- Showcase the power and limitations of data centred approaches
- Jointly understand and learn from the different COVID approaches and views
- Shape the time for Data Science research/education after the lock-down
𝗟𝗲𝗰𝘁𝘂𝗿𝗲 𝟱: 𝗖𝗢𝗩𝗜𝗗-𝟭𝟵 𝗮𝗻𝗱 𝗰𝗮𝗽𝗮𝗰𝗶𝘁𝘆 𝗺𝗼𝗱𝗲𝗹𝗹𝗶𝗻𝗴 𝗶𝗻 𝗽𝘂𝗯𝗹𝗶𝗰 𝘁𝗿𝗮𝗻𝘀𝗽𝗼𝗿𝘁
12:00 Welcome & Introduction
12:05 Talk by Dennis Huisman and Menno de Bruyn
Since Mark Rutte’s press conference on March 12, many people are studying and working from home. As a consequence, the number of passengers using public transport has significantly dropped. On Friday March 13, the number of passengers was 85% lower than on a regular Friday. The following week, the reduction was even larger. At the same time, the percentage of employee illness increased significantly.
In this presentation, we will first talk about the short-term challenges NS faced. From March 21 to June 1, NS operated a significantly reduced timetable. We will discuss how this timetable was designed and how advanced algorithms were used to construct this timetable (and the steps to return to the normal timetable) and the related rolling stock and crew schedules.
We will also talk about the challenges that NS will face in the coming years. Passenger demand will be reduced in the coming years due to the economic depression, other behaviour (working from home and online lectures) and passengers’ fear of using public transport. To get better predictions on travel behaviour, NS started a large customer survey on passenger behaviour after the COVID-19 crisis. We will present the first results of this survey and the expected impact on NS.
Marc Salomon (ABS UvA, ADS) and Mark Hoogendoorn (VU, AMDS)
Dennis Huisman is Expertise Manager Logistic Processes at NS and Endowed Professor Public Transport Optimization at Erasmus University Rotterdam