Headway

Project dossier · Intelligent Systems P4 · November 2026

Headway

Dispatch that learns how long New York takes.

A neural network learns trip times across New York for every hour of the day. A constraint solver gives each order a van, and A* orders each van's stops. When a route runs late, Headway learns a new rule and plans again.

Moaz Hassan El-Garawany · Ahmed Hossam El-din

SlidesReportSource
Demo day · Thursday20 orders · 3 vans
ServeDestinationVanOrderStatus
  1. 10:15LENOX HILL W0#11ON TIME
  2. 10:45SUTTON PLACE2#07ON TIME
  3. 11:30YORKVILLE W0#14ON TIME
  4. 11:45UES NORTH2#12ON TIME
  5. 11:45UES SOUTH1#01ON TIME
  6. 12:30YORKVILLE W0#00ON TIME
  7. 12:45PENN STATION2#06ON TIME
  8. 12:45UWS SOUTH1#02ON TIME
  9. 12:49UES SOUTH0#13ON TIME
  10. 13:02LINCOLN SQ E1#08ON TIME
  11. 13:15LINCOLN SQ E2#18ON TIME
All twenty on time after the second planning loop

The dossier

Thirteen items on five lines. Each stop opens the work itself.

Code and data

  1. 1CodebaseOne package split by responsibility, four entry points, a pytest suite
  2. 2Data pipelineNYC taxi trips, January 2022, filtered and sampled with a fixed seed
  3. 3Data dictionaryEvery column, real or generated, and how it was made

Models

  1. 4Travel-time modelA numpy MLP measured against three baselines
  2. 5Route searchUCS, Greedy and A* with node counters and a brute-force check
  3. 6Van assignmentA CSP with switchable backtracking, forward checking and AC-3

System

  1. 7Integrated demoOne command: input, solution, trace, pruning, model on and off
  2. 8SetupPinned environment and the exact commands, in order
  3. 9Test suite29 test functions, 38 cases, normal, edge and impossible

Evaluation

  1. 10ExperimentsThree experiments, ten seeds each, mean and standard deviation
  2. 11ReportTen pages: problem, design, results, limits, conclusions
  3. 12PresentationTen slides with speaker notes and the live demo script

Team

  1. 13ContributionsIndividual statements and the git log