A quantitative assessment on the design of a railway station

Transcription

1 A quantitative assessment on the design of a railway station W. Daamen Delft University of Technology, Department of Civil Engineering, The Netherlands Abstract Public transfer stations are evolving into multi-functional public areas, attracting much more people. A lot of extra trips are made by public transport, causing the system to reach its capacity, especially during peak periods. Not only does the number of vehicles increase and does their occupancy degree grow, also congestion occurs in the transfer station itself. Unlimited expansions of the necessary transfer area is not an option: inner city areas must contain many different functions and public transport is just one of them. By adding more functions, the number of processes increases, their complexity increases and the design process also becomes more complex. Therefor, (simulation) models are needed to evaluate the location of the functions and the amount of infrastructure for each function. A key issue in this process is the comfort of the pedestrian: he must be able to walk to his destination inside the railway station, in a quick and comfortable way, along short paths without too many height differences. Also, the occurrence of congestion must be prevented as much as possible, in which especially stairs and escalators will form bottlenecks. In this paper an overview is given of the process of integration of the different functions, the timetables and the platform allocation to optimise pedestrian comfort. The applicability of this simulation model will be exemplified by a model of the station of Delft. 1 Introduction The traditional way of designing transfer stations is based on rules of thumb. These rules convey many years experience concerning the behaviour of 1/1

2 passengers in transfer stations. However, they only pertain to static situations. Until now, a scientific foundation for these design rules has not yet been provided. Moreover, the dynamic behaviour of pedestrians in relation to the other processes in a transfer station also needs to be taken into account in order to predict the impact of a station layout design in practice. 1.1 Purpose of the paper In association with Delft University of Technology, Holland Railconsult has developed the simulation tool SimPed to estimate both mean and variability of walking times incurred by transferring passengers and to visualise walking patterns inside transfer stations. Simulation studies with this tool reveal levels of service for passengers in transfer stations. This paper shows a case study in Delft, for which the model has been applied. 1.2 Requirements for the simulation tool The requirements for SimPed can be divided into three categories, namely: requirements regarding the situations the tool can cope with, requirements regarding the dynamics in the pedestrian model and requirements regarding the performance Different model situations The aim of this research is to model pedestrians, rolling stock and the interactions between them (i.e. access a train and egress from a train). Therefor, a generic architecture has to be developed, which can be extended with all other modes of transport. This tool needs to be applicable for different situations. For one, the tool needs to be sensitive for variations in spatial design, which also includes variations in the spatial form of the different areas. Secondly, variations in timetable or train frequencies having effects on the pedestrian flows in the station need to be possible and must be visible in the output of the tool. Then, variations in the type of trains stopping at the platform need to be taken into account, resulting in different times to get on and off the train and thus generating another pattern and headway of incoming passengers. Finally, we distinguish different types of pedestrians with different behaviour characteristics leading to different transfer times. General traffic characteristics of pedestrians will be adjusted to those of passengers in transfer stations and calibrated using Dutch empirical data (to be collected) in order to obtain an appropriate model for the Dutch situation Model dynamics Both pedestrians and public transport facilities are part of dynamic processes. Interactions between pedestrians are explicitly modelled in microscopic models, where macroscopic models describe the characteristics of pedestrian flows. Both types of models will be included in the tool. Public transport facilities influence arrival and departure times of pedestrians and thus influence the resulting pedestrian flows and especially the times pedestrians pass in railway stations. 2/2

3 Also, characteristics of the different rail vehicles influence the times pedestrians need to enter or exit it. All these public transport characteristics must be included in the tool Model performance The simulation tool must be able to handle large transfer stations of at least 100,000 m 2 area intended for walking purposes. Furthermore, it should be prepared for the presence of about 100,000 persons during the same period of time. 1.3 Outline of the paper This paper outlines the simulation tool for pedestrians SimPed. We start with an illustration of the pedestrian model within the tool. Then, the opportunities of the tool are illustrated by an example of Delft Station. We end with conclusions. 2 Operation of the pedestrian model Using a macroscopic model, we can roughly assess the level of service and occurring congestion in the network. Subsequently, microscopic simulations are used to analyse these locations in more detail thereby determining the causes for congestion. In the current version of the model, a (quasi-) macroscopic model is built in, explained by the following example. Entrance Walkway Exit In this example, pedestrians enter the walkway on the left, walk through the walkway and exit the model at the right. This process is visualised in Figure 1. Speed - density relations Mean speed (m/s) Density (peds / m 2 ) Figure 1: Visualisation of the macroscopic model 3/3

