tuchandra/route-externalities

An examination of externalities associated with alternative routing criteria and third-party platforms.

route-externalities

An examination of externalities associated with alternative routing criteria and third-party platforms.

Origin-Destination Pair Preprocessing

1. Choose geographic area and download OSM-based road network from Mapzen
   • (https://mapzen.com/data/metro-extracts/)
2. Generate grid covering city area
   • preprocessing/grid_creation.py
3. Generate od-pairs for a grid
   • preprocessing/generate_od_pairs.py

Scenic Routing Preprocessing

1. Gather Flickr and Twitter data for study region
2. Score each grid cell based on Empath analysis of Flickr/Twitter data
   • preprocessing/generate_grid_scores.py

Safety Routing Preprocessing

1. Generate mapping of grid cells to census tracts (or equivalent) for city
   • utils/gridcell_to_ct_mapping.py
2. Gather crime data for city
3. Aggregate grid data to census tract equivalent and set threshold for unsafe areas
   • utils/aggregate_grid_values_to_ct.py

Analysis Steps

1. Get Google and Mapquest routes for od-pairs
   • mapping_platforms/get_routes.py
2. Get GraphHopper routes for od-pairs
   • see https://github.com/joh12041/graphhopper
   • com.graphhopper.reader.osm.AlternativeRoutingExternalities
3. Match Google and Mapquest routes to GraphHopper network for final metrics
   • see https://github.com/joh12041/graphhopper
   • com.graphhopper.reader.osm.AlternativeRoutingExternalities
4. Merge together GraphHopper metrics and original data
   • utils/merge_api_gh_results.py
5. Route-level analyses between all routes
   • routelevel-externalities/routelevel_externalities.ipynb
6. Compute signiificant differences with GraphHopper fastest routes
   • utils/significant_diff_segments.py
7. Run community-level analyses
   • community_externalities/calc_hmi.py

Example Data

• Load in statsobjs_routeexternalities.pkl in routelevel_externalities/routelevel_externalities.ipynb