i "UK -i -i - / s • - if. /
{/)
CO
c
• ^ ^ ^u
CU
Q.
^OOZ J9qtu939
e*-,Ki. oS t t S S '
U O È S C M
Qj " o
Planologisch Memorandum is een uitgave van de Sectie Infrastructuurplanning van de Subfaculteit der Civiele Techniek, Technische Universiteit Delft.
De Sectie IPL richt zich in haar onderwijs en onderzoek op drie gebieden:
• beleidsontwikkeling rond infrastructuur,
• ruimtelijke planning en vormgeving van fysieke infrastructuur,
• methoden en techniek van planning en ontwerp.
PM informeert over de activiteiten van de Sectie IPL. PM bevat berichten, artikelen, samenvattingen van onderzoeksprojecten en van afstudeerverslagen.
PM verschijnt in elk geval tweemaal per jaar. In de reeks kunnen ook
monografieën of aparte themanummers worden opgenomen.
Faculteit CiTG
f^ibIiotheekCivi(
Stevinwes J
2628 C N W t
et
j:pi
i''iö'i
•
2 ,^/. - 7 , . , , ® Sectie Infrastructuurplanning, Civiele Techniek, TU Delft.Redactie: P.M. Schrijnen
Informatie over Planologische Memorandum
Sectie Infrastructuurplanning
a Postbus 5048, 2600 GA Delft b Stevinweg 1, Delft, kamer 2.15 t 015 27 83692 f 015 27 85263 e ipl@citg.tudelft.nl
n
O
o
ersitejt D d / i
'Je Techniek
locations,
a GIS analysis for identifying locations.
T.P. de Laat
Transfer point Schiedam
H.M. van Wingerden
Transferring faster in Delft
Network analysis as an instrument for designing public transport stations
Prof. Ir. F.M. Sanders Ir. E. van Duin
Agglomeration transfer points around the Randstad Holland
R. Schram
The development and
implementation of a parking place within the future Schiphol area
C.J.G. van Remoortere
Combination possibilities of transfer points with commercial real estate: modelling and financial analysis
/?./-/. Kootstra
View on Corridors
Valuating accessibility for location development
Editorial
Spatial structures and transport networks meet each other in transfer points. Transfer points are places where people change from car to train and vice versa, f r o m motorised travellers Into pedestrians, as well as from movement towards activities. M o d e r n transfer points are not only nodes In a network but also urban centres of activities. Offices, shops and entertainment meet mobility and create an environment w h e r e accessibility is transformed into inviting facilities and revenues.
O p t i m i s i n g the spatial organisation of these transfer points is a major assignment for planners. This M e m o r a n d u m summarises a number of Master's thesis done by graduates of the Department of Infrastructure Planning, of the Faculty of Civil Engineering. Together, the seven articles give a w i d e variety of answers t o this assignment. The perspective in these articles is foremost on method. They focus o n the development of tools to analyse the behaviour of travellers and on the actual design of some elements of the transfer points.
In the first article De Laat studies the possibilities to use GIS (geographical information system) as a tool to choose proper locations for transfer points. He finds that GIS can be a proper tool to determine certain aspects of this location choice. The accessibility of various locations can be compared, the distribution of the transfer points over the research area can be optimised and the travel time for different modes of transport can be compared. De Laat stresses that GIS doesn't cope with all considerations relevant in choosing such locations.
Van Wingerden uses the results of the thesis of De Laat and focuses on the design of a
transfer point from road to train, near the Schiedam Station, near Rotterdam. Van Wingerden studies into detail the origins and destinations of possible users of this transfer point. On a micro level he also looks for a proper location of the facility. Integrating the facility with the development of offices right near the Schiedam railway station creates a feasible project, according to a MCA.
In the next article. Van Duin and Sanders use the Grafen theory to create a model for optimising the spatial composition of a transfer point. The study focuses on the travel time of the transfers between different access modes around the railway system. The model is applied on the case of the Delft railway station. The model enables designers to evaluate alternatives spatial configurations for such transfer points in detail.
Schram analyses the choices that car drivers make, in using park-and-ride facilities:
whether to use the car on the whole trip or to change to a train half way. Schram uses a systems analysis approach. He creates a model of the trade-off car drivers make. On that basis Schram selects locations for transfer points and designs the technical-functional lay out of one transfer point in detail. In his scheme, travellers can change their mode within six minutes.
On a smaller level of scale. Van Remoortere works on a scheme for short parking, an important facility in the accessibility of Schiphol airport. Using the simulation program Arena, she describes the process of parking in detail. She varies elements like traffic assignment systems, p a y i n g systems, and the influence o f luggage, and measures the
impact on possible time gains. Arena appears to be a suitable programming tool for modelling the various trade offs in the design problem.
In the next article Kootstra summarises his thesis on the combination of transfer points and commercial real estate. Kootstra works with Stella, a systems dynamics tool. With this tool he finds the optimal location for combining park-and-ride facilities and real estate development in the Randstad. On top of that he is able to assess different design schemes for the actual location.
In the last article, the real estate value of transfer points is addressed. Van der Knaap studies the relationship between changes in accessibility and the market value of an area. The surplus land value might be a source for the investment in infrastructure. Van der Knaap makes a residual land value calculation for a test location. He concludes that overall accessibility cannot be safeguarded on the basis of the real estate developments. But within a single corridor, a real estate development can substantially contribute to the infrastructure developments.
All these analyses show that there is still a lot to be learned about the design of transfer points. Traditionally, decisions about road and rail, and about infrastructure and real estate, are taken separately. The perspective of each individual initiator was dominant. When the perspective shifts to the consumers or to the travellers, new location choices and new design solutions for the road and rail networks come into the picture. With their work, the graduates of the Department of Infrastructure Planning have enriched and diversified the concepts of infrastructure systems.
Pieter Schrijnen December 2002
Transfer points: Searching for locations,
a GIS analysis for identifying locations.
T.P. de Laat
Abstract
This paper presents the results of an investigation on the usefulness of a geographical information system (GIS) to determine locations for transfer points. In the study, interesting locations for developing transfer points in the Utrecht region have been researched. Multi modal accessibility is used as the criterion to describe the potential of a specific location. Multi modal accessibility is defined as the accessibility of a location by car and public transport.
A geographic information system is used in this research. Three GIS-analyses have been carried out:
1. Quantifying the accessibility of possible locations for transfer points.
For a large number of possible locations, the accessibility is expressed in a potential value. This value is calculated by dividing the number of inhabitants of each zip code area by the time needed to travel from there to the transfer point location. These values per zip code area are then utilised to determine the potential value of the transfer point location. The analysis results in a ranking of the best accessible locations. These locations have the highest potential value. They are accessible for a large number of people in a small amount of time. Such locations can be found around the major cities - Utrecht, Amsterdam and
Rotterdam.
