MUSTANG MOBILITY

Accessibility-first campus navigation

Navigating a university campus isn’t just about distance—it’s about access. Existing tools like Google Maps or static accessibility PDFs don’t support real campus needs: multiple destinations, entrance-level accessibility, or building hours.

Buildings aren’t single points.

Accessibility depends on which entrance you use. Modeling each building as a single node hides critical constraints and leads to unusable “shortest paths.”

SIXTY PERCENT

of disabled students experience fatigue simply trying to get around campus—often without sufficient institutional support.

THE SOLUTION

Model the campus as a graph where each building has multiple entrance nodes, each with its own accessibility metadata. Then compute routes using Dijkstra’s algorithm, selecting the most accessible entrance–exit combination at every step.

Users can:

• Select multiple buildings

• Filter for wheelchair-accessible entrances

• View entrance images, building hours, and closing warnings

THE PROBLEM

INSIGHT

CORE SYSTEM DESIGN

• Graph-based model with 5,000+ edges

• Dijkstra’s algorithm for reliable, constraint-aware routing

• Adapter pattern to decouple graph storage from algo and UI

• Singleton graph instance to ensure consistency and performance

This structure made the system scalable, debuggable, and realistic.

CHALLENGES → SOLUTIONS

• Messy real-world data → CSV validation + logging

• Missing nodes in adjacency lists → defensive checks + refactored edge models

• Multi-entrance complexity → evaluate all entrance combinations per route leg
  
  

Each challenge reinforced that real-world systems are messy—and must be designed for it..