Literature DB >> 32919220

Exploring drivers' mental workload and visual demand while using an in-vehicle HMI for eco-safe driving.

Xiaomeng Li1, Atiyeh Vaezipour2, Andry Rakotonirainy3, Sébastien Demmel3, Oscar Oviedo-Trespalacios3.   

Abstract

Eco-safe driving is a promising approach to improve road safety while reducing transport emissions. The application of an eco-safe driving system is feasible with the support of vehicle-to-vehicle/infrastructure technologies. To guarantee system usability and safety appropriateness, a key precondition is to ensure that driver mental workload and visual demands required for using the system are reasonable. This study explored how drivers' mental workload and visual demands were affected when driving with an eco-safe driving HMI (human-machine-interface). Four in-vehicle eco-safe HMI information conditions were evaluated, including baseline, advice only, feedback only, and advice & feedback. Two traffic scenarios (stop-sign intersection with traffic vs. stop-sign intersection without traffic) were simulated using an advanced driving simulator. Behavioural variables (e.g. brake force, acceleration), visual variables (e.g. blink metrics, pupil size) and subjective workload scores were collected from 36 licensed Australian drivers. The experiment results showed that the HMI prompted drivers to apply a smooth and stable brake force when they approached the intersection and a smooth acceleration when they left the intersection. Drivers' mental workload indicated by visual measurements were consistent with their subjective reported workload levels. Drivers had a higher mental workload when they received and processed additional eco-safe information in the advice & feedback condition. An increase in mental workload induced by the in-vehicle cognitive task initiated more blink activities while the increase in visual demand caused by a complex road situation led to blink inhibition. The study shows the HMI could significantly promote eco-safe driving behaivours without causing excessive mental and visual workload of drivers.
Copyright © 2020 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Driver assistance system; Driving simulator; Eco-Safe driving; Mental workload; Visual demand

Mesh:

Year:  2020        PMID: 32919220     DOI: 10.1016/j.aap.2020.105756

Source DB:  PubMed          Journal:  Accid Anal Prev        ISSN: 0001-4575


  2 in total

1.  An Evaluation of the EEG Alpha-to-Theta and Theta-to-Alpha Band Ratios as Indexes of Mental Workload.

Authors:  Bujar Raufi; Luca Longo
Journal:  Front Neuroinform       Date:  2022-05-16       Impact factor: 3.739

2.  Evaluation of Multimodal and Multi-Staged Alerting Strategies for Forward Collision Warning Systems.

Authors:  Jun Ma; Jiateng Li; Hongwei Huang
Journal:  Sensors (Basel)       Date:  2022-02-04       Impact factor: 3.576

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.