Learning To Drive Autonomously

Details

• Creators:
  Jiang, Zhong-Ping ; Ozbay, Kaan ; Cui, Leilei
• Corporate Creators:
  Connected Cities for Smart Mobility toward Accessible and Resilient Transportation Center (C2SMART) ; New York University
• Corporate Contributors:
  United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology
• Subject/TRT Terms:
  • Autonomous vehicles
  • Connected vehicles
  • Differential equations
  • Drivers
  • Traffic simulation
  • Vehicle mix
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Corporate Publisher:
  Connected Cities for Smart Mobility toward Accessible and Resilient Transportation Center (C2SMART)
• Abstract:
  In this report, the authors model the system of a platoon mixed with multiple connected human-driven vehicles (HDVs) and a connected and autonomous vehicle (CAV) as a set of differential difference equations (DDEs), by taking into account drivers’ heterogeneous feedback gains and reaction delays as well as the actuator (engine) delay. Then, the authors follow an approximate discretization procedure to rewrite DDEs into a sampled-data linear system with approximation error. This discretization step transforms the problem of controlling DDEs to the control of an augmented linear system without delay and simplifies the control design procedure.
• Format:
  PDF
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/59903/dot_59903_DS1.pdf
• File Type:
  [PDF - 3.49 MB]
• Collection(s):
  Autonomous Vehicles ; University Transportation Centers ; US Transportation Collection
• Main Document Checksum:
  urn:sha-512:640763245ca631c79fbd3e2e0424bfea922c96d85bfc41273d74c8270e988018a7cf55fc2f7e77d7d0d9ce7fc42734c960866e6198d0bccb844b8f4495a006ec