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Deventer, Netherlands

Van Oort N.,Goudappel Coffeng | Van Nes R.,Technical University of Delft
Transportation Research Record | Year: 2010

Ensuring reliable rail transit services is an important task for transit agencies. The effects of various terminal configurations on reliability of services were studied. The results could also be used for short-turning infrastructure. Short turning is a widespread measure to restore service after major disturbances; in many rail networks, additional switches are constructed to enable short turning. Calculations of the average delay per vehicle, regarding three main types of terminals, show the effect of frequency and occupancy time [determined by the distance from the switches to the platform (i.e., length of the terminal), technical turning time, and scheduled layover time]. The substantial effect of arrival variability and the number of lines using the terminal are also illustrated. With stochastic variables, delays will occur, although they are not to be expected in the static case. The best performance regarding reliability is achieved when double crossovers are situated after the platforms. Single tail tracks facilitating the turning process are acceptable only if frequencies are low, although they are often used in practice as short-tuning facilities for high frequency services. Occupancy time has a large impact on expected delays. This time can be minimized by designing short distances between switches and platform and tail tracks. Capacity management is not common in transit. However, increasing frequencies and large deviations force the consideration of limited capacity when planning infrastructure. If not, delays will occur, and additional measures will be necessary to solve them, which could be more expensive in the long term. Source


Van Oort N.,Goudappel Coffeng | Wilson N.,Massachusetts Institute of Technology | Van Nes R.,Technical University of Delft
Transportation Research Record | Year: 2010

Improving service reliability is becoming a key focus for most public transport operators. One common operational strategy is holding. Holding vehicles can improve reliability, resulting in shorter travel times and less crowding. In this paper both schedule-based and headway-based holding strategies in short headway services are analyzed. Despite significant attention to holding in the current literature, some important aspects were not previously researched. The main new variables are maximum holding time, reliability buffer time, and, in the case of schedule-based holding, percentile value used to design the schedule. A real line in the Hague (Tram Line 9), Netherlands, and hypothetical lines are analyzed with various levels of running time variability. Headway-based and schedule-based holding have the largest effect if deviations are high. When schedule-based holding is applied with a maximum of 60-s holding time, the optimal value of the percentile value becomes about 65% for all lines analyzed. When no maximum holding time is applied, schedule-based holding is more effective; there is no difference when the maximum holding time is set to 60 s. This research also shows the effect of holding on crowding: an average level of irregularity of 20% could decrease to 15%, enabling either smaller capacity slack or less crowding. Source


Friso K.,DAT.Mobility | Rijsdijk J.,Stadregio Rotterdam | De Graaf S.W.,Goudappel Coffeng
2015 International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2015 | Year: 2015

Mobile phone data are a new, unprecedented rich source to infer all kinds of mobility related information. The possibilities of mobile data are tremendous, i.e.: crowd images, frequencies of visits, foreign visitors, origin maps, traffic flows and OD-matrices can be generated locally, regionally and nationally and 24/7. The application fields are much broader than just traffic and transport: retail, city marketing, events and festivals, tourism, economy and security (crowd control) are other disciplines in which these mobility related data can generate new insights. Mobile phone data are helpful and cost effective in monitoring, evaluation, planning and policy-making [1]. In this paper we present an approach where mobile phone data is used for enriching the transport model of the region of Rotterdam. We obtained data from one of the 3 mobile phone providers in the Netherlands at which between 30% and 40% of the Dutch mobile phone usage is facilitated. This means, by accessing these data we have travel information of about one third of the total Dutch population. No other data source is known that gives travel information at a national scale at this high level. The raw data is processed into basic information which is subsequently translated into OD-information (Origin-Destination), where a destination is defined when a mobile device is longer than 30 minutes at a certain location. © 2015 BME. Source


Condeco-Melhorado A.,European Commission | Tillema T.,Van Alkemadelaan 448 | de Jong T.,University Utrecht | Koopal R.,Goudappel Coffeng
Journal of Transport Geography | Year: 2014

Network effects and spatial spillovers are intrinsic impacts of transport infrastructure. Network effects imply that an improvement in a particular link in a network generates effects in many other elements of that network, while spillover effects can be defined as those impacts occurring beyond the regions where the actual transport investment is made. These two related effects entail a redistribution of impacts among regions, and their omission from road planning is argued to cause the systematic underestimation of the profitability of transport projects and therefore the public financing they require. However, traditional transport appraisal methodologies fail to consider network and spillover effects. In this study we focus on the spillover impacts of two highway sections planned in the city region of Eindhoven, located in the Dutch province of Noord-Brabant, a region with traffic congestion problems. The new road infrastructure will be financed mainly by national government, the province and the urban region of Eindhoven ('. Stadsregio Eindhoven'), which consists of 21 municipalities. We measure the benefits of the additional links in terms of travel time savings and the accompanying monetary gains. The results show that important spillovers occur in those municipalities close to the new links. The province of Noord-Brabant will benefit the most. We also found important spillovers in the province of Limburg. This latter province will benefit from reduced travel times without contributing financially to the establishment of the analysed new road links. © 2013 Elsevier Ltd. Source


Wismans L.J.J.,Goudappel Coffeng | Wismans L.J.J.,University of Twente | Brands T.,Goudappel Coffeng | Brands T.,University of Twente | And 2 more authors.
Journal of Advanced Transportation | Year: 2014

Solving the multi-objective network design problem (MONDP) resorts to a Pareto optimal set. This set can provide additional information like trade-offs between objectives for the decision making process, which is not available if the compensation principle would be chosen in advance. However, the Pareto optimal set of solutions can become large, especially if the objectives are mainly opposed. As a consequence, the Pareto optimal set may become difficult to analyze and to comprehend. In this case, pruning and ranking becomes attractive to reduce the Pareto optimal set and to rank the solutions to assist the decision maker. Because the method used, may influence the eventual decisions taken, it is important to choose a method that corresponds best with the underlying decision process and is in accordance with the qualities of the data used. We provided a review of some methods to prune and rank the Pareto optimal set to illustrate the advantages and disadvantages of these methods. The methods are applied using the outcome of solving the dynamic MONDP in which minimizing externalities of traffic are the objectives, and dynamic traffic management measures are the decision variables. For this, we solved the dynamic MONDP for a realistic network of the city Almelo in the Netherlands using the non-dominated sorting genetic algorithm II. For ranking, we propose to use a fuzzy outranking method that can take uncertainties regarding the data quality and the perception of decision makers into account; and for pruning, a method that explicitly reckons with significant trade-offs has been identified as the more suitable method to assist the decision making process. Copyright © 2012 John Wiley & Sons, Ltd. Source

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