November 14, 2019
In the future, vehicles equipped with automated driving systems (ADS) that drive us instead of us driving them will become a reality. These vehicles will integrate onto roadways and may change operational interactions with other vehicles in certain scenarios. Public safety officials, such as law enforcement, fire and rescue, and emergency medical personnel routinely interact with a broad spectrum of public and private vehicles to protect people, to investigate crimes or crashes, and to save lives. This research effort sought to determine the following:
- What are the common scenarios where public safety officials must engage in several different interactions and interaction types with a broad spectrum of public and private vehicles?
- What are the protocols used during those scenarios and the different interactions and interaction types?
- Do variables such as weather, roadway type, geometry, or vehicle type impact current protocols used in those scenarios?
- How may the current operations change due to the introduction of ADS-equipped vehicles in driverless operation (DO)?
- Are there opportunities where the interactions of public safety officials could be improved with the introduction of ADS-equipped vehicles in DO?
An extensive review of available literature and consultations with subject matter experts allowed the research team to determine the most common scenarios where public safety officials interact with other vehicles. Those scenarios included responding to an incident, securing an incident scene, conducting traffic direction and control, conducting a traffic stop, investigating an abandoned or unattended vehicle, and performing stabilization and patient extrication. Each of these operations were broken down task-by-task using a Hierarchical Task Analysis (HTA). The HTAs were converted into task diagrams to illustrate the procedures.
A combined effort between the Virginia Tech Transportation Institute (VTTI) and the University of Massachusetts Traffic Safety Research Program (UMassSafe), a division of the UMass Transportation Center (UMTC), conducted focus groups and one-on-one interviews with a total of 79 public safety officials. The participants were law enforcement, fire and rescue, and emergency medical services (EMS) personnel from 22 different U.S. states and 3 Canadian provinces.
In the interviews and focus groups, the research teams showed the participants three of the six different scenarios and posed questions regarding how accurate the research team’s depictions of the operations in the videos were. These responses allowed the research team to fill in any gaps in knowledge or highlight any potential differences in operations that may exist depending on department size, department type, or geographical region.
In the final portion of each interview, the research team showed a video that introduced participants to the idea of ADS-equipped vehicles in DO (referred to in the focus groups and interviews as vehicles equipped with automation in driverless mode). Subsequent questions focused on the scenarios the groups had previously discussed, and they were asked how the advent of those systems might change their current procedures. Responses were typically provided in the form of questions or hypotheticals. Much of the feedback provided allowed the research team to deduce the suggested needs of public safety officials as well as potential opportunities for the technology to benefit their current procedures. Each interview closed with questions regarding which scenario may be afforded the greatest opportunity for improvement when considering ADS-equipped vehicles in DO as well as the extent of their experience with vehicles that are currently sometimes referred to as “autonomous.”
The recorded interviews were transcribed and then placed in worksheets, so themes could be coded. Responses were placed in “bins” that correlated with a specific theme or idea. Each theme or idea was then associated with an interaction type: direct, indirect, or informational. Direct interactions involve a physical interaction between a public safety official and a vehicle either by touching it or using a tool to touch it. Indirect interactions are when a public safety official manipulates a vehicle, or driver, without coming into contact with a vehicle. Informational interactions are when public safety officials gather information from a vehicle or driver either by observing it, searching around it, or requesting it.
The most common responses included the following interaction types, themes, and associated number of responses, indicated in the parenthesis.
Direct Interaction: Represented the need to know “How to…”
- Disable the vehicle when securing an incident scene (38), investigate an abandoned vehicle (4), or perform stabilization or extrication (4)
Indirect Interactions: Represented the need to know “How to…”
- Know that the ADS-equipped vehicle has sensed or detected the presence of emergency vehicles during an incident response (16) or when conducting a traffic stop (19)
- Signal or communicate to the vehicle when conducting traffic direction and control (39) or securing an incident scene (5)
Informational Interactions: Represented additional “Need to know how…”
- The vehicle will react or behave in advance of responding to an incident (30), conducting traffic direction and control (17), or investigating an abandoned vehicle (4)
- To identify or determine a vehicle is an ADS-equipped vehicle in DO when responding to an incident (22), conducting traffic direction and control (14), conducting a traffic stop (11), securing an incident scene (7), or investigating an abandoned vehicle (6)
- To determine who is responsible for the vehicle when securing an incident scene (23) or conducting a traffic stop (20)
- To obtain various data from the vehicle prior to its involvement in an incident being secured (23) or the initiation of a traffic stop (2)
The participant feedback indicates several potential opportunities for improved interactions between public officials and future ADS-equipped vehicles in DO. Consistent actions by vehicles in all the scenarios was said to largely benefit the safety and efficiency of public safety officials. Additional technologies that were speculated to be associated with these vehicles, such as mass communication capabilities to warn other vehicles and detailed data of the vehicle’s behavior prior to an incident or traffic stop, were all mentioned as strong positives for resources, time, and safety. The responses garnered from the interviews conducted with public safety officials were stated inquisitively as needs but are opportunities for additional research efforts to investigate further.
The objectives of this research effort were to:
- Determine common public safety scenarios through a literature review and subject matter expert opinions
- Use an HTA to analyze and breakdown the tasks of each scenario step-by-step
- Verify that the safety scenarios are complete by requesting further subject matter expert opinion via focus groups and interviews
- Inquire how introduction of ADS-equipped vehicles in DO may change current procedures conducted in each scenario
- Determine opportunities where the interactions of public safety officials could be improved with the introduction of ADS-equipped vehicles in DO
The steps taken to accomplish these objectives will be the focus of this document:
- Chapter 2 describes the research methods associated with the project tasks, including the literature review, HTA, and DO needs assessment.
- Chapter 3 provides additional details on the DO needs assessment data analysis efforts.
- Chapter 4 presents the literature review and HTA.
- Chapter 5 discusses of the DO needs assessment findings for each operational scenario.
- Chapter 6 summarizes to key findings from the DO participant feedback assessment key findings.
- Chapter 7 draws attention to potential opportunities for improved operational procedures and interactions moving forward.
Read the full final report here.
For more information, contact:
Will be available for interviews.
Must contact Pamela Stiff to schedule.