University of Twente Student Theses


Estimating railway ridership : demand for new railway stations in the Netherlands

Hartholt, T. (2016) Estimating railway ridership : demand for new railway stations in the Netherlands.

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Abstract:Demand estimation for new railway stations is an essential step in determining the feasibility of a new proposed railway stations. Multiple demand estimation models already exist. However these are not always accurate or freely available for use. Therefore a new demand estimation model was developed which is able to provide rail ridership estimations. Main question of this thesis that will be answered is: How can the daily number of passengers of a new train station be forecasted on the basis of departure station choice and network accessibility? Aim is to estimate a demand estimation model which is valid for the whole of the Netherlands and focusses on proposed sprinter train stations. Factors determining total rail ridership Rail ridership can be determined by three main factors:  Built environment factors  Socio-economic factors  Network dependent factors Built environment factors are factors that describe the situation in the direct environment of the station. A subdivision can be made into station environment factors based on the three d’s as described by Cervero and Knockel-man (1997): o Density: Describing the amount of activities in the proximity of the station. This could be the e.g. number of jobs, number of students, shops or total population. o Diversity: describing the diversity of the activities that take place in the proximity of the station. o Design: variables describing the properties of a station (area) as a direct consequence of its design. E.g. the accessibility by bike (bicycle parking available), design of the station itself (architecture) or perceived safety. The socio-economic variables are mainly adding an additional layer to the density variables. They give additional information on for example income, employment, age, or car ownership which can increase of decrease the probability a person will use the train. Network dependent variables describe the connectivity of the station with the other station in the network. This can be described with variables such as frequency, number of lines, intercity service available or an accessibility index. Secondly, network dependent variables can also describe the quality of the potential feeder modes such as the frequency and number of lines for bus, tram and metro or the availability of a park & ride. In total 147 variables have been categorized and tested for their explanatory value.
Item Type:Essay (Master)
Faculty:ET: Engineering Technology
Subject:56 civil engineering
Programme:Civil Engineering and Management MSc (60026)
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