Constructed a comprehensive dataset of student travel routes and spatial interactions in Delhi by combining reported travel behavior, GIS processing, and simulated routing. Student-reported routes were mapped as sequences of travel legs using the Google Maps API, incorporating departure times and multimodal transport. In parallel, potential routes were generated across walking, driving, and public transit options, selecting the top alternatives suggested by Google Maps and accounting for traffic conditions and standardized departure times.
The dataset integrates multiple spatial components. Student location shapefiles were merged and used to compute neighborhood proximity measures within varying radii. Route-level data were enriched with safety indicators through GIS-based intersections with safety surfaces, producing segment- and route-level safety measures. Additional datasets capture route overlaps by transport mode, routes outside Delhi, and extended samples for major colleges.
To complement observed data, a simulation framework generated routes between grid-based origin points across Delhi and all colleges, estimating travel time, distance, cost, and safety attributes. All datasets were harmonized and consolidated into standardized formats, enabling consistent analysis of travel behavior, accessibility, and safety across both observed and simulated routes.