Abstract

Safe and socially acceptable interactions with human-driven vehicles are a major challenge in automated driving. A good understanding of the underlying principles of such traffic interactions could help address this challenge. Particularly, accurate driver models could be used to inform automated vehicles in interactions. These interactions entail complex dynamic joint behaviors composed of individual driver contributions in terms of high-level decisions, safety margins, and low-level control inputs. Existing driver models typically focus on one of these aspects, limiting our understanding of the underlying principles of traffic interactions. Here, we present a Communication-Enabled Interaction model based on risk perception, that does not assume humans are rational and explicitly accounts for communication between drivers. Our model can explain and reproduce observed human interactions in a simplified merging scenario on all three levels. Thereby improving our understanding of the underlying mechanisms of human traffic interactions and posing a step towards interaction-aware automated driving.

Details

Title
A model of dyadic merging interactions explains human drivers’ behavior from control inputs to decisions
Author
Siebinga, Olger 1   VIAFID ORCID Logo  ; Zgonnikov, Arkady 1   VIAFID ORCID Logo  ; Abbink, David A 1 

 Mechanical Engineering - Cognitive Robotics, TU Delft , Delft, CD 2628 , The Netherlands 
Publication year
2024
Publication date
Oct 2024
Publisher
Oxford University Press
e-ISSN
27526542
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3191892654
Copyright
© The Author(s) 2024. Published by Oxford University Press on behalf of National Academy of Sciences. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.