How to Cite
Abstract
The argument developed in this paper is that an understanding of driver experience is central to the development of AV HMIs and should be integral to the design process [1]. We based our analysis partly on van Erp et al.’s (2019) framework but mostly on Khondoker et al.’s (2019) work. They reasoned that the safety benefits for drivers, passengers, pedestrians, and other road users would broadly relate to basic human factors considerations including: vigilance and attention, intention, perception, problem-solving, memory, personality, and emotions. These are the core cognitive competences associated with the concept of “driver experience," which covers physical, social, legal, psychological, and informational factors.emás de profundidad To this we add a focus on the design of the Stars interface and the role of virtual vehicle models on the screen as reifying our purpose. It is evident, from the approach taken, that we also retargeted part of the research structure suggested in the AV HMI design and evaluation automotive design cycle derived from Beatty’s (2004) thinking.
References
H. Muslim and M. Itoh, "Long-Term Evaluation of Drivers’ Behavioral Adaptation to an Adaptive Collision Avoidance System," 2021. ncbi.nlm.nih.gov
D. Zhao, "Application of Neural Network Based on Visual Recognition in Color Perception Analysis of Intelligent Vehicle HMI Interactive Interface under User Experience," 2022. ncbi.nlm.nih.gov
Tatineni, Sumanth. "Security and Compliance in Parallel Computing Cloud Services." International Journal of Science and Research (IJSR) 12.10 (2023): 972-1977.
S. Lee, Y. Cho, and B. C. Min, "Attack-Aware Multi-Sensor Integration Algorithm for Autonomous Vehicle Navigation Systems," 2017. [PDF]
L. Chen, Y. Li, C. Huang, Y. Xing et al., "Milestones in Autonomous Driving and Intelligent Vehicles Part I: Control, Computing System Design, Communication, HD Map, Testing, and Human Behaviors," 2023. [PDF]
M. Scalas and G. Giacinto, "Automotive Cybersecurity: Foundations for Next-Generation Vehicles," 2019. [PDF]
Tatineni, Sumanth. "Compliance and Audit Challenges in DevOps: A Security Perspective." International Research Journal of Modernization in Engineering Technology and Science 5.10 (2023): 1306-1316.
Vemori, Vamsi. "From Tactile Buttons to Digital Orchestration: A Paradigm Shift in Vehicle Control with Smartphone Integration and Smart UI–Unveiling Cybersecurity Vulnerabilities and Fortifying Autonomous Vehicles with Adaptive Learning Intrusion Detection Systems." African Journal of Artificial Intelligence and Sustainable Development3.1 (2023): 54-91.
Shaik, Mahammad, Leeladhar Gudala, and Ashok Kumar Reddy Sadhu. "Leveraging Artificial Intelligence for Enhanced Identity and Access Management within Zero Trust Security Architectures: A Focus on User Behavior Analytics and Adaptive Authentication." Australian Journal of Machine Learning Research & Applications 3.2 (2023): 1-31.
L. Fridman, "Human-Centered Autonomous Vehicle Systems: Principles of Effective Shared Autonomy," 2018. [PDF]
Y. Li, W. Liu, Q. Liu, X. Zheng et al., "Complying with ISO 26262 and ISO/SAE 21434: A Safety and Security Co-Analysis Method for Intelligent Connected Vehicle," 2024. ncbi.nlm.nih.gov
S. N. Saadatmand, "Finding the ground states of symmetric infinite-dimensional Hamiltonians: explicit constrained optimizations of tensor networks," 2019. [PDF]
F. Berman, E. Cabrera, A. Jebari, and W. Marrakchi, "The impact universe—a framework for prioritizing the public interest in the Internet of Things," 2022. ncbi.nlm.nih.gov
F. Farhad Riya, S. Hoque, X. Zhao, and J. Stella Sun, "Smart Driver Monitoring Robotic System to Enhance Road Safety : A Comprehensive Review," 2024. [PDF]
A. Bastola, J. Brinkley, H. Wang, and A. Razi, "Driving Towards Inclusion: Revisiting In-Vehicle Interaction in Autonomous Vehicles," 2024. [PDF]
N. Moghe, M. Steedman, and A. Birch, "Cross-lingual Intermediate Fine-tuning improves Dialogue State Tracking," 2021. [PDF]
S. Jeong, Y. Baek, and S. H. Son, "Component-Based Interactive Framework for Intelligent Transportation Cyber-Physical Systems," 2020. ncbi.nlm.nih.gov
G. Bella, P. Biondi, M. De Vincenzi, and G. Tudisco, "Privacy and modern cars through a dual lens," 2021. [PDF]
A. Biswas and H. C. Wang, "Autonomous Vehicles Enabled by the Integration of IoT, Edge Intelligence, 5G, and Blockchain," 2023. ncbi.nlm.nih.gov
S. M Mostaq Hossain, S. Banik, T. Banik, and A. Md Shibli, "Survey on Security Attacks in Connected and Autonomous Vehicular Systems," 2023. [PDF]
L. Stappen, J. Dillmann, S. Striegel, H. J. Vögel et al., "Integrating Generative Artificial Intelligence in Intelligent Vehicle Systems," 2023. [PDF]