Netherlands Railways (NS) is facing increasing volumes of passengers in many stations. And this number is expected to grow in the next few years. Royal HaskoningDHV developed measuring system in cooperation with Netherlands Railways (NS). This tool has already been implemented on the NS railway stations of Leiden and Groningen.
Confronted with potential capacity problems, Netherlands Railways needs to have insight into future demands. Although many ideas had been proposed to resolve future challenges, the quantitative data was still missing. There was no measuring tool that could produce reliable and accurate measurements of visitors in high density areas like a station. At the same time, it was important to handle the privacy of those visitors very carefully. Royal HaskoningDHV was asked to develop such a system in cooperation with Netherlands Railways.
Measuring system provides insightSMART Station is a measuring system that provides Netherlands Railways with the requested data so that all their criteria are met. As such, it collects and analyses data to obtain better understanding of how passengers use a station. A selection of analysed variables:
- Passenger duration times in an area
- Passenger route choices
- Passenger densities in an area
- Passenger waiting times for facilities, trains
- Passenger capture rates for signage, retail
- Conversion rates
- Passenger volume dwell and peak cycles
- Walking speeds
- Passenger Travel purpose
Data used to improve stations
Smart Stations gives Netherlands Railways better insight into how stations are used. With this data, operations and future designs can be improved, optimising station passenger handling capacity and creating faster, more comfortable and safer Transfer. Jeroen van den Heuvel, programme manager SMART Station at NS: “SMART Station allows us to generate new weekly insights for station regeneration projects and current station and train operations. In some cases, the measurements confirm common knowledge in our company, but frequently we run into unexpected results about passenger behaviour. These insights allow us to focus on what really matters for our passengers.”