AlterAtlas: Shifting Travel Planning from AI Generation to Validation via Persona-Driven Simulations
Human-Computer Interaction
Summary
The authors created AlterAtlas, a travel planning tool that helps people make better trip plans by using traveler profiles called personas. These personas simulate how different users might feel during the trip, like getting tired or hungry, to find problems in the itinerary. Users can then adjust both the trip plans and the personas to create better fits between the plan and personal preferences. The authors showed that people using AlterAtlas made plans that matched traveler needs more closely and felt more confident in their final decisions.
Authors
William Huang, Ruofei Du, Yang Zhang
Abstract
Travel planning requires balancing interacting goals and constraints across time and space. Current AI travel tools provide limited support for encoding these constraints and understanding how generated travel plans may fail users. We present AlterAtlas, an interactive travel planning system that supports high-fidelity itinerary validation and revision through persona-based simulations grounded in geospatial information. AlterAtlas models travelers as editable personas, generates candidate itineraries from prioritized places of interest, and simulates how different personas would experience each plan. Simulations expose route-level tradeoffs, temporal user states (e.g., fatigue, hunger), and mismatches between plans and user preferences to allow users to iteratively refine both itineraries and user personas. An expert evaluation of 51 paired itineraries demonstrates that simulation-guided revisions significantly improve plan-persona alignment. Furthermore, a within-subjects study (N=11) reveals that AlterAtlas empowers users to uncover hidden constraints, fluidly compare alternatives, and build trust in their final plans. Our results suggest that simulation-based validation is a powerful, transparent interaction layer for AI-assisted travel planning.