2. Optimizing the distribution of transfer points over the research area.
A Location-Allocation model is used to distribute the transfer points over the area. A selection is made out of a set of potentially suitable locations. These are the one hundred locations with the highest potential value in the first analysis. A good distribution of the transfer points must prevent their competition with each other. This is because every transfer point must have enough users to function properly. The
result from the analysis is a distribution of transfer points over the area, based on several criteria. Most of the transfer point locations are at the outside border of the search area. The large number of people outside the search area draws the transfer point to the border of the area.
3. Comparing the travel time for different means of transport.
The travel time from every zip code area to the centre of Utrecht has been calculated for three means of transport: car, public transport (train) and by using a transfer point. The assumption is that, inhabitants of a certain area chose the fastest means of transport. The car is the fastest means of transport for most of the zip code areas. To understand this situation more, the influence of congestion in the main road network is studied with the result that in a situation with congestion, using a transfer point is a good alternative instead of travelling by car. Secondly, the effects of an improvement of public transport is researched. If the speed of public transport is improved, then public transport is the best option to reach the city centre of Utrecht. However, this only applies to the areas properly linked to public transport.
For these analyses, various assumptions have been made. By using more detailed information, the assumptions can be reformed leading to more reliable results.
However, here a caveat must be drawn that despite the high practicability of the GIS-method, some questions will remain unanswered. The choice for a location depends on more factors than studied here. Not all of these factors can be visualised or analysed with a GIS. Thus, the role of GIS in finding suitable locations for transfer points is more limited to being supporting and directional (direction giving).
1. Introduction
Driven by economic growth and growing prosperity, car use in The Netherlands has increased rapidly over the past twenty years. The Dutch infrastructure has not been able to sustain fully the rising amount of road users, despite ongoing expansions of the road network. This has lead to congestions on the roads and it has had a negative impact on the living environment. The Dutch government has been trying to reduce the number of car kilometres in two ways: 1. by discouraging car use through
financial measures;
2. by offering good alternatives for car use.
The last category also includes the concept of transfer points [7]. The realisation of several transfer points is a measure to overcome mobility problems in The Netherlands. The objective of transfer points is to stimulate car users to transfer from their cars to public transport at convenient junctions i.e. Multi modal movements instead of unimodal [6].
The centre of The Netherlands is one of the key areas facing the negative consequences of growing congestion. Several projects in the field of traffic and transportation have been started to overcome the problems. The project "Transfer point - central Holland" is one of them. The aim of this project is to develop a concept of transfer points in a
network of roads and public transport connections. This research contributes to that particular project. It is a co-operation between Rijkswaterstaat Directorate Utrecht and The Delft University of technology, faculty of Civil Engineering. The focus of this research is on the choice for locations based on the accessibility of transfer points.
The problem analysis shows that currently no documented and manageable method to research locations for transfer points exists. Therefore, the objective is to develop a method to evaluate locations of transfer points on the criterion of multi modal accessibility. Multi modal accessibility means that a location is accessible by different means of transport. Besides that, the method analyses the sensitivity of a location for external influences. This research uses available automated systems. It has not been the intention to develop new ones.
The research uses a geographical information system (GIS). A geographical information system is a computer-based tool for mapping and analysing things that exist and events that happen on earth [1, 2]. GIS has considerable possibilities and advantages that can be applied in this research. GIS technology integrates common database operations such as query and statistical analysis with the unique visualisation and geographic analysis benefits offered by maps. A GIS has excellent possibilities for executing network operations. For example, the searching of a road with the least resistance. Or finding an optimum location within a network. A GIS consists of software (Arc/Info and Arcview), databases describing spatial elements and hardware (UNIX-workstation or Windows PC).
This paper consists of six sections. The first is an introduction to the subject and provides the general framework. The
research approach is explained in section 2.
The implementation of the approach is described in three parts:
• research into the accessibility of transfer point locations (section 3),
• research into the optimum distribution of transfer points (section4) and
• research into the functioning of transfer points (sections).
The study ends in Section 6 with the conclusions and recommendations.
2. Method of research
The following scheme shows the three analyses that have been carried out to evaluate transfer point locations.
Accessibility
Competitiveness
Transfer function
Potential values are calculated to compare the accessibility of potentially Interesting locations.
An optimum distribution of transfer points is generated to prevent mutual
competition.
Travel times of different means of transport provide insight in the functioning of transfer points.
Starting with the first analysis:
accessibility.
To compete with the car as the main means of transport, transfer points must have good accessibility. Good accessibility is also an important factor to attract business. The combination of business parks and transfer points leads to mutual benefits. Thus good accessibility is an important success factor for transfer points. Accessibility is defined as follows: the efforts one has to take to travel from one point to another
with a specified means of transport, at the desired point in time and via the desired route [5]. Effort is expressed in travel time, travelling expenses and comfort. It is important to use all these factors to describe the resistance to travel [5]. However, not all the necessary information was available to use ail the factors. Therefore, only travel time is taken into account.
A method to determine the accessibility of a location j is to divide the inhabitants of the area i by the travelling-time to get from i to j . To determine the accessibility of the location for more surrounding areas, all values are summoned. In formula:
The Dutch population is divided over
population i
Accessibility j = V
'~f traveling time i—j
almost 4000 zip code areas. The total population of a zip code area is chosen, because all inhabitants are potential users of a transfer point. The value that is calculated with the formula is called the accessibility value. This value is used to express the accessibility of a location. With the value, the accessibility of different locations is compared to each other.
Not every traveller uses the transfer point in the same way. Therefore, different user-groups have been distinguished. These are:
• public transport internal: coming from Utrecht, using public transport; • public transport external: coming
from outside the area, using public transport;
• car internal: coming from Utrecht, using the car;
• car external: coming from outside the area, using the car.
The accessibility values are calculated for all these four categories. The values are
combined to create one overall value for a specific location. Before they are summarised, they are weighted. In this way, the differences between locations will not be ignored. For example, a location can have a significantly better score in one category. That advantage is taken into account in the overall value. Secondly, the different categories are of the same magnitude. The result is a value for the multi modal accessibility of a specific location.
For the second analysis, a
Allocation model is used.
Location-Allocation determines the best location for one or more facilities in a way that makes it efficiently accessible for the public. Simultaneously the locations of the facilities and the allocation of the mass (to the facilities) are optimised. The set of possible locations is given in advance. As well as the number of facilities to be realised. The population is divided over a network with which the travel time is calculated.
The population of a specific area is always allocated to the nearest facility. However, there are six different models within Arc/Info to determine the best location for a facility. The MINDISTANCE model is chosen. This model minimises the total travelling resistance within the network. Travelling resistance is the total travel time of all the inhabitants from their origins to the transfer points. The secondary movement from the transfer point to the final destination is not included in the analysis. The model uses the shortest route for each traveller. This model suits the Dutch policy regarding mobility in the best way. The policy is to reduce the number of kilometres driven by car.
