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Dimensional Evolution of Intelligent Cars Human-Machine Interface considering Take-Over Performance and Drivers’ Perception on Urban Roads

Authors :
Hao Yang
Yueran Wang
Ruoyu Jia
Source :
Complexity, Vol 2020 (2020)
Publication Year :
2020
Publisher :
Wiley, 2020.

Abstract

The study analyzed the drivers’ take-over behaviors in intelligent cars when driving on urban roads and tried to find reasonable dimensions of the human-machine interface. Firstly, the main driving assistance functions in the process of take-over were analyzed based on the entropy theory, and the weight values of each function for the consumer’s purchase intention were calculated. Secondly, we explored the perceived comfortable dimensions of the interactive components under typical interaction modes. By means of experiments using a within-subjects design, the initial population of the evolutionary computation was obtained. The evolutionary mechanism of dimensions driven by users’ perception was constructed with a genetic algorithm. After debugging the parameters of the model, we verified the rationality of the model and evolved appropriate dimensions. Finally, the validity of the evolved dimensions was proved by a controlled experiment and paired-sample t-test. The results indicated that the completion time of most take-over tasks under the HMI with the evolved dimensions was significantly shorter, which ensured the HMI could be more conducive to the take-over quality and traffic efficiency.

Details

Language :
English
ISSN :
10762787 and 10990526
Volume :
2020
Database :
Directory of Open Access Journals
Journal :
Complexity
Publication Type :
Academic Journal
Accession number :
edsdoj.040d8afdacd345f2b1fd12cadf37e666
Document Type :
article
Full Text :
https://doi.org/10.1155/2020/6519236