Recent Comments

    Posts tagged Big Data

    Operations of zero-emission buses: impacts of charging methods and mechanisms on costs and the level of service

    To limit global warming and strive for more liveable and sustainable cities, innovative zero-emission buses are on the rise all around the world. For now, only trolley, battery and fuel-cell electric vehicles can be classified as (on the pipe) zero-emission vehicles. Different charging methods, including different charging systems and power, are available to charge battery electric vehicles. However, scientific literature focused on the operation and charging scheduling of electric vehicles is scarce.
    In this study, a comparison of different applied charging methods for electric buses is obtained. A new ZE-bus station simulation method is developed to assess charging methods and charging regulations with regard to their impacts on costs and level of service.
    The shift to zero emission bus transport is meant for achieving more sustainable and liveable cities. However, this research concludes that this is involved with higher costs and passenger disturbances. The investment costs increase substantially. Benefits of electric operations, including vehicle propulsion cost savings up to 70 percent, are not able to compensate these high investments. (Slow) depot charging offers opportunities for operations on short distance lines. The depot location should be close to a bus station and additional fleet is required. In order to prevent fleet overcapacity, vehicles should be recharged with high charging power along the line, preferably at combined bus stations and terminals in order to prevent charging related delays. Dynamic/In-motion charging – still in its infancy stage yet – offers opportunities to prevent these delays due to combined charging and operation time.

    Find the TRB paper and poster of Max Wiercx HERE and HERE

    Robust Control for Regulating Frequent Bus Services: Supporting the Implementation of Headway-based Holding Strategies

    Reliability is a key determinant of the quality of a transit service. Control is needed in order to deal with the stochastic nature of high-frequency bus services and to improve service reliability. In this study, we focus on holding control, both schedule- and headway-based strategies. An assessment framework is developed to systematically assess the effect of different strategies on passengers, the operator and transport authority. This framework can be applied by operators and authorities in order to determine what holding strategy is most beneficial to regulate headways, and thus solve related problems. In this research knowledge is gained about what service characteristics affect the performance of holding strategies and the robustness of these strategies in disrupted situations, by using scenarios. The framework is applied to a case study of a high-frequency regional bus line in the Netherlands. Based on the simulation results, we identified the line characteristics that are important for the performance of schedule- and headway-based strategies and determined how robust different strategies are in case of disruptions. Headway-based control strategies better mitigate irregularity along the line, especially when there are disruptions. However, schedule-based control strategies are currently easier to implement, because it does not require large changes in practice, and the performance of both strategies is generally equal in regular, undisrupted situations. In this paper, insights into what the concerns are for operators with respect to technical adaptations, logistical changes and behavioral aspects when using a headway-based strategy are given.

    Find the TRB paper and presentation of Ellen van der Werff HERE and HERE

    Supervised learning: Predicting passenger load in public transport

    For many Public Transport (PT) users, overcrowding in PT vehicles has a major decreasing effect on the comfort experience. However, most online routing applications still not take comfort regarding to crowdedness into account, but provide recommendations based on shortest distance, shortest travel-time, or number of interchanges.
    Being able to include certain information on crowdedness, requires knowledge about the current and future level of passenger load. Increasing amount and complexity of data describing public transport services allows us to better explore the detection methods and analysis of different phenomena of PT operations. Some countries or operators provide the possibility to use Smart Card (SC) data for occupancy prediction. However, SC data is not available in real time, which makes it hard to incorporate it into real time recommendation models. In this work, we show that it is possible to predict the passenger load via supervised learning, eliminating the need for fare collection data beyond the set needed for training.

    Find the CASPT presentation by Léonie Heydenrijk-Ottens HERE

    Assessing disruption management strategies in rail-bound urban public transport from a passenger perspective

    This paper provides a framework for generating and assessing alternatives
    in case of disruptions in rail-bound urban public transport systems,. The proposed
    framework considers the passenger perspective as well as the operator perspective,
    for the often-used measures of detouring and short-turning. An application of the
    framework demonstrates that currently used disruption management protocols often
    do not lead to the optimal solution from the passenger perspective. Furthermore, the
    optimal choice between alternatives from passenger perspective shows to be
    dependent on the passenger flows.