4 When a pedestrian enters a walkway, the current density is calculated, dividing the number of pedestrians present in the walkway by the net surface of this walkway. Then, the mean speed at this density is derived from the given speed density relation. The individual speed of the pedestrian is calculated, multiplying the mean speed by the ratio of factor free speed of the pedestrian over the mean free speed. The time the pedestrian needs to walk through the area is calculated by dividing the length the pedestrian has to walk to its speed. During this time, the pedestrian is connected to the walkway. After this time the pedestrian will either go to another area or, as is the case here, leave the model. 3 Application of SimPed for Delft Delft is a city of inhabitants, situated in the western part of the Netherlands between four large Dutch cities (Amsterdam, Rotterdam, The Hague and Utrecht). The railway line running from Rotterdam via The Hague to Amsterdam passes Delft. This railway line nowadays has two tracks, but with eight trains per hour per track during peak hours, the capacity of this line is nearly reached. Therefor, several studies have been performed to study the possibilities of a four track tunnel under Delft. Some of these studies also take into account the possibility of transforming the current tramline into a light rail line, being underground in the centre of Delft as well. The simulation study we performed for the new underground station is used to illustrate our simulation tool. 3.1 Location description The starting point was a first design, shown in Figure 2. Figure 2: Overview of Delft Station 4/4

5 At the 2 level four train tracks are situated with two central platforms. At the end of the platforms are two escalators and stairs in between, leading to the lower level. This level contains one central platform with on both sides a light rail track. At the other end of this level, two escalators and one stairs in between lead to the exit points at the ground floor. Two lifts (one to each train platform) are located at this side of the ground floor, also connected to the light rail platform. 3.2 Input model Based on this information, we constructed the input model, part of which is shown in Figure Figure 3: Input model of Delft Station In our input application, we distinguish the following infrastructure elements: 1. Walkways. This is the area pedestrians walk on. For each walkway we know the number of pedestrians present. Pedestrian density is homogeneous on the walkways, so the infrastructure is divided into smaller areas. 2. Stairs. Pedestrians have the same behaviour on stairs as on walkways; only their speed differs in both upwards and downwards direction. 3. Escalators. We distinguish pedestrians walking on the escalator and pedestrians just standing still. Furthermore, the next pedestrian can only step on the escalator when a new step has arrived. 4. Lift. Pedestrians can be given the characteristic of being disabled, so they can not use stairs or escalators. In general, normal pedestrians do not use the lift, except when it is the only opportunity to go to another level. 5/5

6 5. Connections. Connections are used to indicate the locations a pedestrian can go from one walkway to another. This can be free space (on a platform for example), but also a door or a turnstile. These last elements can also cause some delay (the pedestrian needs to open the door before he can pass it). 6. Activities. A pedestrian can perform activities in a station. These can be either station related or not. Station related activities are for example buying a ticket, where a not station related activity is for example buying a paper. Locations where activities can be performed are indicated in the input application and for each location the type of activity is indicated. The pedestrian then chooses those locations to perform his activity that minimise his total walking time. 7. Tracks. These tracks can be for railroad traffic, but also for light rail, metros and buses. Its function is to indicate the stopping place of the vehicles, in order to determine the locations of the doors. To determine the moments passengers enter and leave the model, we can define a timetable, shown in Figure 4. Figure 4: Timetable The tracks are set along the vertical axis, whereas the time is set along the horizontal axis. Each dark grey line in the timetable indicates a train or light rail vehicle. It starts at the moment a vehicle has been planned to arrive along the platform and is ready to open its doors and it ends at its planned departure time. For each train the rolling stock can be determined. Especially in the Netherlands many different types of rolling stock are used, all having other doors at different locations. The rolling stock characteristics concern length of the vehicle, number of cars, number and location of doors and characteristics of each door such as door width and height above the platform. For each train the number of boarding passengers and their origins and the number of egressing passengers and their destinations is specified. A destination can also be another train, this way creating transferring passengers. The simulation tool can also be applied in areas without public transport, for example in stadiums, in airports and in shopping centres. Origins and destinations of pedestrians are then not determined by a timetable. Therefor, we can define entrance and exit points in the model, indicating locations where 6/6

