Understanding collective behaviour in

disaster & emergency response

Joanne Hinds

Ana Calderon

Rachid Hourizi

Peter Johnson

What are Human-Autonomous

Systems?

• Collections of human and autonomous agents

• Defense, disasters and emergency response, search and

rescue, transport

Human-Autonomous Systems

Collective Capability

Current challenges

Providing the right information to the right agent at the right time

Overcoming inflexible, rule bound behaviour

Quality and trustworthiness of decision-making

Overall Aims:

To enable multiple agencies (autonomous and human) to work together to increase the collective capability of the whole human-autonomous system

To enable HAS to achieve their objective in a safe, agile and efficient manner

Studies

Study 1:

How do humans respond to dynamic events in a

disaster?

Study 2:

How does a group attempt to solve a wicked problem?

Large-scale emergencies and

crises

Typically have:

Decentralised response and rescue effort

Volatile, unpredicatable, conflicting information

Efforts are increasingly incorporating human and autonomous agents

The role of autonomous

systems in emergencies Autonomous systems can help a variety of people

in a variety of circumstances

From official responders to locals on the ground

Study – Human Autonomous

Systems in crisis Qualitative study

Hurricane scenario

21 students/staff Bath University

Emergency responder immersed in a HAS

Commands and reports issued by:

Issued by humans (trained responders or locals on the ground) or

autonomous agents

Co-located or remote

Urgent or non-urgent

Addressing HAS Challenges Questions

To what extent do agents follow commands and how flexible are they with execution?

What information do agents seek/report and why?

HAS Challenges

Providing right information to the right agent at the right time

Quality and trustworthiness

Overcoming flexible, rule bound behaviour

Properties of information

Conflicting

Uncertain

Rapidly changing

Rule bound

Scenario

No.3 CoupleUrgent

No.2 1 elderly

ladyUrgent

No. 1Family of

4Non-

urgent

No. 5Family of

3Urgent

No. 4 Student house of

6Non-

urgent

No. 6 Flats

30 residents disabledUrgent

No. 8 Shop

Family of 8

Non-urgent

No. 10Couple

Non-urgent

No. 7 –Offices

30 peopleUrgent

No.91

residentNon-

urgent

Drop-off point

Commands Injured and disabled people are prioritised for evacuation

Only evacuate people classified as “urgent”

Evacuate buildings with the highest numbers of people first

Always fill the boat to full capacity before returning to the drop-off point

Provide regular reports (updates) to your collaborators so they can coordinate their actions and respond most effectively.

Findings Thematic analysis

Commands

Integration

Compliance with original commands

Reports

Reprioritisation

Compliance with original commands

Clarification

Findings - Command

Compliance with original commands – “Return to

the drop-off point” (Non-urgent)

“If it’s from my supervisor…. I could maybe look for 10

minutes so I still may not go immediately, I might see what

the situation was. If I could get them in the boat quickly I

would, so I would go against direct orders a little bit but I

would make my way back to the drop off point quickly.”

“Ignore it, because it is non- urgent.”

Findings - Report

Clarification – “Entrance to no. 8 is blocked” (Non-urgent)

“I would send for the UAV to check and see what it is because it doesn’t look like high priority so if it checks, I can keep going with what I’m doing. I’ll wait for the report and then I can reprioritise if necessary.”

Reprioritisation – “There is a distressed cry for help from house no.2” (Urgent)

“I could pick her up on one of my trips, if I just get three and then get one….Yeah, I’ll take 3 instead and then pick her up on the way.”

Conclusions Responders utilised autonomous systems to aid their

workload through delegation and clarification

Behaviour was rule bound, yet there was some

flexibility

Dynamic events influenced trustworthiness

Work in Progress: Study 2

Wicked problem solving – “in the wild”

Members of the collective:

Searching for information

Sharing information

Cryptic tasks and clues

HAS Challenges

Timing of information

Quality/trustworthiness

Flexibility

Summary Autonomous systems are improving collective

capability

Emergency response and wicked problems

Addressing HAS challenges (timing of information,

flexibility, quality) by exploring decision making,

information exchange and rationales

Aiming to make HAS more efficient, safe and agile

Thank you