• The objective of the third and last analysis is to make a comparison of
the travel time for different means of
transport to reach Utrecht. Road users do not want to make too much extra
efforts when using a transfer point. If a journey via a transfer point costs too much time compared to a journey by car, then using a transfer point is not an attractive alternative. The origin is determined by the zip code area where the traveller comes from. The city centre of Utrecht is the destination. For every zip code area the travel time is determined three times:
• by car (the shortest route using the road network);
• by public transport (using the railroad network);
• and by using a transfer point (approach transfer point by car, leaving by public transport).
For every zip code area the fastest means of transport is determined. This is visualised in a map. Then by varying the assumptions, different situations and developments are evaluated. First, the influence of congestion in the research area is studied. Secondly, the influence from an improvement of public transport is researched.
3. Accessibility values.
Before calculating the accessibility values, a set of locations must be given in advance. These locations are linked to the nodes in the transport network. This data is stored in a CENTERS-file. A CENTERS-file describes in ARainfo where (possible) facilities are located. This file forms the input for the accessibility analysis. For each of the different locations in the file, the accessibility value is resolved.
At first, the accessibility is determined for existing locations. Transfer points already exist at some of these locations. Others are still being developed. These locations are stored in a different CENTERS-file. With the file a first analysis is made. The analysis of the existing locations is to test the method and to see if it provides the
expected results. The method worked as expected.
It is more interesting to calculate the accessibility of potentially new suitable locations. These are determined using the following criteria:
1. The travel time from the transfer point to the centre of Utrecht using public transport must stay within 30 minutes.
2. The location is accessible by car and by public transport.
3. The distance between the location and a highway stays within 500 meters. Highways have a corridor function. Therefore, they ensure sufficient potential customers to a transfer point.
Given the criteria, crossings of road and rail infrastructure are looked upon as potentially interesting locations for developing a transfer point. There are 1012 intersections between the rail and road network in the search area. However, only 295 are located within 500 meters of a highway.
These 295 locations are placed in a CENTERS-file. Each location has four different values, representing the accessibility for different user groups. The way in which they are calculated is described in the previous paragraph. Each value is divided by the average of all locations of that particular user group. These weighted values of the four categories are combined to create a single value; the multi modal accessibility value. This is done for all of the 295
locations. The following table shows an example of the database operations,
The research led to an ambiguous result describing the best accessible locations. Each user group gives a different perception of the best accessible places in the search area. For the users with
their origin in Utrecht, the best locations are situated as close as possible near Utrecht. For the users with an origin outside the area, locations near areas with high population densities score well.
These are situated near Amsterdam, Rotterdam and Utrecht. Utrecht is selected due to its central situation in The Netherlands. The mutual differences in locations between car and public transport are small.
Although an ambiguous result is obtained, some locations are spotted more frequently then others. This concerns the following locations:
• Utrecht: Westraven, Ysselstein, Lunetten, Driebergen, Bunnik • Amsterdam: South-Amsterdam,
Southeast-Amsterdam,
• Rotterdam: Rotterdam-Alexander.
4. Distribution of transfer points.
The success of a transfer point depends on many factors. Good accessibility is an important one, sufficient travellers using a transfer point is another. The flow of travellers passing through a transfer point must be large enough to ensure proper functioning and use. Therefore, when several transfer points are planned in a certain area, it is useful to study the competition between them. This is because, the objective is to create a balanced distribution of transfer points over the area.
A Location-Allocation model is used to determine the optimum distribution of facilities over the area. The model selects a given number of facilities from a set of potentially interesting locations. The set consists of the 100 best accessible locations from the accessibility analysis.
Table 1
N o d e *
40577 40566 40515
example table with potential values,
Accessibility Car ext. 5115.64 5118.20 5123.35 Car int. 437.71 438.61 440.43 Public trans. ext. 3093.10 3093.95 3094.80
weighted values and the sum of the vali
Public trans. ext. 6290.61 4283.05 3279.67 Weighed Car ext. 1.026 1.027 1.028 Car int. 2.252 2.256 2.266 Public trans. ext. 0.636 0.636 0.636 jes Public trans. ext. 34.663 23.601 18.072 Sum 38.577 27.520 22.002
Figure 1 the 10, 50 and 100 best accessible locations in the area (black, green, light green)
The figure above shows a selection of the best accessible locations.
The 195 locations with a lower accessibility value are excluded. This accelerates the Location-Allocation analysis.
Several analyses have been carried out to gain a thorough insight in the usefulness of the Location-Allocation model. The set of the 100 locations and the MINDISTANCE method form the basis
for each analysis. The distinction is made by using:
• different transport networks (road and rail network);
• different target groups (internal and external users) and
• a different number of transfer points to be developed.
Most of the analyses use the road network. Transfer points focus on road
Tabel 2 different analyses carried out
a Internal and external b Internal and external c Internal and external d Internal and external e Internal and external f Internal g Internal h External i External
users. They should leave their cars at the transfer point and travel further to the centre by public transport. Thus, most users of transfer points will approach by car. The table below shows the different analyses. The analyses with both user groups (a, b, c, d and e) show a decentralised distribution of transfer points. The locations are at the border of the research area. This is caused by the MINDISTANCE method and the large number of users living outside the research area. Analyses h and i show the same results more extremely. In these analyses the potential users coming from within the research area are not taken into account. This "pulls" the transfer points even more to the borders. Analyses f and g show the opposite results. The locations are as close to Utrecht as possible.
Although, the Location-Allocation model shows a balanced distribution of transfer points over the area, one has to keep in mind that several factors influencing the location choice are not taken into account. The fact that the transfer point is not the final destination is an important one. Of all the analyses, analysis c is the most realistic one. Developing a transfer point is an expensive operation. Thus it is not possible to develop as many as one may wish. Five transfer points is a realistic assumption. The following
Car Car Car Car Car Car Public transport Car Public transport 10 7 5 3 1 5 5 5 5
illustration shows the 5 locations with their catchment areas.
Figure 2 result Location-Allocation, car, internal + external, 5 transfer points including catchment areas
The catchment areas show the fastest reachable transfer point from different zip code areas. The catchment areas provides an insight in the number of potential users for a specific transfer point. The total number of inhabitants of the zip code areas in a specific catchment area are summarised. A more sophisticated method is to use an origin-destination matrix. An origin-destination matrix gives the number of people that travel from a
zip code area to Utrecht or to the transfer point.
Finally, analysing catchment areas has an important value for companies which are looking for a suitable location for business. Especially when looking on a National level, the used method in this study is an interesting option. For example, multiple stores can benefit from a good coverage in The Netherlands.
