Voice Navigation Effects on Real-World Lane Change Driving Analysis Using an Electroencephalogram | Zendy

Chin-Teng Lin | Zendy; Jung-Tai King | Zendy; Avinash Kumar Singh | Zendy; Akshansh Gupta | Zendy; Zhenyuan Ma | Zendy; Jheng-Wei Lin | Zendy; Alexei Manso Correa Machado | Zendy; Abhishek Appaji | Zendy; Mukesh Prasad | Zendy

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Voice Navigation Effects on Real-World Lane Change Driving Analysis Using an Electroencephalogram

Author(s) -

Chin-Teng Lin,

Jung-Tai King,

Avinash Kumar Singh,

Akshansh Gupta,

Zhenyuan Ma,

Jheng-Wei Lin,

Alexei Manso Correa Machado,

Abhishek Appaji,

Mukesh Prasad

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.2018.2820161

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

Improving the degree of assistance given by in-car navigation systems is an important issue for the safety of both drivers and passengers. There is a vast body of research that assesses the usability and interfaces of the existing navigation systems but very few investigations study the impact on the brain activity based on navigation-based driving. In this paper, a real-world experiment is designed to acquire the electroencephalography (EEG) and in-car information to analyze the dynamic brain activity while the driver is performing the lane-changing task based on the auditory instructions from an in-car navigation system. The results show that auditory cues can influence the speed and increase the frontal EEG delta and beta power, which is related to motor preparation and decision making during a lane change. However, there were no significant results on the alpha power. A better lane-change assessment can be obtained using specific vehicle information (lateral acceleration and heading angle) with EEG features for future naturalized driving study.

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