Space Invaders: Pedestrian Proxemic Utility Functions and Trust Zones for Autonomous Vehicle Interactions

TY - JOUR

T1 - Space Invaders

T2 - Pedestrian Proxemic Utility Functions and Trust Zones for Autonomous Vehicle Interactions

AU - Camara, Fanta

AU - Fox, Charles

N1 - Funding Information: This project has received funding from EU H2020 project interACT: Designing cooperative interaction of automated vehicles with other road users in mixed traffic environments under Grant Agreement No 723395. The authors are grateful to the Associate Editor and the anonymous reviewers for their valuable time and very useful feedback. Publisher Copyright: © 2020, The Author(s).

PY - 2021/12/5

Y1 - 2021/12/5

N2 - Understanding pedestrian proxemic utility and trust will help autonomous vehicles to plan and control interactions with pedestrians more safely and efficiently. When pedestrians cross the road in front of human-driven vehicles, the two agents use knowledge of each other’s preferences to negotiate and to determine who will yield to the other. Autonomous vehicles will require similar understandings, but previous work has shown a need for them to be provided in the form of continuous proxemic utility functions, which are not available from previous proxemics studies based on Hall’s discrete zones. To fill this gap, a new Bayesian method to infer continuous pedestrian proxemic utility functions is proposed, and related to a new definition of ‘physical trust requirement’ (PTR) for road-crossing scenarios. The method is validated on simulation data then its parameters are inferred empirically from two public datasets. Results show that pedestrian proxemic utility is best described by a hyperbolic function, and that trust by the pedestrian is required in a discrete ‘trust zone’ which emerges naturally from simple physics. The PTR concept is then shown to be capable of generating and explaining the empirically observed zone sizes of Hall’s discrete theory of proxemics.

AB - Understanding pedestrian proxemic utility and trust will help autonomous vehicles to plan and control interactions with pedestrians more safely and efficiently. When pedestrians cross the road in front of human-driven vehicles, the two agents use knowledge of each other’s preferences to negotiate and to determine who will yield to the other. Autonomous vehicles will require similar understandings, but previous work has shown a need for them to be provided in the form of continuous proxemic utility functions, which are not available from previous proxemics studies based on Hall’s discrete zones. To fill this gap, a new Bayesian method to infer continuous pedestrian proxemic utility functions is proposed, and related to a new definition of ‘physical trust requirement’ (PTR) for road-crossing scenarios. The method is validated on simulation data then its parameters are inferred empirically from two public datasets. Results show that pedestrian proxemic utility is best described by a hyperbolic function, and that trust by the pedestrian is required in a discrete ‘trust zone’ which emerges naturally from simple physics. The PTR concept is then shown to be capable of generating and explaining the empirically observed zone sizes of Hall’s discrete theory of proxemics.

KW - Autonomous vehicles

KW - Mathematical models of human behaviour

KW - Pedestrians

KW - Proxemics

KW - Trust

UR - http://www.scopus.com/inward/record.url?scp=85097173460&partnerID=8YFLogxK

U2 - 10.1007/s12369-020-00717-x

DO - 10.1007/s12369-020-00717-x

M3 - Article

AN - SCOPUS:85097173460

SN - 1875-4791

VL - 13

SP - 1929

EP - 1949

JO - International Journal of Social Robotics

JF - International Journal of Social Robotics

IS - 8

ER -