5. Functioning of transfer points.
To what extent can a movement via a transfer point compete with public transport and the car? The calculation of travel times for different means of transport is the key method in this analysis. A comparison of these travel times provides an insight in the effective functioning of the transfer points. In this study, the choice for a specific means of transport is entirely based on travel time. However, in reality, the choice for a means of transport depends on more factors such as expenses, comfort etc. In this research, these are not considered. It is assumed that every traveller chooses the fastest means of transport.
Two sets of transfer points are used to determine the travel time via a transfer point. The first set is called "Theory-locations". The locations in this set are based on the accessibility analysis and the Location-allocation model. It consists of locations that were frequently spotted in these analyses. The second set is called "Practice-locations". It is based on recommendations of the project team "Transfer points central Netherlands". The set consists of existing transfer points
(mostly park and ride facilities) and locations where future transfer points are planned.
The following assumptions regarding public transport are made to calculate the travel time:
• The average speed of public transport is 50 km / h . Stops are taken into account.
• Zip code areas within 5 kilometres of a railway station are linked up with public transport. Areas further away are not.
• Time needed to reach a railway station is not taken into account. • Time needed to transfer is not taken
into account.
A digitalised version of the Dutch road network is used to calculate the travel time by car. Of the available systems, the basic network used by the Dutch Department of Traffic and Transport suits this research best. The network is up to date, complete and dense. Secondly, the version has a detailed description of the car speeds on different road sections. These car speeds correspond to the values which are measured in reality. With the car speeds, the travel time for each road section is calculated. This makes it suitable to use in this GIS analysis.
The fastest means of transport for each zip code area is visualised on a map. Each zip code area gets a specific colour. The colour represents the fastest means of transport which results from the comparison; red for the car, green for public transport and blue for a movement via a transfer point. The figure on the next page shows the map for the transfer points on the Theory-Locations.
The car is by far the fastest means of transport for most of the zip code areas, as can be seen on the map. This is also the case for the Practice-Locations. The main reason is the low speed of the train compared to the speed of the car. The average speed on the Dutch highways described in the digitalised road network
Figure 3 transfer points on Theory-Locations, choice for means of transport based on minimum travel time
is 100 km/h. This is twice as fast as public transport. The average car speed drops in the city because of traffic lights and speed
limits. Therefore public transport is more
competitive in the city. Travelling via transfer points is merely in a few cases interesting. However, the analysis does show which of the Practice-Locations have the most potential for the transfer.
As mentioned before, the travel time depends on many factors. By changing the assumptions that have been made, the effects of changing circumstances can be explored. Two questions have been researched. What is the effect of traffic jams on the choice for a means of transport? Secondly, what is the effect of an improvement of public transport?
To simulate congestion, the car speed on the highways in the research area is reduced by 50 %. The train speed remains unchanged. With the new assumptions, the travel times are calculated again. The results show that a journey via a transfer point becomes an
attractive alternative in a situation with congestion.
To simulate an improvement of public transport, the train speed is increased from 50 to 100 kilometres an hour. The train speed in the first analysis is on the low side. In practice, the average speed of a train is approximately 75 km / h. Stops are taken into account. To visualise the impact of an improvement, 100 km / h is used. The results show that for all the areas that are properly linked to public transport, the train provides the fastest means of transport to reach Utrecht. For the other areas, the car remains the best alternative. Transfer points are hardly used.
6. Conclusions
In this study, the choice for locations to develop transfer points in the Utrecht Region have been explored. Three analyses using a geographical information system were carried out. The question remains if it is useful to employ a GIS to determine the locations of transfer points. In other words, what is the practical use of a GIS-analysis? Based on the results of the separate analyses, this question can be answered.
1. Quantifying the accessibility of possible locations for transfer points.
If competition is not taken into account, then the method provides interesting results. For example, when only one facility is needed. In case several locations are situated close to each other, competition forms a vital threat to the functioning of these facilities.
In this analysis, all the inhabitants of The Netherlands have been taken into account. Better results can be obtained when a selection of The Netherlands is used or a specific target group. Origin-destination matrices can be used to provide information regarding actual
traffic flows. In that way, the number of users is calculated more precisely.
2. Optimising the distribution of transfer
point over the research area.
A Location-Allocation model determined the optimum distribution of transfer points over the area. In this way competition has been avoided. All zip code areas are allocated to a specific transfer point; the nearest one.
However, not all the locations are ideal places for developing a transfer point. Some of the identified locations are situated far from Utrecht. In this way, cities within the research area (in the vicinity of Utrecht) are badly facilitated. Furthermore, the tie of a transfer point with Utrecht becomes unclear when it is located northwest of Amsterdam. This does not necessarily have to be a problem since the transfer point can function as an origin transfer point'. The main advantage is that the majority of the journey is done by public transport. This has the maximum effect on reducing the number of car kilometres. Besides, some locations can function as an origin transfer points as well as a destination transfer point and vice versa.
3. Comparing the travel time for different means of transport.
Although, many assumptions have been made to make this analysis possible, the analysis of travel times provide good insights in the functioning of transfer points. The results give a good idea of the proportions between the travel times of the different means of transport. The analysis can be improved when the assumptions are sharpened. E.g. the time needed for finding a parking space and for transferring should be taken into account to make the analysis more realistic. Secondly, the traveller's choice
' Transfer points can be located near the origin or near the destination; origin and destination transfer points.
for a means of transport is not only based on travel time, but on more factors like travelling costs and comfort. In future studies, these factors need to be taken into account as well.
The practical use of the results arising from these analyses should be seen as supporting or directional. A GIS can play a role in quantifying characteristics of locations and visualising the effects of government policies. However, the necessary data for developing a realistic model is often difficult to obtain. Thus, assumptions and simplifications have to be made. Secondly, not all the aspects involving the locations of transfer points can be investigated using a GIS, e.g. factors such as the current spatial policy or the political climate. Therefore, a GIS analysis should not be the sole determinant for decision making. But it definitely has its value in supporting decisions regarding transfer point
locations.
References
[1] Arcdoc, the on-line guide for Arc/Info.
[2] ArcView, on-line help function.
[3] Buck Consultants International
(1998): Transferpunten
Midden-Nederland, fvveede concept, Studie naar
de ruimtelijk-economische invulling van transferpunten, Nijmegen.
[4] Hakimi, S.L. (1965): Optimum
distributions of switching centres in a communication networl< and some related graph theoretic problems,
Operations Research, part 13, page 462-475.
[5] Hilbers, H.D. & Verroen, E.J.
