Citation

Hu D, Yang X, Zhao X, Li X, Feng X, Yang J. Int. J. Automot. Technol. 2022; 23(4): 1127-1140.

Copyright

(Copyright © 2022, Holtzbrinck Springer Nature Publishing Group)

DOI

10.1007/s12239-022-0099-6

PMID

unavailable

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.

Language: en

Keywords

Connected vehicle; Freeways with heavy fog; Human machine interface; Markov chain; Visual attention trajectory; Visual transition characteristics