TY - JOUR

T1 - Behaviour control with augmented reality systems for shared spaces

AU - Kamalasanan, V.

AU - Sester, M.

N1 - Funding information: The authors cordially thank the funding provided by DAAD and participants of DFG Training Group 1931, SocialCars on the directions used in the work.

PY - 2020/8/25

Y1 - 2020/8/25

N2 - Augmented Reality (AR) in a traffic context has mainly been used in navigation with path augmentation, focused around safely guiding the user with prior knowledge of the route and the destination. Other works are reported to warn drivers by visualizing other traffic participants or dangers, which are yet currently out of sight. However they do not cover aspects of mediating control by recommending users with actions, even when such efforts are expected to foster collaboration in a multiagent environment. To the best of our knowledge, AR has not yet been applied to visualize virtual control information, e.g. virtual lanes or signposts, notably in the context of shared spaces. Such an environment should support spatial understanding of proximate participants with adaptive augmented controls to recommend actions to each user. However when such systems work in context where a conflict of interest would arise, a rule based control logic centered on priority should be accounted for. Traditionally, these rules are defined by traffic management. This paper presents a Behaviour Control with AR (BCAR) Systems based framework for control of user behaviour in a shared space via augmentation and proposes how a control logic can be part of it. The framework which incorporates navigation focuses on mapping users from real to the virtual world.This framework also enables simulations and visualization of multiagent interactions and proposing controls for user actions leveraging the environment complexity reduction achieved through the real to virtual transfer. A prototype implementation of the proposed framework with ARCore and unity3D has been evaluated for pedestrian behaviour control to understand its feasibility.

AB - Augmented Reality (AR) in a traffic context has mainly been used in navigation with path augmentation, focused around safely guiding the user with prior knowledge of the route and the destination. Other works are reported to warn drivers by visualizing other traffic participants or dangers, which are yet currently out of sight. However they do not cover aspects of mediating control by recommending users with actions, even when such efforts are expected to foster collaboration in a multiagent environment. To the best of our knowledge, AR has not yet been applied to visualize virtual control information, e.g. virtual lanes or signposts, notably in the context of shared spaces. Such an environment should support spatial understanding of proximate participants with adaptive augmented controls to recommend actions to each user. However when such systems work in context where a conflict of interest would arise, a rule based control logic centered on priority should be accounted for. Traditionally, these rules are defined by traffic management. This paper presents a Behaviour Control with AR (BCAR) Systems based framework for control of user behaviour in a shared space via augmentation and proposes how a control logic can be part of it. The framework which incorporates navigation focuses on mapping users from real to the virtual world.This framework also enables simulations and visualization of multiagent interactions and proposing controls for user actions leveraging the environment complexity reduction achieved through the real to virtual transfer. A prototype implementation of the proposed framework with ARCore and unity3D has been evaluated for pedestrian behaviour control to understand its feasibility.

KW - Augmented reality

KW - Behavioural control

KW - Proximity

KW - Shared spaces

KW - Situational awareness

KW - Spatially Aware Interface

KW - Virtual traffic system

UR - http://www.scopus.com/inward/record.url?scp=85091598351&partnerID=8YFLogxK

U2 - 10.5194/isprs-archives-XLIII-B4-2020-591-2020

DO - 10.5194/isprs-archives-XLIII-B4-2020-591-2020

M3 - Conference article

AN - SCOPUS:85091598351

VL - 43

SP - 591

EP - 598

JO - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

JF - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

SN - 1682-1750

IS - B4

T2 - 2020 24th ISPRS Congress - Technical Commission IV on Spatial Information Science

Y2 - 31 August 2020 through 2 September 2020

ER -