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The Applications and Challenges of Intelligent Driving Assistance Systems in China’s New Energy Vehicle Industry: A Comprehensive Analysis on its User Experience

Qu, Weihua LU and Yang, Bingshen LU (2024) INFM10 20241
Department of Informatics
Abstract
This master thesis will explore the application and challenge of Intelligent Driving Assistance System (IDAS) within China’s New Energy Vehicle (NEV) industry, aiming to identify and address user experience challenges to enhance interaction with smart driving features. Quantatitive research method, by survey and its analysis, is utilized to underscore the importance of user-centric design in developing IDAS. Key findings indicate that while users appreciate the safety and convenience offered by IDAS, concerns remain in system reliability under adverse weather conditions and issues related to privacy and cybersecurity. This master thesis provides practical recommendations to improve IDAS functionalities that focus in enhancing system... (More)
This master thesis will explore the application and challenge of Intelligent Driving Assistance System (IDAS) within China’s New Energy Vehicle (NEV) industry, aiming to identify and address user experience challenges to enhance interaction with smart driving features. Quantatitive research method, by survey and its analysis, is utilized to underscore the importance of user-centric design in developing IDAS. Key findings indicate that while users appreciate the safety and convenience offered by IDAS, concerns remain in system reliability under adverse weather conditions and issues related to privacy and cybersecurity. This master thesis provides practical recommendations to improve IDAS functionalities that focus in enhancing system reliability, addressing privacy concerns, and ensuring robust cybersecurity measures. These insights may be valuable for manufacturers and policymakers that may contribute for the advancement of user-focused innovations within the NEV industry to promote broader adoption and satisfaction of intelligent driving technologies. (Less)
Please use this url to cite or link to this publication:
author
Qu, Weihua LU and Yang, Bingshen LU
supervisor
organization
course
INFM10 20241
year
type
H1 - Master's Degree (One Year)
subject
language
English
id
9172499
date added to LUP
2024-08-26 09:04:19
date last changed
2024-08-26 09:04:19
@misc{9172499,
  abstract     = {{This master thesis will explore the application and challenge of Intelligent Driving Assistance System (IDAS) within China’s New Energy Vehicle (NEV) industry, aiming to identify and address user experience challenges to enhance interaction with smart driving features. Quantatitive research method, by survey and its analysis, is utilized to underscore the importance of user-centric design in developing IDAS. Key findings indicate that while users appreciate the safety and convenience offered by IDAS, concerns remain in system reliability under adverse weather conditions and issues related to privacy and cybersecurity. This master thesis provides practical recommendations to improve IDAS functionalities that focus in enhancing system reliability, addressing privacy concerns, and ensuring robust cybersecurity measures. These insights may be valuable for manufacturers and policymakers that may contribute for the advancement of user-focused innovations within the NEV industry to promote broader adoption and satisfaction of intelligent driving technologies.}},
  author       = {{Qu, Weihua and Yang, Bingshen}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{The Applications and Challenges of Intelligent Driving Assistance Systems in China’s New Energy Vehicle Industry: A Comprehensive Analysis on its User Experience}},
  year         = {{2024}},
}