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Study on the Impact Degrees of Several Driving Behaviors When Driving While Performing Secondary Tasks
Author(s) -
Lisheng Jin,
Baicang Guo,
Yuying Jiang,
Fangrong Wang,
Xianyi Xie,
Ming Gao
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2018.2878150
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Driving while performing secondary tasks is a common phenomenon and can lead to car crashes and human injuries. However, the impact degrees of several secondary tasks have not been determined. To study the importance of several secondary task driving behaviors on driving safety, an eye movement tracking system and a vehicle running state collection system were utilized to determine the laws of behavioral parameters when driving while performing six secondary tasks including Bluetooth calls, cell phone calls, sending text messages, operating car-mounted players, chatting, and singing. Then, an experiment was carried out to collect the evaluation indices of eye movement behaviors and vehicle running statuses. A characteristic extraction method that is based on the gray incidence clustering method was used to extract the characteristic evaluation indices. The generalized gray Euclidean distance was utilized to extract the characteristic evaluation indices. Then, seven characteristic evaluation indices were extracted from 17 evaluation indices. In order to verify the accuracy of the evaluation index system, 17 candidate evaluation indices were screened out to eight by principal component analysis. From this result, the established evaluation index system is all included in eight indices selected by principal component analysis. Furthermore, the characteristic evaluation indices and the six secondary task modes were combined to build the entropy weight decision-making matrix, based on which the weights of each driving behavior mode were determined via the entropy weight method and the impact degrees of the six driving behavior modes on the driving safety were obtained. The results of this research demonstrate that the operation of car-mounted players had the greatest impact on driving safety, whereas making cell phone calls had the least impact.

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