(1993): Het beoordelen van de
bereikbaarheid van lokaties, TNO-rapport
INRO-VVG 1993-09, TNO Inro, Delft. [6] Ministry of Transport, Public Works and Water Management (1993):
Transferia, resultaten van voorbereidinsfase, uitwerking concept en
beleid, Projectgroep Transferia,
Bouwdienst, Directoraat-Generaal Rijkswaterstaat, Utrecht.
[7] Ministry of Transport, Public Works and Water Management (1996):
Nota samen werken aan bereikbaarheid
Directoraat-Generaal voor het Vervoer, Directie Individueel Personenvervoer, 's Gravenhage.
[8] Ministry of Transport, Public Works and Water Management (1998):
Meerjarenprogramma Infrastructuur en Transfport 1999-2003.
[9] Réveile, CS. & Swain, R.W. (1970): Central facilities location, Geographic Analysis, part 2, page 30-42. [10] Teware, V.K. & Jena, R.W. (1970):
High school location decision making in rural India and location allocation models, Spatial Analysis and location
allocation models, Eds Ghosh, A. & Rusthton, G., Van Nostrand Reinhold Company, New York, page 137-162.
Transfer point Schiedam
H.M. van Wingerden
Abstract
Former studies about transfer points have resulted into a network of transfer points divided over The Netherlands [2, 3J. Schiedam is one part of that network. In the present study, the transfer point in Schiedam is analysed at a more detailed level and develops these investigation results into possibilities of developing a transfer point in Schiedam.
At first, the road users belonging to the future target groups are identified. A distinction has been made between means of transport, purpose of the travel and traffic intensity during the day. Subsequently, the origins and destinations of the potential users are determined. The transfer point of Schiedam has a dual function, which has to be taken into account. The transfer point has an origin function for travellers coming from Schiedam and its environs. Secondly, it has a destination function for travellers going to Rotterdam Region. This knowledge has been used to estimate the expected number of users which further helps to determine the capacity of the transfer point.
Secondly the potential locations (at the local level) which can be considered for the development of the transfer point have been studied. Two locations in proximity to the railway station Schiedam Central proved to be suitable. A multi criteria analysis (MCA) following this identified the location behind the railway station (location Schieveste), as the best option.
Further, the possibility of the realisation of the transfer point in combination with the development of office space and other business activities has been probed. This is in accordance with the desire of the municipality of Schiedam for developing office space at the same location. A spatial design which has been developed also reviews presence of
adequate parking space. This has been followed up by an investigation into the way in which the area can be linked up to the Dutch road network.
The research concludes that the development of a transfer point in Schiedam should definitely be looked upon as a serious option. However, in order to achieve an integrated planned development, the transfer point should be incorporated in the regional and local traffic and transport policy. This must prevent developments that will undermine the use of the transfer point.
1. Introduction
Various studies have been undertaken to exemplify the manner in which transfer points can establish a link between the car and public transport system. To begin with, different types of transfer points have been defined. Next, the most suitable locations for transfer points have been investigated. These studies have resulted in a large number of potentially interesting locations. From this large numbers, a set of locations with a high potential to become successful was extracted. And developed into a network of transfer points [2, 3]. The network developed aims to prevent an overcapacity of transfer points around the major cities. Most of the transfer points can be found in the congested areas in the west of The Netherlands. Railway station Schiedam Central is such a location with a potential to succeed.
T^gningen I f c - ^ é ^ \ J * ^ * / i'-Stompwiik'''' v ' " • Rijnwoude Zoetermeer Nootdorp Kethel \ / # \ r w . ^ * ,Piinkker . ' * * ' ^ ^ % \ . , * « ^ f OudeLeede Bergschenhoek f % Heijplaat •pernis • J., Ktlmpei a .'.if fiS. Vondelingenplaati • , jV taiek ....sgf^'^'-'^-- * V i i e t ~ " ^ : ^ J o b g v l e t ^ Spijkenisse Hekelingen ^-1— »4 Bolni \ y '^^iRidderkerk, .Rhoon •''•^Smrshpék"BanS=^ïfcl-*|Bk ^H T1 Schiedam T2 Plaspoel polder T3 Nootdorp T4 Moordrecht T5 Vaan plein
I
«and ?Figure 1: current situation
P'B^-^
:lig|||k 1 %.
Heerjansclam
^ • - ^ d ^ ^ ^ d ' ; H e i n e n o o r d / ... sHeari
Therefore, Schiedam has been incorporated in the developed network.
The town of Schiedam lies in the Randstad^ between Vlaardingen and Rotterdam. The highway A20 crosses the city. This highway is currently an important link in the road network of the Rotterdam Region. The railway station Schiedam Central has an important function for travellers between Amsterdam and Hoek van Holland.
Just after Schiedam Central, the railway line coming from Rotterdam is divided in
^ T h e R a n d s t a d is t h e u r b a n i z e d w e s t o f T h e N e t h e r l a n d s .
two lines - one going to Amsterdam and one going to Hoek van Holland. This transfer function which the station already has for public transport travellers, is only expected to increase in the near future. The station will be linked to the metro line coming from Rotterdam Marconiplein, passing through Schiedam and going to Spijkenisse. These features (presence of a railway station, available different means of public transport and proximity to major road network) make Schiedam an ideal location for developing a link between the car and public transport system.
The objective of this study is to further investigate the possibilities for developing a transfer point in Schiedam. The following subjects have been included in the discussion which also determines the structure of the study: • User groups: Whether or not a road
user makes use of a transfer point depends on various factors (section 2).
• Type of transfer point. The transfer point in Schiedam functions as an origin and a destination transfer point (section 3 and 4).
• Number of road users. The total number of users is determined in section 5.
• Location choice. At which specific location can the transfer point be developed? Section 6.
• Spatial design. The transfer point has to be integrated into the surrounding physical context as well as in the development plans of the municipality of Schiedam (section 7).
2. Users of transfer points
Clearly, not all road users can be counted amongst the future target group. Lorries and trucks are tied to their vehicles because of their loads. Thus they cannot transfer to public transport. Mainly drivers of passenger cars belong to the group of possible users of transfer points. Besides the distinction between different types of vehicles, a distinction is made between different motives for the trip. The two most important motives are commuter traffic and social recreational traffic.
The purpose of the trip together along with the traffic intensity on the road network is of a major influence on the willingness of road users to use a transfer point. In this study, the day is divided into peak periods and off-peak periods. The chart below shows the course of the traffic intensities during the day. The
peaks in the morning and evening hours resulting from commuter traffic are clearly visible. The small peak around midday is caused by employees who lunch at home. In the afternoon and the evening the social recreational traffic increases. 1995 Q remaining • shopping • recreation B txjsiness • commuter traffic O C M ^ ( 0 « ) O e M n < 0 ( 0 O C > j
hours of the day
Figure 2: traffic intensities during the day (cumulative)
Peak hours
Motorists in the morning peak hours (06.00 till 10.00 hour) form an important and potential user group. In this period 25 7o of the total number of movements in the day is made [5]. On the considered roads around Schiedam, 90 % of the vehicles are passenger cars during these hours [1]. The motives of the trips by the motorists are shown in ffgure 3. Motorists without a permanent and regular work address are not considered as possible users of a transfer point since this is an irregular and dynamic group. Also, these road users usually depend on their cars for the daily activities of their profession.
