Example code of BSM analysis using Python and Jupyter Notebooks
| Notebook | Description |
|---|---|
| find_nearest_road_segment | calculate the road segments traversed during a trip; this algorithm is still a work in progress; needs more work to perfectly identify the exact road segments traverse. It will sometimes pick up roads intersecting the trip or miss a segment altogether |
| weather_info | get the historical weather from Dark Sky for a given GPS coordinates and timestamp |
| Google_Maps_Time_Zone_API | return the time zone and time offset for a given GPS coordinates and a timestamp |
| geopandas_spatial_join | assign vehicle activity points to correct census tracts; plotting a complete trip over tracts |
| generate_road_network | generate Michigan road network |
| trip_dashboard | rudimentary dashboard for a trip including speed, yawrate using Bokeh (unfortunately Bokeh plots don't render on Github) with linked brushing |
It's currently at this github site: https://github.com/caocscar/ConnectedVehicleDocs