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International Journal of Automotive Technology > Volume 23(4); 2022 > Article
International Journal of Automotive Technology 2022;23(4): 1127-1140.
doi: https://doi.org/10.1007/s12239-022-0099-6
METHOD OF HMI OPTIMIZATION DESIGN BASED ON FIXATION TRANSITION CHARACTERISTICS AND VISUAL ATTENTION TRAJECTORY: A DRIVER SIMULATOR STUDY
Dunli Hu 1,2, Xinyu Yang 1,2, Xiaohua Zhao 3,4, Xuewei Li 3,4, Xiaofan Feng 1,2, Jiaxia Yang 3,4
1Beijing Key Laboratory of Field-Bus Technology and Automation, North China University of Technology
2College of Electrical and Control Engineering, North China University of Technology
3Beijing Collaborative Innovation Center for Metropolitan Transportation, Beijing University of Technology
4College of Metropolitan Transportation, Beijing University of Technology
PDF Links Corresponding Author.  Xiaohua Zhao  , Email. zhaoxiaohua@bjut.edu.cn
ABSTRACT
To further enhance the role of connected vehicles with the Human-Machine Interface (HMI) in helping drivers in foggy weather, it is meaningful to optimize the HMI based on the driver’s needs. In order to explore the method of HMI optimization, this paper builds a driving simulation experimental test platform of freeway connected vehicle system, designing two experimental scenarios according to the technical conditions (without HMI or with HMI). After that, the paper uses Markov chain to explore the drivers’ fixation transition to identify the driver’s needs in different sections at different conditions. Besides, combined with the visual trajectory results, the paper provides suggestions for optimizing HMI. The results show the review rate of drivers in each section for the straight upper front area is very high. The highest value occurs in the heavy fog zone, suggesting that HMI can provide more road information. HMI should offer a prompt to the driver before entering the warning zone, and remind the driver of changes in the speed limit before entering the fog area. The prompt module of HMI should shorten the horizontal length. In conclusion, this paper aims to propose a general diagnosis method by diagnosing the self-designed HMI.
Key Words: Freeways with heavy fog, Connected vehicle, Human machine interface, Visual transition characteristics, Markov chain, Visual attention trajectory
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