Real-world observations and human factors evaluation of AV shuttle operations
To date, there have been dozens of autonomous shuttle projects across the country aiming to test fully driverless transit operations (Federal Transit Administration 2023). Typically, these pilots involve small shuttles, or “pods,” which carry between 12-15 people and operate at relatively slow speeds (~25 mph). While many of these shuttles operate without incident, there have also been accidents and injuries that have occurred during pilots. For example, in 2017, an automated passenger shuttle in Las Vegas was hit by a truck backing up (Gibbs 2017). Although an attendant was on board, they could not steer the shuttle out of the way because the controls were locked in a compartment (National Transportation Safety Board 2019). More recently, an autonomous shuttle in Orlando collided with a full-length bus at low speed while the shuttle was pulling forward from a stop near the curb and the bus was making a lane change toward the curb (Hope 2023). The onboard attendant attempted to stop the shuttle; however, reports suggest there was insufficient time or space to avoid the collision. Although it seems counter-intuitive, increased automation can actually make the task of operating a vehicle more challenging. Prior research on human-machine teaming in aviation (Casner and Hutchins 2019) outlines how novel challenges emerge when operators need to take over quickly during emergency situations (Casner and Hutchins 2019) such as skill atrophy (Ebbatson et al. 2010, Pettigrew, Fritschi, and Norman 2018) and mode confusion (Sarter and Woods 1995). As automation takes over more routine aspects of driving, operators are left to manage the most challenging situations. Research on this phenomenon shows that reaction time increases as time disengaged from the task of driving increases, regardless of cognitive engagement (Funkhouser and Drews 2016). Within aviation, automation has reduced many common crash scenarios; however, it has also created new, more complex situations leading to new kinds of crashes (Casner and Hutchins 2019). For example, the tragic Boeing 737 MAX MCAS crashes resulted from a single malfunctioning AOA sensor which provided incorrect data, leading to pilots experiencing sudden and unexpected loss of control authority. In this research project, the research team will partner with Beep (https://ridebeep.com/) an autonomous shuttle bus service provider to conduct field observations and interviews with on-board AV shuttle operators and remote operators. The focus in these observations and interviews will be to understand the current work processes and human factors of the work these operators do. The team will conduct cognitive and physical task evaluations of operators’ work processes and usability evaluations of the physical and digital interfaces that they use. Based on these observations and evaluations, the team will co-develop recommendations for improved work processes, new training, and potential interface improvements. Overall, the team aims to improve the human-machine interaction of on-board and remote shuttle operations, ultimately enhancing the safety of AV shuttle operations.
- Record URL:
Language
- English
Project
- Status: Active
- Funding: $200000
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Contract Numbers:
69A3552344811
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Sponsor Organizations:
Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 -
Managing Organizations:
Carnegie Mellon University
Pittsburgh, PA United StatesSafety21 University Transportation Center
Carnegie Mellon University
Pittsburgh, PA United States 15213 -
Project Managers:
Stearns, Amy
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Performing Organizations:
Carnegie Mellon University
Transportation Research Institute
Pittsburgh, PA United States 15213 -
Principal Investigators:
Fox, Sarah
- Start Date: 20240701
- Expected Completion Date: 20250630
- Actual Completion Date: 0
- USDOT Program: University Transportation Centers
Subject/Index Terms
- TRT Terms: Autonomous vehicle handover; Autonomous vehicles; Human factors engineering; Human machine systems; Interfaces; Shuttle buses
- Subject Areas: Data and Information Technology; Public Transportation; Safety and Human Factors; Vehicles and Equipment;
Filing Info
- Accession Number: 01933406
- Record Type: Research project
- Source Agency: Safety21 University Transportation Center
- Contract Numbers: 69A3552344811
- Files: UTC, RIP
- Created Date: Oct 13 2024 9:50AM