260%2F25%3A00390688" target="_blank" >RIV/68407700:21260/25:00390688 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21730/25:00390688
Result on the web
<a href="https://doi.org/10.14311/NNW.2025.35.001" target="_blank" >https://doi.org/10.14311/NNW.2025.35.001</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.14311/NNW.2025.35.001" target="_blank" >10.14311/NNW.2025.35.001</a>
Alternative languages
Result language
angličtina
Original language name
Assessment of Conversational Chatbots for Driving Support Applications
Original language description
The study evaluated chatbots designed as conversational assistants for drivers with the aim of reducing driver fatigue through appropriate and undemanding conversation. The introductory part included a questionnaire survey focused on identifying preferred topics of conversation while driving, which provided a basis for selecting the content focus of the experiment. This was followed by a subjective evaluation of selected chatbots using user experience metrics, focusing on their comprehensibility, naturalness, and ability to maintain attention without increasing mental load. The final part used the QFD method to assess the extent to which individual chatbot procedures and features met the set criteria. The output was a comparison of chatbots and a determination of their suitability for further extensive experiments.
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
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Neural Network World
ISSN
1210-0552
e-ISSN
2336-4335
Volume of the periodical
35
Issue of the periodical within the volume
1
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
16
Pages from-to
1-16
UT code for WoS article
001738205700001
EID of the result in the Scopus database
2-s2.0-105035805196