Difference between revisions of "Defining an Alternative Pathfinding Method by Approaching Social Distancing through Micro and Macro Level in the City"

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[[DC I/O 2021]] Poster by [[SAHAR GOHARI MOGHADAM]], [[AVA FATAH GEN. SCHIECK]] and [[PETROS KOUTSOLAMPROS]].
 
[[DC I/O 2021]] Poster by [[SAHAR GOHARI MOGHADAM]], [[AVA FATAH GEN. SCHIECK]] and [[PETROS KOUTSOLAMPROS]].
  
[[File:PENDING|center|800px]]
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[[File:DCIO2021 S-Gohari-Moghadam.jpg|center|800px]]
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=Abstract=
 
=Abstract=
The outbreak of the Coronavirus in 2020 im-pacted social behaviors and urban daily ac-tivities greatly. Activities involving city path-finding and navigation have been impacted particularly because the new virus is air trans-missible, meaning that crowding should be avoided. There have been numerous social dis-tancing measures defined for daily activities in cities. However, there have not been sufficient virus safety measures for pathfinding. There is thus a need for a pathfinding method that can produce paths that could be perceived as safe from the virus by navigators.
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The outbreak of the Coronavirus in 2020 impacted social behaviors and urban daily activities greatly. Activities involving city path-finding and navigation have been impacted particularly because the new virus is air transmissible, meaning that crowding should be avoided. There have been numerous social distancing measures defined for daily activities in cities. However, there have not been sufficient virus safety measures for pathfinding. There is thus a need for a pathfinding method that can produce paths that could be perceived as safe from the virus by navigators.
  
Related studies include the mobile app “Safe Paths”, a 2020 research by MIT Media Lab which uses Bluetooth to track the number of people in locations and find paths that can be the safest from the virus. This is a time-based approach as it deals with the live tracking of pedestrians. A second study by Space Syntax Limited, em-ployed a probability-based approach, based on street network analysis, aiming to propose cy-cling and walking plans.
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Related studies include the mobile app “Safe Paths”, a 2020 research by MIT Media Lab which uses Bluetooth to track the number of people in locations and find paths that can be the safest from the virus. This is a time-based approach as it deals with the live tracking of pedestrians. A second study by Space Syntax Limited, employed a probability-based approach, based on street network analysis, aiming to propose cycling and walking plans.
  
Rather than only using a macroscale method for pathfinding, this research aims to use both a macroscale and microscale method, as both spatial configuration and human experience matter for navigation in paths. Additionally, based on the related work, as a time-based ap-proach is not cost-efficient, a probability-based approach is chosen as the methodology.
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Rather than only using a macroscale method for pathfinding, this research aims to use both a macroscale and microscale method, as both spatial configuration and human experience matter for navigation in paths. Additionally, based on the related work, as a time-based approach is not cost-efficient, a probability-based approach is chosen as the methodology.
  
 
=Presentation=
 
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=Conference Poster=
 
=Conference Poster=
[[File:PDF-Icon.png |Left|50px|link=https://www.dropbox.com/PENDING]] [https://www.dropbox.com/s/PENDING Conference Paper].
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[[File:PDF-Icon.png |Left|50px|link=https://www.dropbox.com/s/tr3g77sa9he8e82/DCIO2021_S2-6_S.G.Morghadam.pdf?dl=0]] [https://www.dropbox.com/s/tr3g77sa9he8e82/DCIO2021_S2-6_S.G.Morghadam.pdf?dl=0 Conference Poster].
  
 
=Keywords=
 
=Keywords=

Latest revision as of 22:07, 7 June 2022

DCIO2021-Logo.png
DC I/O 2021 Poster by SAHAR GOHARI MOGHADAM, AVA FATAH GEN. SCHIECK and PETROS KOUTSOLAMPROS.


DCIO2021 S-Gohari-Moghadam.jpg


Abstract

The outbreak of the Coronavirus in 2020 impacted social behaviors and urban daily activities greatly. Activities involving city path-finding and navigation have been impacted particularly because the new virus is air transmissible, meaning that crowding should be avoided. There have been numerous social distancing measures defined for daily activities in cities. However, there have not been sufficient virus safety measures for pathfinding. There is thus a need for a pathfinding method that can produce paths that could be perceived as safe from the virus by navigators.

Related studies include the mobile app “Safe Paths”, a 2020 research by MIT Media Lab which uses Bluetooth to track the number of people in locations and find paths that can be the safest from the virus. This is a time-based approach as it deals with the live tracking of pedestrians. A second study by Space Syntax Limited, employed a probability-based approach, based on street network analysis, aiming to propose cycling and walking plans.

Rather than only using a macroscale method for pathfinding, this research aims to use both a macroscale and microscale method, as both spatial configuration and human experience matter for navigation in paths. Additionally, based on the related work, as a time-based approach is not cost-efficient, a probability-based approach is chosen as the methodology.

Presentation

Left Video Recording.

Conference Poster

Left Conference Poster.

Keywords

PENDING

Reference

DOI: https://doi.org/10.47330/DCIO.2021.HSPW7821

Bibliography

  • AL-SAYED, K., TURNER, A., & HILLIER, B. (2013). Space Syntax Methodology, The Bartlett School of Graduate Studies, University College London, UK.
  • BATTY, M. (2020). The Coronavirus crisis: What will the post-pandemic city look like? : Urban Analytics and City Science, Vol. 47(4) 547–552
  • DUCKHAM, M. & KULIK, L. (2003). “Simplest” Paths: Automated Route Selection for Navigation. Spatial Information Theory. Foundations of Geographic Information Science, pp.169-185.
  • GRAJEWSKI, T. (1992), VAUGHAN, L. (2001), Space Syntax Observation Manual, UCL.
  • HILLIER, B. (2007), Space is the Machine: A Configurational Theory of Architecture. Space Syntax: London, UK. pp.99
  • LANNING, D., HARRELL, G., WANG, J., (2014), Dijkstra’s algorithm and Google