From the evening peak hours no new.
users are expected. These movements are mainly made by motorists who made the same movement in the opposite direction during the morning peaks. Therefore, the motorists who are willing to transfer have been taken into account
Morning peak Off-peak hours
m 70 % permanent work address
• 10 % no permanent work address D 5 % social recreational
D 15 % remaining
m20% permanent work address
• 15 % no permanent work address D 50 % social recreational
D 15 % remaining
Figure 3: % depicting purpose of the trips during peak hours and off-peak hour.
Off-peak hours
Another large group of possible users of transfer points are found during the off-peak period from 10.00 till 16.00 hour. Around 40 % of the total number of movements over the day is made during this period [5J. However, the target group is smaller than during peak hours - 80 % passenger cars [11]. Unlike during peak hours, congestion on the roads is not the main reason for using a transfer point since there is hardly any congestion. It is the parking problems at the place of destination and congestion in the local road network (in the city centres) which gives cause for using transfer points during these times.
The number of transfer point users due to traffic during evening hours is negligible. Lower frequencies of public transport make transfer points less attractive during these hours, especially late in the evening. These are mostly the times when people return home from visits to friends or family.
To summarise this section, two user groups have been identified: commuter
traffic in the morning peak hours and social recreational traffic during daytime. Despite the advantages the transfer point can offer, not every car user is willing to transfer to public transport. Therefore a model describing the choice for a means of transport is made. Based on the model, around 15 % of the mentioned target groups are willing to transfer.
3. Destination function
The transfer point in Schiedam will function as a destination transfer point for Rotterdam and its environs. For motorists coming from Vlaardingen and Schiedam, this transfer point will also operate as an origin transfer point. A clear distinction between these functions is necessary since the origins and destinations of the users differ.
For the destination function, the number of users depends on the presence of other transfer points in the surroundings. Travellers who come across more transfer points on their journey are offered a choice. The congestion in the road network is one factor influencing that
choice. The final destination point is another. The following section looks into the directions from which Schiedam could expect travellers.
Travellers from the northern direction have a choice between transfer point Plaspoelpolder and Schiedam (figure 1). In case of congestion on the A13, a journey to Rotterdam is faster by public transport than by car. Thus, the car user will choose to transfer at Plaspoelpolder. Outside peak hours, a transfer at Schiedam is more effective in terms of travelling time. Secondary, motorists would want to park their cars closer to their ffnal destination. Thus outside peak hours Schiedam can expect users from the North.
Hardly any travellers are expected from the south. Motorists from this direction going to the Rotterdam Region will use transfer point Vaanplein. Vaanplein is better situated for these travellers. Travellers with a destination to the north of Rotterdam will use transfer points more closely situated to their final place of destination. Again, from the East, few users are expected. Transfer point Moordrecht is of more importance for these travellers. A reason for travellers to consider a movement via transfer point Schiedam lies in local congestion and poor parking facilities in Schiedam and its surroundings. However, traffic inquiries show that only a few motorists coming from the east are finally heading to the western regions of Rotterdam that are linked by the Schiedam metro line. Therefore, for these travellers it is not very useful to transfer and take public transport in Schiedam.
From the west, Schiedam has no competition from any other transfer point. Therefore, future users of the Schiedam transfer point are expected from the northern direction travelling on highway A13 and from the western
direction travelling on highway A20. The figures on the next page show the origins and destinations of the motorists from the A20and A13.
4, Origin function
In this section, Schiedam and Vlaardingen are divided into two sectors in order to investigate what the origins and destinations are for travellers from this area. Travel time factors determine from which sectors users can be expected. They show the relation between the travelling times by car and by public transport for a specific sector.
Travel time factor = travel time public transport/travel time car
The travelling times for both means of transport consists of several components. The components differ for a movement by car or by public transport. The schematic representation below shows the different components.
Preliminary Trip time After transport Pre Waitin Trip Transf Trip After
It should be noted that in this research only the movement between origin and transfer point Schiedam is analysed. In reality, travellers consider the total movement. However, no information about the final destination of the travellers was available. Secondly, the final points of destination vary tremendously. Thus, it is not possible to determine the travelling times of all these separate movements.
Before calculating the travelling times for public transport, it is necessary to know what travelling alternatives are available for inhabitants to choose from. To access this information, ffeldwork was done in the different sectors. This also involved, studying the time-tables and short term development plans of this region. For the
available alternatives, the travelling times for the different sectors have been calculated. Time schedules of local public transport were used and assumptions were made with regard to waiting times and pre and post transfer times.
Figure 4 origins and destinations
Amsterdam 0.5% Wesüand 80% Europoort 8.5% Zuidhollandse eilanden 0.5% Hague 10% Delft 0.5% Amsterdam 0.5%
4 ^
The Hague 2% Delft 0.5% • Pijnacker2% • ^ ' / yiardingen Schiedam 11% 22°/i >^ Gouda 2.5% Capelle 2% Utrecht 4% Dordrecht 6% Gorinchem 6% Zeeland 2% ORIGIN DESTINATIONRoad survey A20 between Maassluis and Vlaardingen
Amsterdam 16 % The Hague 53% ORIGIN Westland 1.5% Europoort 3% Zuidhollandse eilanden 6.5% Zeeland 3%
Contour lines have been used for calculating the travelling times by car. These contour lines bind the areas that can be reached from the Schiedam railway station within respectively 5, 10, 15 and 20 minutes. Estimations have been made for the areas in between the contour lines. Subsequently the travel time factors have been calculated for the two identified sectors of Vlaardingen and Schiedam (table 1).
Tablel 1 travel time factors
Vlaardingen Holy Vlaardingen West Vlaardingen Centrum Schiedam North Schiedam Nieuwiand Schiedam Centre Schiedam South Schiedam East 33 35 30 26 21 19 23 17 20 24 21 16 14 12 15 11 1.7 1.5 1.4 1.6 1.5 1.5 1.5 1.5 Public transport is considered competitive when the travelling time via this means is 1.5 times the travelling time of the car [7]. As the factor increases the competitive position of the public transfers decreases. This results in a lower number of public transport users. In this study, the transfer point at Schiedam is useful for the sectors with the travel time factors bigger than 1.5. Therefore users are expected from Schiedam North and Vlaardingen Holy. These areas lack a good link to the public transport network. So the inhabitants would probably prefer to use the car initially. At transfer point Schiedam they can hook on to public transport.
