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ACT Driving Simulator

2020 ~ Present


The main goal of the ACT (Autonomous and Connected Transportation) Lab is to understand interactions between drivers/travelers, emerging vehicular technologies related to connectivity and autonomy, and novel infrastructure designs using a driving simulator environment, analytical modeling, and field test tracks. Using the collected data, we seek to develop analytical models and perform data analytics to predict the autonomous and connected transportation future.

Issues Involved or Addressed

To understand the interactions between humans, autonomous vehicles, and infrastructure. We work or plan to work on the following projects:

·        Build fully autonomous vehicles (AVs) and conduct field tests;

·        Evaluate the effects of different levels of automation and connectivity (i.e., vehicle to vehicle, vehicle to infrastructure, and vehicle to pedestrian communications);

·        Design Human-Machine Interface (HMI) with auditory, visual, haptic and gestural cues for safe traffic operations at different levels of autonomy;

·        Understand driver/traveler behaviors by collecting and analyzing physiological data (i.e., EEG, ECG, and eye-tracking data);

·        Apply virtual reality (VR) and augmented reality (AR) technologies for enhancing driver/traveler experiences;

·        Investigate the impacts of novel roadway designs (i.e., dedicated autonomous vehicle lane and AV pickup/drop-off location) on AV operations;

Model autonomous and connected vehicle behaviors (i.e., lane changing and car-following behaviors) in mixed traffic flow conditions.

Methods and Technologies

  • High-fidelity driving simulators
  • Physiological sensors (i.e., EEG, ECG, and eye tracking device)
  • Video image processing
  • Microscopic traffic simulation
  • Virtual reality/augmented reality
  • Experiment design
  • Behavior psychology
  • Control theory
  • Optimization
  • Machine learning

Academic Majors of Interest

  • Aerospace Engineering - OLD
  • Civil Engineering
  • Computer Science
  • Electrical Engineering
  • Human-Computer Interaction
  • Industrial Engineering
  • Mechanical Engineering
  • OMSCS synchronous, case-by-case
  • Psychology
  • Public Policy
  • Robotics

Preferred Interests and Preparation

CEE, ISyE: Background/interest in connected and autonomous vehicle, smart and sustainable city, transportation engineering, human factors, analytical modeling, optimization, data analytics, machine learning, etc.

ECE, CS, ME: Background/interest in human-machine interactions, machine learning, image processing, augmented reality, virtual reality, robotics, embedded systems, etc.

PSYCH: Background/interest in human factors, cognitive/applied psychology, and human in the loop experiments.

Meeting Schedule & Location

Meeting Day 

Team Advisors

Srinivas Peeta