7 pedestrians can enter or leave the model. For each pedestrian flow in the model, we can define a generator, indicating the number of pedestrians walking from a specified origin to a specified destination during a given time period. For each pedestrian flow an origin and destination is known. On their way, pedestrians can perform activities. For each flow is specified what activities the pedestrians will perform and the number of pedestrians actually performing them. For example, 40% of passengers coming from outside the station going to the train to Amsterdam first have to buy a ticket and, when they have time left, they will buy a newspaper. For each pedestrian flow also characteristics of pedestrians can be indicated. These are free speed (the speed they want to walk with when no one is around) and familiarity with the station (when pedestrians are familiar, they walk directly to their destination, whereas when they are not familiar, they first look for additional information). 3.3 Animation After the input of the model has been completed, the model can be simulated. To make processes understandable (see what is happening) animations can be used. In fact, we created two types of animation. The first one is more technically orientated (see Figure 5) whereas the second animation is more suited for decision makers (see Figure 6). Figure 5: Frame of the 'technical animation' of Delft In the 'technical animation', the number of pedestrians present in a part of the infrastructure (walkway, stairs or escalator) is indicated by the level of service. We use internationally accepted standards for this level of service, as defined by Fruin [1]. In Table 1 these levels of service are shown. 7/7

8 Table 1: Definitions of levels of service on walkways Level of service Colour Density (m 2 / ped) Intensity (ped/m/min) Speed (m/s) A Dark green > 3.2 < B Light green C Bright green D Yellow E Orange F Red < 0.5 > 82 Also, the public transport vehicles are shown. For each element in the animation, characteristics are shown in a dialog (such as width, length, number of pedestrians present). For walkways, stairs and escalators, it is also possible to see how the number of pedestrians changes. Figure 6: Frame of the three dimensional animation of Delft This three dimensional animation provides a realistic view on the crowds within the station. In Figure 6 we see the 1 level, with two light rail vehicles at each side of the platform. The viewpoint is right above the train platform and we look in the direction of the exits at the ground floor. We see groups of passengers waiting to get in the light rail vehicles and we see that queues have already been formed for the escalator leading to the train platform (transferring passengers). This animation is based on exactly the same results as the technical animation. 8/8

9 3.4 Output The results of the simulation are stored in a database. The simulation tool provides a number of utilities to analyse the data. The results are based on interactions between pedestrians and infrastructure. We therefor can look at the results from the point of view of the infrastructure and from the point of view of the pedestrians. Let us illustrate both Infrastructure Figure 7 shows the percentage of time a specific part of the infrastructure had a specific level of service. Each bar represents a part of the infrastructure, which name is shown under the bar. For example, on the escalator with number 1 (leading from the train platform to the light rail platform) level of service A occurred 53% of the time, level of service B 2% of the time, level of service C about 10% of the time, level of service D about 12% of the time and the rest of the time (26%) level of service E occurred. The administrator of the infrastructure has standards for this level of service: for example, he wants his station to have 95% of the time a level of service D or better. Figure 7 shows that this standard is not reached and modification of this infrastructure is necessary. 100% 90% 80% Percentage (% 70% 60% 50% 40% Level 2 02 Level 2 12 Level 3 16 Level 3 19 Platform 1&2 22 Platform 1&2 23 f Platform 3&4 20 Platform 3&4 21 Escalator 1 Figure 7: Percentage of level of service on the infrastructure during the simulation Stairs Pedestrians In this study for Delft we made an indication of the deviations of pedestrians from the minimal walking time on a specified origin - destination relation. 9/9

10 25 Pedestrians (%) Walking time (min) looptijd (min) Variations weena - N Figure 8: Variations in walking time from an origin to a destination In Figure 8 the percentage of pedestrians having a certain walking time is indicated. At first, all pedestrians have the same (shortest) walking time. Then, more pedestrians use these routes, speeds of the pedestrians decrease and walking times becomes longer. At some moment, another route is longer, but faster and more pedestrians will use this second best route. The walking time stabilises until the number of pedestrians again decreases or increases. This figure indicates the robustness of the station: when the number of pedestrians increases, do their walking times increase equally? 4 Conclusions This paper describes the dedicated pedestrian simulation tool SimPed, The tool is able to model pedestrians in transfer stations and provides inside into the comfort of the pedestrian in a transfer station during peak hours. The tool can be used in the early planning phase (when the plans are not yet elaborated and the number of stairs and escalators and the width of tunnels can be changed), but also during the design stage (when more detailed plans are drawn) and during the operational stage (bottlenecks become visible and need to be solved). The tool has already been applied successfully in several studies, among others for Rotterdam. The type of input and possible outputs are shown from the example of Delft, a medium sized transfer station in the Netherlands. References [1] Fruin, J.J., Pedestrian planning and design, New York: Metropolitan Association of Urban Designers and Environmental Planners Inc, /10