    Read the CASPT paper HERE and find the presentation HERE

    Assessing and improving operational strategies for the benefit of passengers in rail-bound urban transport systems

    Unplanned disruptions in transit can have consequent impacts on passengers. The more inconvenienced passengers are, the more likely operators will be negatively impacted. Yet so far, operators and researchers have addressed the rescheduling problem during disruptions mainly with a supply-side focus – timetable, crews and vehicles – and not with a passenger perspective. Urban rail transit particularly lacks insights in terms of passenger- focused rescheduling. Being able to assess the inconvenience experienced by passengers during disruptions compared with what they normally experience, and being able to compare how different rescheduling strategies affect them are therefore two major challenges.

    The framework developed in this study precisely aims at tackling 8 these challenges. A case study of the metro of Rotterdam is used to test the framework developed in this paper. Alternative strategies are developed focusing on the incident phase (from the beginning of the incident until its cause is resolved). The application of the framework reveals that a regularity-focused rescheduling strategy would be beneficial for high-frequency service users. Realistically, yearly savings could amount to around €900,000 in terms of societal passenger costs for the operator in the Rotterdam area alone. However, the omnipresence of the punctuality paradigm, through which most operators plan and analyze operations, makes the implementation of passenger-focused strategies a challenging task for traffic controllers. The results of the study are valuable for transit operators worldwide and the framework can provide insights to decision-makers on the performance of different strategies, bringing to light trade-offs between supply and passenger sides during disruptions.

    Read more of this research by Anne Durand: Paper TRB and Poster TRB

    Nieuwe lessen over de potentie van Fiets en OV

    Het combineren van fiets en openbaar vervoer is een duurzame oplossing voor de (mobiliteits)uitdagingen in zowel stedelijke gebieden als daarbuiten. Er is een revival van de fiets gaande en ook hoogwaardig openbaar vervoer rukt op. De keten van fiets mét openbaar vervoer combineert de voordelen van beide systemen: De fiets zorgt voor fijnmazige ontsluitingen van herkomst en bestemmingen, is milieuvriendelijk en stimuleert een gezonde leefstijl. Voor wat betreft OV neemt de kwaliteit de laatste jaren sterk toe door de introductie van hoogwaardig OV (HOV): snelle, frequente en betrouwbare bus- tram- en metrolijnen met een hoog comfortniveau. Voorbeelden zijn R-Net, Randstadrail en Q-Link. De halteafstanden van deze systemen zijn relatief hoog, waardoor de fiets een belangrijke rol speelt in de gebiedsontsluiting.
    Om het succes van de fiets en OV verder uit te bouwen is kennis nodig over hoe de mobilist zich nu en in de toekomst beweegt: Wat zijn de succesfactoren, welke voorwaarden spelen een rol en waarom worden bepaalde keuzes gemaakt, bijvoorbeeld. Dit paper laat de resultaten zien van vier TU Delft onderzoeken op dit gebied. Belangrijkste, nieuwe inzichten zijn bijvoorbeeld dat het invloedsgebied van HOV haltes tot 4x groter is ten opzichte van “gewoon’’ OV. Verder blijkt dat treinreizigers bereid zijn ca. 6 min. extra te fietsen naar een station waar ze een directe trein kunnen nemen naar hun bestemming (in plaats van met een overstap). Tot slot blijkt dat de huidige groep fiets-OV’ers in te delen is in 7 groepen, waarvan de middle-aged male professionals de grootste zijn en de gepensioneerden de kleinste. De resultaten zijn de basis voor verder onderzoek en toepassing om te komen tot een optimaal Fiets-OV netwerk.

