Real-World Observations and Human Factors Evaluation of AV Shuttle Operations

Details

• Creators:
  Fox, Sarah ; Martelaro, Nikolas
• Corporate Creators:
  Carnegie Mellon University
• Corporate Contributors:
  Carnegie Mellon University. Traffic21 Institute. Safety21 University Transportation Center (UTC) ; United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology ; United States. Department of Transportation. Federal Highway Administration
• Subject/TRT Terms:
  Autonomous Vehicle Handover Autonomous Vehicles Human Factors Engineering Human Machine Systems Interfaces Shuttle Buses
• Publication/ Report Number:
  563
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Edition:
  Final Report (July 1, 2024 – June 30, 2025)
• Corporate Publisher:
  Carnegie Mellon University. Traffic21 Institute. Safety21 University Transportation Center (UTC)
• Abstract:
  The integration of autonomous vehicle (AV) shuttles and advanced driver assistance systems (ADAS) into public transit is positioned as a means of enhancing safety, accessibility, and operational efficiency. However, these technologies also transform the role of human operators, who must intervene during complex and high-risk scenarios. This study examined human factors in AV shuttle operations and ADAS testing through ethnographic observations, interviews, and human factors evaluations in both live service and controlled testing environments across the U.S. and Canada. Findings reveal that ergonomic strain, sustained cognitive workload, unclear communication protocols, and insufficiently realistic testing conditions can diminish the intended safety benefits of automation. AV shuttle attendants faced physical discomfort from poorly designed seating and display placement, while remote monitoring staff contended with fragmented alert systems and inconsistent communication pathways. ADAS collision avoidance testing often failed to reflect real-world operating conditions, limiting the relevance of results. Recommendations include ergonomic workstation redesign, improved alerting and communication systems, operator-centered training, and scenario-based testing that mirrors operational complexity and diversity. Embedding operator perspectives in design, testing, and deployment processes can ensure that automation effectively supports safe and efficient transit operations.
• Format:
  PDF
• Funding:
  69A3552344811 / 69A3552348316
• Collection(s):
  University Transportation Centers Autonomous Vehicles
• Main Document Checksum:
  urn:sha-512:be198a22f1096c85ac44e51f214f968b7b357f4672bf14ceeba2f044b23199ac520d6ab47bd76a57dbc14120ba667daf4991ced5c7ebfa3a231c4b2b889f9baa
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/86169/dot_86169_DS1.pdf
• File Type:
  [PDF - 505.02 KB ]