Author(s)

Yu Quan ¹, Wangchuan Yang ¹, Yangchao Jie ¹, Songshu Jian ¹

Affiliation(s)

¹ School of Electrical and Control Engineering, North China University of Technology, Beijing, China

Corresponding Author

Wangchuan Yang

ABSTRACT

This study investigates the determinants of driver trust in semi-autonomous vehicles through an integrated theoretical framework. Building upon established automation trust models and empirical observations of current system deployments, we identify eight critical antecedents: system predictability, automation reliability, interface transparency, human-machine interaction design, anthropomorphism, contextual driving scenarios, inherent user traits, and information accuracy. A structural equation model (SEM) was developed to test 12 hypothesized relationships. Methodologically, we adapted measurement scales from prior literature through iterative pilot testing (N=45), culminating in a validated 28-item questionnaire. Empirical data from 231 valid responses (total collection: 276) were analyzed using SmartPLS 3.0, incorporating: 1) confirmatory factor analysis assessing convergent validity (AVE=0.61-0.79), discriminant validity (HTMT<0.85), and composite reliability (CR=0.83-0.91); 2) bootstrapped mediation analysis (5,000 subsamples); and 3) path coefficient evaluation (β=0.18-0.43, p<0.05). Results reveal that seven determinants significantly predict trust formation, with system transparency demonstrating the strongest total effect (β=0.41, p<0.001). Theoretical implications for human-automation collaboration and practical guidelines for ADAS interface optimization are discussed.

KEYWORDS

Semi-autonomous vehicles; Trust formation; System determinants; Psychometric questionnaire; Structural Equation Modeling (SEM)

CITE THIS PAPER

Yu Quan, Wangchuan Yang, Yangchao Jie, Songshu Jian, Investigating the Determinants of Driver Trust in Semi-Autonomous Vehicle Systems: A Multidimensional Analysis. Frontiers in Traffic and Transportation Engineering (2025) Vol. 5: 12-24. DOI: http://dx.doi.org/10.23977/ftte.2025.050102.

