Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Define Local Accessibility Sensitivities for Pedestrians #1760

Closed
10 tasks done
Tracked by #1804
Philipp-Otter opened this issue Nov 30, 2022 · 2 comments
Closed
10 tasks done
Tracked by #1804

Define Local Accessibility Sensitivities for Pedestrians #1760

Philipp-Otter opened this issue Nov 30, 2022 · 2 comments
Assignees

Comments

@Philipp-Otter
Copy link

Philipp-Otter commented Nov 30, 2022

Goal of this issue

Currently, GOAT uses a sensitivity of 300000 for almost all amenities, but since the willingness to walk to a destination is different for different amenities, the goal of this issue is to group the amenities and assign more precise sensitivity parameters.

  • 1) Process GOAT 3.0 survey results and fit data to the combined and the modified Gaussian function -> create plots and an overview table
  • (optional) Filter respondents
  1. Filter if respondents live in cities or not (maybe intersect with the RegioStaR)
    -> detailed analysis of respondents living in cities as 90% live in cities
    -> detailed analysis of respondents living in cities
  2. analyze age groups
  3. analyze gender
  • 2) Group our amenities into four categories:
  1. Immediate Surroundings (travel time <= 5 min) e.g. bakery, supermarket
  2. Close Surroundings (tt <= 10 min) e.g. post office
  3. District-Wide Surroundings (tt <= 20 min) e.g. secondary school
  4. Citywide Surroundings (tt > 20 min) e.g. theatre
  • 3) compare our results with the publication "Stadt Chemnitz Mobilitätsplan 2040 Standort-Werkzeug"
  • 4) define sensitivity parameters for the four categories
  • 5) visualize results
  • 6) revise categories (especially secondary schools)
  • 7) recalculate 15 min Score for Munich
  • 8) clean acatech code
  • 9) document results in the Miroboard (Heatmap Ideas), so it can be implemented in the future -> link important code snippets from the acatech repo/ our first couple trials

Resources

Deliverables

our amenities grouped into 4 groups with different sensitivity parameters

Branch to derive

analyses-acatech/feature/sensitivity-analysis (-> notebook goat_survey)

@Philipp-Otter Philipp-Otter added this to the v1.5 milestone Nov 30, 2022
@Philipp-Otter Philipp-Otter self-assigned this Nov 30, 2022
@EPajares EPajares modified the milestones: v1.5, v1.6 Jan 3, 2023
@Philipp-Otter
Copy link
Author

Miro Board (also with links to config etc.) -> Miro Frame "Summary" (https://miro.com/app/board/uXjVPW_6D8w=/?share_link_id=396722062190)

@EPajares EPajares removed this from the v1.5 milestone Jun 6, 2023
@p4b-bro
Copy link

p4b-bro bot commented Jun 6, 2023

This task/issue closed on Tue Jun 06 2023 ✅

@p4b-bro p4b-bro bot closed this as completed Jun 6, 2023
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants