bcn-transport_skill

Overview

This skill encapsulates operational knowledge of Barcelona's transport geography with emphasis on El Prat Airport (BCN), Sants station, and the local taxi sector. It helps shape geofences, predict taxi demand, and tune a useWhereNext scoring algorithm for dispatch decisions. The focus is practical: terminal layouts, taxi queue points, typical travel times, and demand drivers.

How this skill works

The skill maps terminal areas (T1, T2A/B/C) and Sants station platforms to precise polygon geofences and labeled pick-up/drop-off zones. It correlates flight and train schedules with known demand patterns and applies IMET-style operational constraints (shifts, peak pricing windows) to rank next-best staging or dispatch locations. Travel-time heuristics between key nodes refine scores and account for event-driven spikes.

When to use it

• Designing or adjusting BCN airport and Sants station geofences for taxi operations
• Tuning a useWhereNext algorithm to reflect local peak hours and travel times
• Predicting taxi demand around Fira events, nightlife peaks, or train/flight arrivals
• Modeling shift and pricing impacts using IMET-style rules
• Deciding where drivers should stage after completing a fare

Best practices

• Place geofences aligned to the physical terminal layout: separate polygons for T1 departures, arrivals, and dedicated pick-up lanes, and distinct polygons for T2A/B/C
• Treat Sants taxi zone and adjacent drop-off points as separate entities to capture AVE vs regional passenger flows
• Weight scores by correlation with vuelos.json and trenes.json arrival surges rather than raw counts; use short-term smoothing to avoid noise
• Incorporate typical travel times between BCN, Sants, Fira, Born, and Eixample when computing next-best locations
• Account for IMET-style shift schedules and holiday rules so staging suggestions respect legal and peak-pricing constraints

Example use cases

• Automate dynamic staging suggestions for drivers arriving at T1 after a cluster of incoming flights
• Adjust geofence polygons for T2C to better capture low-cost carrier passenger flows
• Prioritize dispatch to Sants taxi queue during AVE arrival windows and to Fira during trade-show peaks
• Refine useWhereNext scoring to avoid sending drivers into congested Eixample corridors during evening leisure peaks
• Simulate the effect of a public holiday on demand distribution and driver availability