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Abstract

The study conducted a simulated driving experiment to explore the impact of visibility and warning types in connected environment on driving performance, eye movement, and brain activity. Twenty-four drivers participated the experiment. A rural two-way two lanes highway was designed as the roadway environment. Data were aggregated from different scenarios (4 (visibility: clear, low fog, medium fog, night) × 3 (warning types: no warning, visual warning, and visual with audio warning). All Participants must perform both car-following and lane-changing driving tasks in each drive. The experimental results show that the usage of different warning types under different visibility conditions in the connected environment has a significant impact on the driving performance and traffic safety. The findings have important implications for the application of the connected environment and the choice of different warning types.

Details

Title
Evaluating the Efficiency of Different Warning Types in the Connected Environment Under Different Visibility Conditions
Author
Liu, Yi
Publication year
2022
Publisher
ProQuest Dissertations & Theses
ISBN
9798363503009
Source type
Dissertation or Thesis
Language of publication
English
ProQuest document ID
2755798262
Copyright
Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works.