5. Number of users
To calculate the expected number of users, this study has used traffic census
along the A13 and the A20 [1]. With this data the average amount of journeys over a working day have been determined. After this it becomes necessary to distinguish the part of these journeys made by motorists belonging to the group of possible users? Earlier in this study a distinction has been made between origin and destination function. This distinction will be retained.
Furthermore, it is important to acknowledge that road users will have to get used to the concept of transfer points. Therefore two scenarios have been developed. In the first scenario the habituation is expressed by the willingness to transfer. In the second scenario, the willingness of a motorist to travel via a transfer point is lower.
Number of users from destination function (A13 and A20)
The target group during the morning peak is calculated by using the percentages given in section 2 and the traffic census. An origin-destination matrix was used to distribute the vehicles over the concerned origins and destinations. This is necessary because the transfer point in Schiedam does not serve all the connections (section 3) that operate over the A13 and A20. The relevant connections for transfer point Schiedam are determined by using an inquiry.
From these motorists only a percentage is actually willing to transfer. Different percentages have been used. In the first instance, the willingness to transfer differs for the two scenarios mentioned above. Secondly, it is studied whether the transfer point is along the route or if a small detour is required. Even a small detour can lead to gaining of time. This depends on the congestion in the main road network. However, the willingness to transfer of road users who need to make a detour is smaller than for road users who do not. The percentages used
vary between 5, 10 and 15 %. With these percentages, the expected number of transfer point users during the morning
peak has been determined.
The users during the off-peak hours are determined in the same way. But different percentages (passenger vehicles, travelling motive and willingness to transfer) have been used. Besides, the origins and destinations are different.
Number of users from origin function The number of users in this case has been calculated in the same way as for the destination function. The distinction between peak and off-peak hours remains the same. And so do the percentages for passenger vehicles, travelling motives and willingness to transfer. However, Schiedam as an origin transfer point has different origins and destinations. Schiedam North and Vlaardingen Holy are the origin areas (section 4). The direction Benelux tunnel and the Region Rotterdam are the destinations. The expected number of transfer point users is calculated by multiplying the number of passenger cars with the respective percentages.
The total number of expected users is established by adding the destination function and the origin function. The total number of users varies between 1380 and 785 per working day for respectively the first and second scenario (table 2 and 3).
Table 2 total number of cars, first scenario
Peak hours 615 340 965 Off-peak hours 285 130 415
1380
Table 3 total number of cars, second scenario
Peak hours 365 210 575 Off-peak hours 140 70 210
785 With the number of users, the parking capacity can be calculated. The required parking capacity will be smaller than the number of cars arriving at the transfer point daily. This is because not all cars are parked at the transfer point at the same time. The required parking capacity is determined based on the turn-over which indicates the number of cars using one available parking space. The turn-over is different for different user groups. Social recreational traffic has a higher turn-over (3) than commuter traffic for a fulltime job (1). In the first scenario, a parking capacity for 955 cars is required. In the second scenario, the required capacity is 560 cars.
6. Location choice at local level
Around the existing station of Schiedam Central, various developments are taking place. A new metro line is being developed, the station square is being reorganised and the station is being redesigned. Besides the plans of the municipality of Schiedam, the Dutch Railroads plan to double the number of trains between Schiedam and Delft in the future. These already planned developments lead us to the question of where is the potential space available for realising a transfer point in Schiedam. The following criteria have been used to find suitable sites:
1. suitability of site: sufficient surface, current functions;
2. situation with respect to the highway;
3. situation with respect to the railway station.
: Centre Schiedam
Figure 5: transfer locations
The number of locations emerging appeared to be limited. Two sites meet the criteria (figure 5). A multi criteria analysis (MCA) has been used to determine the best location. In an MCA the alternatives are evaluated based on several criteria. A distinction is made between the main and sub criteria. Table 4 on the following page shows the MCA. The criteria used can be seen in this overview. The importance of the different criteria is determined by using the matrix method in which all the criteria are compared in twos. The more important one of the two gets a 1 and the other a 0. The horizontal addition sum gives the importance of the criterion. Costs and the linkage to the road network appeared to be the most important criteria.
Before executing the MCA, the criteria are valuated. To obtain an objective image of the value of the criteria,
different persons have valuated the criteria independently. The average of these values is used. Then the same persons have performed the MCA for the two sites.
From this MCA, location Schieveste comes through as the better location for developing a transfer point. It is mainly the lower initial investments and the better possibilities for expansion which makes Schieveste the better site.
7. Spatial design
The multi criteria analysis brought location Schieveste out as the best location for developing a transfer point in Schiedam. However, this does not comply with the development plans of the municipality. The municipality of Schiedam plans to develop commercial office space at this location. Office space would stimulate employment in the
Table 4 MCA
Accessibility 2.9 External 5 of the area internal 5
Costs 2.4 Initial 4 Exploitation 6
Expansion 1.9 Station 4 possibilities Transfer point 6
Fit in of the 1.5 City 4 plan development ^ plan Surroundings Development 0.8 Surrounding 4 nuisance areas ^ Traffic Development 0.5 Preparation 5 '^"^^ Transfer point 5 10
service sector. This is a sector that lags behind in Schiedam.
Since the location has opportunities for both functions and both functions can strengthen each other, an integration of these seems natural. However, this needs further investigation. To make a combination possible, the ground level is Within the new location, the transfer point and its parking spaces must be developed as close as possible to the existing station-building. The crucial factors for the transfer point would be the maximum walking distance (125 m.) and the available pedestrian tunnels (figure 6). In the current situation there are two available. The one in the east (green) is not yet developed.
14.5 7.5 108.75 4.5 62.25 14.5 4 58 7.5 108.75 9.6 8 76.8 3 28.8 14.4 5 72 5 72 7.6 5 38 7.5 57 11.4 7 79.8 3.5 39.9 6 3 18 9 54 9 6 54 8 72 3.2 4.5 14.4 6 19.2 4.8 4 19.2 5 24 2.5 8 20 3 7.5 2.5 6 15 6 15 100 573.9 563.40
artificially raised 6 meters to level the department platforms of the trains. The space under the new ground level can be used for the parking space for the transfer point and the offices. There is enough space in this raised part for two parking levels. On top of the new ground level, offices and facilities can be developed.
For situating the office space and the associated functions, the area is divided into four sections (figure 6). In section 1, office space is already developed. For the other three sections a spatial design has been formulated. In the second section it is possible to reserve space for associated functions, which can be combined with office space and designed for a large number of visitors. Congress centres, restaurants, educational facilities and
••••V /^r>-'' ..;
X ^ -
h:l
Deelgebied Figure 6 areas •:•••,-•.•' '••.•••.-Xmap of the area and its sub there is enough parking capacity in all sections.
social cultural institutions are possibilities to be considered.
