ACT Driving Simulator

2020 ~ Present


The ACT (Autonomous and Connected Transportation) Driving Simulator Team addresses problems that arise in multiple dimensions due to the emergence of autonomy, connectivity, and novel tech-leveraged modes in transportation. A major focus is to understand the interactions among drivers/travelers, emerging vehicular technologies related to connectivity and autonomy, and novel infrastructure designs by leveraging a driving simulator environment, analytical modeling, and living labs. Using the collected data, the team seeks to develop analytical models and perform data analytics to predict the autonomous and connected transportation future. Another focus is to leverage these emerging technologies and modes to develop sustainable travel solutions and deployment tools for smart and connected communities (SCCs) using the City of Peachtree Corners, GA, as an immersive living lab.

Issues Involved or Addressed

To understand the interactions between humans, vehicles, and the infrastructure under ACT, and develop sustainable travel solutions for communities, the team works on projects in multiple topical areas:

  • Model autonomous vehicles (AVs) and conduct field tests
  • Understand emergent issues (cybersecurity, control, human factors, etc.) under different levels of automation and V2X connectivity
  • Design Human-Machine Interfaces (HMIs) with auditory, visual, haptic and gestural cues for safe traffic operations under different levels of autonomy and connectivity
  • Predict driver/traveler behaviors under ACT by collecting and analyzing physiological data (i.e., EEG, ECG, and eye-tracking data)
  • Use virtual reality and augmented reality technologies to enhance driver/traveler experiences
  • Investigate the impacts of novel roadway designs that leverage ACT technologies
  • Build mobile apps and multiobjective optimization models to develop sustainable transportation solutions through behavioral interventions and ACT partnerships

Methods and Technologies

  • Machine learning
  • Control theory
  • Optimization
  • Large language models
  • High-fidelity driving simulators
  • Physiological sensors (e.g., EEG, ECG, and eye tracking system)
  • Video image processing
  • Microscopic traffic simulation
  • Virtual reality/augmented reality
  • Experiment design
  • Behavioral and experimental psychology
  • Mobile app development
  • Data analytics

Academic Majors of Interest

  • ComputingComputer Science
  • ComputingHuman-Computer Interaction
  • EngineeringAerospace Engineering
  • EngineeringCivil Engineering
  • EngineeringElectrical Engineering
  • EngineeringEnvironmental Engineering
  • EngineeringIndustrial Engineering
  • EngineeringMechanical Engineering
  • EngineeringRobotics
  • Ivan AllenPublic Policy
  • Other
  • SciencesPsychology

Preferred Interests and Preparation

Anyone with an interest in the broad and multidisciplinary ACT space is welcome to apply to join the team.

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

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

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

Meeting Schedule & Location

5:00-5:50 PM
Meeting Location 
Meeting Day 

Team Advisors

Dr. Srinivas Peeta
  • Civil and Environmental Engineering