CHI2 Presenration

1. Understanding collective behaviour in
disaster & emergency response
Joanne Hinds
Ana Calderon
Rachid Hourizi
Peter Johnson

2. What are Human-Autonomous
Systems?
• Collections of human and autonomous agents
• Defense, disasters and emergency response, search and
rescue, transport

3. 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

4. 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?

5. Large-scale emergencies and
crises
 Typically have:
 Decentralised response and rescue effort
 Volatile, unpredicatable, conflicting information
 Efforts are increasingly incorporating human and autonomous agents

6. 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

7. 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

8. 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

9. Scenario
No.3
Couple
Urgent
No.2
1 elderly
lady
Urgent
No. 1
Family of
4
Non-
urgent
No. 5
Family of
3
Urgent
No. 4
Student
house of
6
Non-
urgent
No. 6
Flats
30
residents
disabled
Urgent
No. 8
Shop
Family of
8
Non-
urgent
No. 10
Couple
Non-
urgent
No. 7 –
Offices
30 people
Urgent
No.9
1
resident
Non-
urgent
Drop-off
point

10. 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.

11. Findings
 Thematic analysis
 Commands
 Integration
 Compliance with original commands
 Reports
 Reprioritisation
 Compliance with original commands
 Clarification

12. 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.”

13. 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.”

14. 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

15. 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

16. 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

17. Thank you