To develop a demand-oriented train service plan, the railway passenger demand characteristics are needed to be analyzed first. The analysis mainly starts with the volume and structure of the demand, and based on these characteristics, periods that have similar characteristics are classified into the same pattern. Thus a period of time, for example, a week, can be divided into several periods with different demand patterns. One period is considered as the base demand period among all those periods, and the demand contained in this period is always present during the week, its fluctuations are small and occupy the vast majority of the time except for the peak period.

Unlike the existing method that the train service is designed according to the peak hour demand, the train plan will first be designed based on the base demand. This base service will exist all through the period (e.g. in one week) and provide service for all base demand services. The service adaption will be made and added to the base service for all other periods. According to the different demand patterns, those adaptions can be add-on or subtracted services. Those adaptions can adjust the service to match the changed demand over time.

The COVID-19 pandemic has had a substantial impact on public transportation. With ridership figures decreasing, it has brought a new sense of urgency to the old problem of crowding. Using a structured design approach, this paper presents the results of a project which set out to reduce crowding in Dutch train stations by
absorbing it at the network level. The design which is detailed in this paper uses advance communication of bike parking availability and price incentives on shared bikes as means to stimulate travellers to access or egress the railway system through alternative, uncrowded stations. It is determined that, theoretically, up to 7% of daily travellers in the Amsterdam region might use the system, suggesting that effects on station capacity would be substantial high adoption levels are realised.

Covid-19 has had a major impact on mobility and especially on public transportation. In the Netherlands, the impact on public transport usage reduced up to 90% per day during the Covid-19 crisis compared to 2019. In June 2021, when travelling by public transport was allowed again, the usage was only half compared to a similar weekday in 2019. To gain information on current and expected future travel behaviour, Nederlandse Spoorwegen (NS) and Delft University of Technology (TU Delft) organized longitudinal surveys in April 2020, June 2020, September 2020, December 2020, April 2021, and September 2021. These surveys give quantitative insights on current and future travel behaviour that help restore and redesign public transport properly after the Covid-19 pandemic.
This project focused on the effects of anxiety on train travelling behaviour during and after Covid-19. The main purpose of this project was to investigate the group of anxious train travellers during Covid19 and gain more insight into this group, their characteristics, behaviour, and attitude. The main factors and characteristics that influenced anxiety levels were age, gender, and vaccination status. These factors are in line with literature from other countries on anxiety in public transportation during Covid-19. A typical profile of an anxious person is a female, older than 25 years old and not vaccinated. Since attitude already has a strong relationship with travel behaviour, the anxious group was compared to the not anxious group to investigate the effects of anxiety on travel behaviour and attitude. The results show that anxiety has a negative effect on attitude which leads to less usage, both current and expected usage in the future. Anxious people tend to generally have a negative attitude towards the train, while not anxious people generally have a positive attitude towards the train. In current train travelling behaviour, anxiety has the effect of people travelling less, and more people are likely to not travel at all. For future expected travel, anxious people are more likely to plan to travel less than not anxious people.
The number of anxious people fluctuates over time and seems to be related to the number of cases or hospitalizations. The number of anxious people was higher when there were peaks in number of cases and hospitalizations, and lower when things were calmer. During the first year (April 2020 to April 2021), the anxious group had been over and around 40% of train travellers. It can be assumed that there will still be a group of people that are anxious after the pandemic, because in September 2021, when cases had been low for some time, there was a group of people still feeling very anxious. The results of this paper helped identify the anxious group and established the effect of anxiety on attitude and behaviour, which helps for designing timetables and planning rolling stock purchases.