Research
To understand whether a validator could function without written instructions, we first examined the current ticket validation experience across Budapest's public transportation network. We documented existing validator interfaces, printed information materials, ticket purchasing instructions, and suburban fare explanations to better understand what information passengers rely on during their journeys.
In parallel, we analyzed open-loop ticketing systems used in other European cities to identify common interaction patterns and approaches to communicating validation, payment, and fare information.
Mapping Information Needs
Based on our observations and findings, we mapped the information passengers encounter throughout the validation process. Through collaborative workshops, brainstorming sessions, and rapid ideation, we explored which pieces of information are essential and how they might be translated into a purely visual language.
Animation Exploration
One of our earliest concepts focused on using animations to guide passengers through the validation process without relying on text. We quickly sketched and tested several animated interactions to communicate ticket purchases, validation states, and system feedback.
While participants generally understood the intended messages, testing revealed that animations introduced unnecessary delays. Public transport interactions happen within seconds, and users expected immediate feedback rather than waiting for explanatory sequences to play out.
Testing Existing Iconography
Since animations proved unsuitable for fast-paced validation scenarios, we shifted our attention to static visual communication. We explored whether BKK's existing iconography could effectively communicate validator states and error situations without the support of written language.
Particular attention was given to error feedback, as failed validations often occur in public settings where passengers may already feel rushed or uncomfortable. We tested for example how to show validator isn't working.
To evaluate the effectiveness of the visual language, we tested multiple symbols and feedback states with users. Participants were asked to interpret the meaning of different icons and describe the actions they would take based on the feedback shown by the validator.
The results highlighted significant inconsistencies in interpretation. Symbols that appeared obvious from a design perspective often conveyed different meanings to different users, demonstrating the challenges of creating a truly language-independent validation experience.
