In this thesis, the applicability of tram-train in an urban region is studied. A three-step top-down method is used, to narrow down the solution space and determine whether a tram-train solution can be applied, is suitable and technically feasible.

A heuristic method for the operation of shunting yards is created that considers the sorting process of wagons with dangerous goods. This concerns shunting yards where the wagons are distributed manually, and communication takes place by telephone. The first problem is that an entire train is considered dangerous if there is a wagon with dangerous goods on the accompanying wagon list. The wagon list shows where each wagon is positioned within a train composition. Due to safety regulations, a certain distance must be kept between wagons for certain dangerous goods classes. Because entire trains are considered dangerous, adjacent tracks must be left empty. This is at the expense of the capacity of the yard. The second problem is that the wagon list is not 100% correct due to human errors. Random checks show that the wagon list does not always turn out to be correct and that mistakes are made in creating the list. Therefore, smart camera techniques have been developed to detect which wagon contains which dangerous goods on arrival to confirm the wagon list. This opens up new possibilities concerning the sorting strategy of wagons from the arrival track onto the classification tracks in accordance with their destination. Research is done to find out what this new sorting strategy should look like. Therefore, the following research question is formulated: ‘What kind of method can distribute wagons, including wagons carrying dangerous goods, on a rail yard, considering safety?’. In order to answer the research question, qualitative research was carried out into the various existing strategies and methods that could be applied. A model is created in which wagons are sorted over classification tracks. The model chooses the track on which the wagons should be placed based on the destination. Specific attention is given to wagons with dangerous goods, for which the model ensures that a specific distance is kept from other wagons on the (neighboring) classification tracks. The model then determines the most appropriate departure time, and the train departs. Different scenarios are tested that the model has to deal with. A distinction is made here between whether the number of classification tracks is equal or not equal to the number of destinations, and whether the rate of dangerous goods over the destinations is equal or not. This makes a total of four scenarios that have been tested. The effect of using a buffer on the track is examined so that a wagon carrying dangerous goods never stands next to another wagon carrying dangerous goods of a different class if they are not allowed to stand together. This is tested in the model, and the output showed the placement of the wagons and the processing times.