Nitra

Nitra has invested in comfortable low‑floor buses and introduced a cashless ticketing system, eliminating manual ticket validation that once provided basic passenger counts. Today only 15 out of 80 buses are equipped with automatic passenger counters, leaving the city planners without a complete and reliable picture of where passengers board and alight. 

As a result, public transport planning relies on fragmented information: occasional manual surveys, partial data and assumptions based on historical patterns limit the ability to understand demand on individual routes and adjust service and timetables accordingly.  

All buses already have CCTV cameras systems capable of capturing passenger movements; however, broader data and understanding is needed to effectively adjust public transport to the real citizen’s needs.  

Accurate, aggregated boarding/alighting data would help Nitra tailor services to demand, identify overloaded or underused segments, and align public transport with the city’s Sustainable Mobility Plan for 2026–2032. 

Area: Selected bus routes within Nitra’s urban bus network (focus on high‑demand corridors such as lines 4, 8 and 12 connecting the city center with residential districts) 

DESIRED SITUATION

Through this RAPTOR pilot, Nitra aims to test an innovative, lightweight solution to automatically collect anonymised boarding and alighting data on selected bus lines. The pilot should demonstrate a practical and scalable way to understand passenger flows and support data-driven improvements to public transport operations.  

The pilot aims to: 

(1) cover at least 80 % of trips on selected bus lines with reliable boarding/alighting data (up from ~19 % today),  

(2) generate detailed passenger counts by route, day and time to inform planning,  

(3) identify at least three under‑ or over‑capacity segments and enable targeted timetable or stop adjustments,  

(4) reduce time spent on manual data collection by 50 %, and  

(5) ensure 100% of collected data is aggregated and anonymised to comply with privacy regulations.  

Longer‑term, the city aims to integrate the solution into its SUMP implementation framework and scale it across the full bus fleet and potentially to other public spaces.