Detailed analysis done to investigate possible reasons for delay in Grab services for NUS Data Analytics Competition 2022, to be found in here and here.
Our main tech-stack:
- Vahalla, a C++ implementation for map matching.
- ipyleaflet, for very interactive visualizations of geospatial data analysis
- geopandas
- Dask
- matplotlib & seaborn
We've shortlisted the reasons to be:
-
Traffic bottlenecks at popular shopping malls due to narrow infrastructures of pickup points. We comparatively found out that pickup speeds at Changi Airport with optimized pick-up and drop-off pioints are much faster at the initial and end-timings of each trip, compared to popular shopping malls with narrow queues at their pick-up and drop-off locations.
-
Drivers picking inefficient routes, as we compare the actual driver routes taken with popular Google Maps and Open Street Map routes which we pulled using Google Maps API and
osmnx. We found out that drivers's supposed "shortcuts" are more often slower, albeit, there were in-fact expert-curated routes which were actually even faster than Google Maps and Open Street Maps. These insights could be used to augment Grab-Nav!
Team:
- Keng Hwee Lead @kenghweeng
- Russell Saerang @RussellDash332
- Sean Gee Zhing @pikasean
- Terry Lim @terrylimxc