REFERENCES

[1] Wang, Y. X., & Chen, H. (2022). Trust Abuse and Trust Deficiency in Human-Machine Trust. Advances in Psychology, 12(8), 6. DOI:10.12677/AP.2022.128317. 
[2] French, B , Duenser, A , Heathcote, A. (2018). Trust in Automation–A Literature Review. CSIRO, Australia.
[3] Tan, Z. Y., Zhang, R. F., Liu, Z. Z., et al. (2024). Research Status and Prospects of Human-Machine Interaction Trust in Intelligent Connected Vehicles. Journal of Mechanical Engineering, Beijing. [Online]. Available: [URL].
[4] Sun, X. F., Zhao, Y., & Lyu, C. M. (2022). Influence Mechanism of Human-Machine Interaction Trust in Autonomous Vehicles. Journal of Northeastern University (Natural Science), 43(9). DOI:10.12068/j. issn.1005-3026.2022.09.013.
[5] Hoff K A, Bashir M .Trust in Automation: Integrating Empirical Evidence on Factors That Influence Trust[J]. Human Factors The Journal of the Human Factors and Ergonomics Society, 2015, 57(3):407-434.
[6] Koo J, Kwac J, Ju W, et al.Why did my car just do that? Explaining semi-autonomous driving actions to improve driver understanding, trust, and performance[J]. International Journal on Interactive Design and Manufacturing, 2014, 9, 269 - 275.
[7] Verberne F M F , Ham J , Midden C J H .Trust in smart systems: sharing driving goals and giving information to increase trustworthiness and acceptability of smart systems in cars[J]. Human Factors, 2012, 54(5):799-810.
[8] Cramer H, Evers V, Kemper N, et al. Effects of autonomy, traffic conditions and driver personality traits on attitudes and trust towards in-vehicle agents[C].  In 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, 2008, 477–482.
[9] Du N, Haspiel J, Zhang Q, et al. Look Who's Talking Now: Implications of AV's Explanations on Driver's Trust, AV Preference, Anxiety and Mental Workload[J]. Transportation Research Part C Emerging Technologies, 2019, 104, 428-442.
[10] Hergeth S, Lorenz L, Krems J F. Prior familiarization with takeover requests affects drivers’ takeover performance and automation trust[J]. Human Factors: The Journal of the Human Factors and Ergonomics Society, 2017, 59(3), 457–470. 
[11] Jonsson I M, Harris H, Nass C. How accurate must an in-car information system be? Consequences of accurate and inaccurate information in cars[C]. Conference on Human Factors in Computing Systems. DBLP, 2008, DOI:10.1145/1357054.1357315.
[12] Petersen L, Tilbury D, Yang J, et al. Effects of Augmented Situational Awareness on Driver Trust in Semi-Autonomous Vehicle Operation[C]. Ground Vehicle Systems Engineering & Technology Symposium, 2017.
[13] Kraus J, Scholz D, Stiegemeier D, et al. The More You Know: Trust Dynamics and Calibration in Highly Automated Driving and the Effects of Take-Overs, System Malfunction, and System Transparency. Hum Factors, 2020, 62(5):718-736.
[14] Mishler S. Whose drive is it anyway? Using multiple sequential drives to establish patterns of learned trust, error cost, and non-active trust repair while considering daytime and nighttime differences as a proxy for difficulty[C]// Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction (HRI '20). New York: ACM, 2020: 439-448. DOI:10.1145/3319502.3374819.  
[15] Shi, Y. W. (2019). The Impact of Environmental Perception on Human-Machine Trust in L2 Autonomous Driving [Master's thesis]. Hangzhou: Zhejiang University.
[16] Endsley M R. Toward a Theory of Situation Awareness in Dynamic Systems[J].  Human Factors, 1995, 37(1):32-64. 
[17] Endsley M. R. Designing for situation awareness: An approach to user-centered design[J]. CRC press, 2016.
[18] Helldin T, Falkman G, Riveiro M, et al. Presenting system uncertainty in automotive UIs for supporting trust calibration in autonomous driving[C]// Proceedings of the 5th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI '13). New York: ACM, 2013: 210-217. DOI:10.1145/2516540.2516554.  
[19] Kunze A, Summerskill S J, Marshall R, et al.Automation transparency: implications of uncertainty communication for human-automation interaction and interfaces[J]. Ergonomics, 2019, 62(3):345-360.
[20] Niu D F, Terken J M, Eggen B. Anthropomorphizing information to enhance trust in autonomous vehicles[J]. Human Factors and Ergonomics in Manufacturing & Service Industries, 2018, 28, 352 - 359.
[21] Epley N , Waytz A , Cacioppo J T .On Seeing Human: A Three-Factor Theory of Anthropomorphism[J]. Psychological Review, 2007, 114(4):864-86.
[22] Renate Häuslschmid, Max Von Bülow, Pfleging B, et al. Supporting trust in autonomous driving[C]// Proceedings of the 22nd International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI '17). New York: ACM, 2017: 1-12. DOI:10.1145/3025171.3025198. 
[23] Lee J G, Kim K J, Lee S, et al.Can Autonomous Vehicles Be Safe and Trustworthy? Effects of Appearance and Autonomy of Unmanned Driving Systems[J]. International Journal of Humancomputer Interaction, 2015, 31(10-12):682-691.
[24] Forster Y , Naujoks F , Neukum A. Increasing anthropomorphism and trust in automated driving functions by adding speech output[C]. IEEE Intelligent Vehicles Symposium, 2017. 
[25] Waytz A, Heafner J, Epley N. The Mind in the Machine: Anthropomorphism Increases Trust in an Autonomous Vehicle[J]. Journal of Experimental Social Psychology, 2014, 52(3):113-117.
[26] Zihsler J, Hock P, Walch M, et al. Carvatar: Increasing trust in highly-automated driving through social cues[C]// Proceedings of the 8th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI '16). New York: ACM, 2016: 9-16. DOI:10.1145/3004323.3004354.
[27] Li W, Yao N, Shi Y, et al.Personality Openness Predicts Driver Trust in Automated Driving[J]. Automotive Innovation Engineering, 2020, 3(1):11.DOI:10.1007/s42154-019-00086-w.
[28] Zhang Q, Robert L P, Du N, et al.Trust in AVs: The Impact of Expectations and Individual Differences[C]. Conference on Autonomous Vehicles in Society: Building a Research Agenda.2018.
[29] Merritt S M, Ilgen D R. Not All Trust Is Created Equal: Dispositional and History-Based Trust in Human-Automation Interactions[J]. Human Factors, 2008, 50(2):194.
[30] Beggiato M, Krems J F. The evolution of mental model, trust and acceptance of adaptive cruise control in relation to initial information[J]. Transportation Research Part F Psychology & Behaviour, 2013, 18(5):47-57.
[31] Zhang, H. N., & Xu, Z. L. (2021). Research on the Formation Mechanism of Consumer Trust in Affiliate Cross-Border E-Commerce Platforms: An Integrated Perspective Based on Information Processing and Trust Transfer. Journal of Yanbian University (Social Science Edition), 54(3), 93-101.

Sponsors, Associates, and Links

---

• Advances in Naval Architecture and Ocean Engineering
  
  
• Journal of Vehicle and Intelligent Transport System
  
  
• Urban Transport Systems
  
  
• Journal of Connected Vehicles