To find out whether there is enough space available under the new surface level to meet the parking needs, a comparison is made of the required space and the available space. Initially, the required space is determined for the second scenario (560 cars) and a parking norm of 1 parking space per 75 m^ office space. From the given conditions, it is determined that in case of two pedestrian tunnels, there are not enough parking spaces in section 2. However, in case of three tunnels, the parking capacity is sufficient.
Likewise it is investigated whether or not there will be enough parking places in the future. This concerns not only a situation with a stricter parking norm (1 place per 150 m^ office space), but also more users after the habituation period (scenario 1). In the case where the eastern pedestrian tunnel is realised,
Besides the parking facilities, the external connectivity of the area is investigated. It is studied whether a direct linkup of the transfer point with the A20 is possible. This helps to minimise the transfer time. From a technical point of view, direct linking-up is possible. However, from financial and social point of view it is not optimal. It would involve a radical change in the current environment. Therefore, the transfer point will have to use the existing exit roads. Different alternatives have been further studied.
The final point of concern in the study is to understand what extra functions the transfer point can fulffl. During night hours and in the weekends the transfer point is hardly used by the identified target groups. Thus during these times this space is available for compatible functions.
The following functions have been identified:
• urban parking facility for visitors of Schiedam;
• parking facility for neighbouring residential quarters;
• parking facility for neighbouring business parks;
• stabling facility for corporation and regional buses;
• stabling facility for trucks from the Rotterdam harbour.
No distinct choice is made for one particular extra function. It should be noted that parking facilities would lead to extra costs resulting from extra hours of opening. The stabling facilities will also have a great impact on the design of the parking space e.g. heights and turning circles which would impact the costs too.
8. Conclusion
In this study, the transfer point -Schiedam is investigated. This aim is to determine whether the development of this transfer point is useful. The main conclusion which can be drawn from the analysis of the situation is that the development of a transfer point in Schiedam holds many positive implications and should definitely get serious attention form the planners. As can be deducted from the estimated amount of users, the transfer point offers a significant contribution in reducing the problems related to increasing car use.
A spatial design has been made as part of the study, to integrate the transfer point into the development plans of the municipality of Schiedam. This plan involves the combination of the transfer point with the development of office space at the location Schieveste. The analysis showed that there is sufficient space to meet the presence and parking needs of both functions. Although, the pedestrian tunnel located at the east of
the area needs to be built to establish a balanced distribution of cars over the area. A road parallel to the railway track coming from the reconstructed junction, Giessenplein, links the transfer point to the highway A20.
A vital condition for developing the transfer point is to include the development of the transfer point in the overall policy concerning traffic and transport. In this way, counterproductive measures and decisions can be avoided. E.g. of such measures could be the development of extra parking space at the destination side of Schiedam or the realisation of new road connections which could result in making the location of the transfer point Schiedam adverse.
References
[1] A W Transport Research Centre (1997): Traffic Data Rijkswaterstaat 1997, The Hague.
[2] Binsbergen, ir. A. van, Egeter, ir. B., Heringa, ir. E. & Schoenmaker, ir. A. (1992): Tranferia, lokatiekeuze en raming
van gebruik. Hoofdrapport, Delft
University of Technology, Faculty of Civil Engineering, Delft.
[3] Binsbergen, ir. A. van, Egeter, ir. B., Heringa, ir. E. & Schoenmaker, ir. A. (1992): Tranferia, lokatiekeuze en raming
van gebruik. Uitwerkingsrapport, Delft
University of Technology, Faculty of Civil Engineering, Delft.
[4] Clerkx, ir. W.C.G. & Jansen, ir. G.R.M.., (1990): External relations
between the four major cities in the Randstad, Delft.
[5] CPB Netherlands Bureau for Economic Policy analysis (1996): Cars in
the Netherlands, CPB, The Hague.
[6] Kropman, ir. J. & Kattelaar ir. H. (1991): Files in de Randstad, oplossingen
op het spoor?, Nijmegen.
[7] Kropman, ir. J. & Kattelaar ir. H. (1993): De betekenis van de
[8] Ministry of Transport, Public Works and Water Management (1994):
De ruit van Rotterdam, ontwerpvisie,
Directie Zuid-Holland, The Hague.
[9] Public Works Department
Schiedam (1991): Development plan
location Schieveste, Schiedam.
[10] Region Rotterdam (1995):
Regional development plans for traffic and transport, Rotterdam.
[11] Schram, R., (1997):
Agglomeratietransferia (Agglomeration Transfer points), Delft University of
Technology, Faculty of Civil Engineering, Delft.
Transferring faster in Delft
Network analysis as an instrument for designing public transport
stations
Prof. Ir. F.M. Sanders
Ir. E. van Duin
Abstract
The quality of a transfer not only depends on the accurate measures in which time schedules are tuned. But equally important is the spatial design of the station and the adjoining areas. The Delft University of Technology has developed a method to investigate the effects of the design on the transfer times to the level of independent transfer relations. With the method the effects of changes resulting from the design can be analysed.
To calculate the trip times within the station area, the Grafen theory is used. In this theory the concerned area is represented by a network. The important origins and destinations in the area are modelled as points. Lines between them represent the possible routes. Weights - like time or distance - are linked to the network. This schematisation makes it possible to analyse the problem systematically. A street plan of the station and its surroundings is needed to execute the analysis. The model is then developed by using AutoCAD and the computer language AutoLISP. The strong graphical basis of AutoCAD makes it possible to analyse different designs easily.
The model is tested on the recently reconstructed station of Delft. In this study, different alternatives in spatial compositions are analysed. They are compared to each other and with the current situation. The model has revealed several measures of possible improvements to further reduce the transfer times at station Delft. However, heavy investments are necessary to realise these improvements.
The research concludes that the model is definitely suitable for comparing different alternatives to the spatial composition of stations. However, the gathering and the processing of spatial data and the traveller flows is relatively laborious. Therefore the method is mainly suitable for complex spatial design problems with many variables.
1. Introduction
Chain mobility succeeds or fails with a perfect transfer. The quality of a transfer does not only depend on a good attuning of the time schedules. Equally important are the connectivity of the station and the composition / spatial design of the station. A better design will reduce the transfer time. The Delft University of Technology has developed a method that provides insight in the influence of the design on the transfer time. This involves a network analysis.
Since new transfer points are being developed and existing stations are being redesigned, it is useful to consider the time which the users by necessity have to spend in these locations. The transfer time is an important factor in determining the quality of a transfer point. This not only concerns the transfer time from train to train, tram or bus. The before and after travelling by car, taxicab, bike or walking also needs attention. Basically this means a door-to-door analysis of the travel.
