## BCIT Traffic Complexity

### Introduction

**Overview:** The Traffic Complexity study was designed to collect extended time-on-task measurements of
subjects performing a driving task in a simulated environment in order to assess fatigue-based performance
through novel biomarkers. Similar to the Baseline Driving study, the Speed Control study was intended to
identify periods of driver fatigue via predictive algorithms formulated from the analysis of driver EEG data,
in comparison to the objective performance measures, and in contrast with the (non-fatigued)
Calibration driving session for the subject. Traffic Complexity extended the paradigm by modulating
the visual complexity and the frequency of perturbation events vs. Baseline Driving.

Further information is available on request from [cancta.net](https://cancta.net).

### Methods   

**Subjects:** Volunteers from the local community recruited through advertisements.  
 
**Apparatus:**  Driving simulator with steering wheel and brake / foot pedals (Real Time Technologies; Dearborn, MI);
Video Refresh Rate (VRR) = 900 Hz; Vehicle data log file Sampling Rate (SR) = 100 Hz);
EEG (BioSemi 64 (+8) channel systems with 4 eye and 2 mastoid channels recorded; SR=2048 Hz);
Eye Tracking (Sensomotoric Instruments (SMI); REDEYE250).

**Initial setup:** Upon arrival to the lab, subjects were given an introduction to the primary study
for which they were recruited and provided informed consent and provided demographics information.
This was followed by a practice session, to acclimate the subject to the driving simulator.
The driving practice task lasted 10-15 min, until asymptotic performance in steering and speed control
was demonstrated and lack of motion sickness was reported.
Subjects were then outfitted and prepped for eye tracking and EEG acquisition.

**Task organization:** Subjects would perform the Baseline Driving task and the Traffic Complexity task,
with counter-balancing used across subjects as to which of them came first.
The Baseline Driving run was 45 minutes of continuous driving, with subjects responsible
for speed and steering control. Both driving tasks were conducted on the same simulated long,
straight road. The Baseline run was done in a visually sparse environment, and the Traffic Complexity
runs included pedestrians and other traffic. In each case, the subject was instructed to stay
within the boundaries of the right-most lane, and to drive at the posted speed limits.

The vehicle was periodically subject to lateral perturbing forces, which could be applied to either
side of the vehicle, pushing the vehicle out of the center of the lane; and the subject was instructed
to execute corrective steering actions to return the vehicle to the center of the lane.

**Independent variables:** Visual Complexity (high vs. low), Perturbation Frequency (high vs. low).

**Dependent variables:** Reaction times to perturbations, continuous performance based on vehicle
log (steering wheel angle, lane position, heading error, etc.), Task-Induced Fatigue Scale (TIFS),
Karolinska Sleepiness Scale (KSS), Visual Analog Scale of Fatigue (VAS-F).

**Note:** Questionnaire data is available upon request from [cancta.net](https://cancta.net).

**Additional data acquired:** Participant Enrollment Questionnaire, Subject Questionnaire for Current Session,
Simulator Sickness Questionnaire.

**Experimental Locations:**  Teledyne Corporation, Durham, NC.

**Note 1:** This dataset has a corresponding dataset in the BCIT Calibration Driving ds004118 which has the
15 minute driving task performed prior to this one.

**Note 2:** This dataset has a corresponding dataset in the BCIT Baseline Driving ds004120 which was a 
longer driving task in a sparse environment.