    Lees het hele CVS paper HIER
    De presentatie is HIER beschikbaar

    Opportunities for the Combined Bicycle and Transit Mode

    Around the world cities face negative effects generated by increasing mobility needs. To tackle these issues, mobility should be environmental and spatial friendly. Combining bicycle and public transport into a ‘bicycle + transit mode’ will create a synergy with the best of both worlds: superb door-to-door accessibility offered by the bicycle and a large spatial reach from transit modes. These complemented modes combined easily challenge private carsin terms of speed as well accessibility.

    Research regarding the users and trip types of the bicycle and transit mode is largely missing. This is unfortunate, since understanding both user and trip characteristics is of the utmost importance to improve the share of the bicycle and transit mode. Policy-makers can make concrete decisions on infrastructure and service investments only when the gap between the aforementioned societal need and scientific knowledge is filled.

    The main analysis in the study is based on data from the Netherlands. The Netherlands is one of the countries with a head start regarding the use of the bicycle + transit mode. A one-day trip diary survey, representative of the population of the Netherlands, with more than 250,000 respondents who made nearly 700,000 trips over the course of 6 years (2010-2015), is used to derive important trip and user characteristics of the bicycle + transit mode. Finally, latent class cluster analysis is applied to find prototypical users of this mode on the basis of their socio-demographic attributes.

    It is, for example, found that the most important purposes of the bicycle and transit mode are work or education, typically involving relatively long distances. Bicycle and transit-potential for other transit network levels, such as metros and bus rapid transit can be found. Moreover, seven unique user groups – from middle-aged professionals to school children – are identified, and their different travel behaviour is discussed.

    Data-driven transfer inference for public transport journeys during disruptions

    Disruptions in public transport have major impact on passengers and disproportional effects on passenger satisfaction. The availability of smart card data gives opportunities to better quantify disruption impacts on passengers’ experienced journey travel time and comfort. For this, accurate journey inference from raw transaction data is required. Several rule-based algorithms exist to infer whether a passenger alighting and subsequent boarding is categorized as transfer or final destination where an activity is performed. Although this logic can infer transfers during undisrupted public transport operations, these algorithms have limitations during disruptions: disruptions and subsequent operational rescheduling measures can force passengers to travel via routes which would be non-optimal or illogical during undisrupted operations. Therefore, applying existing algorithms can lead to biased journey inference and biased disruption impact quantification. We develop and apply a new transfer inference algorithm which infers journeys from raw smart card transactions in an accurate way during both disrupted and undisrupted operations. In this algorithm we incorporate the effects of denied boarding, transferring to a vehicle of the same line (due to operator rescheduling measures as short-turning), and the use of public transport services of another operator on another network level as intermediate journey stage during disruptions. This results in an algorithm with an improved transfer inference performance compared to existing algorithms.

    Find the paper HERE

    Understanding the trip and user characteristics of the combined bicycle and transit mode

    Several cities around the world are facing mobility related problems such as traffic congestion and air pollution. Although limited individually, the combination of bicycle and transit offers speed and accessibility; by complementing each other’s characteristics the bicycle and transit combination can compete with automobiles. Recognising this, several studies have investigated policies that encourage integration of these modes. However, empirical analysis of the actual users and trips of the combined mode is largely missing. This study addresses this gap by (i) reviewing empirical findings on related modes, (ii) deriving user and trip characteristics of the bicycle and transit mode in the Netherlands, and (iii) applying latent class cluster analysis to discover prototypical users based on their socio-demographic attributes. Most trips by this mode are found to be for relatively long commutes where transit is in the form of trains, and bicycle and walking are access and egress modes respectively. Furthermore, seven user groups are identified and their spatial and temporal travel behaviour is discussed. Transport authorities may use the empirical results in this study to further streamline integration of bicycle and transit for its largest users as well as to tailor policies to attract more travellers.

    Find our Thredbo conference presentation HERE

    Read our paper HERE

    Modelling Multimodal Transit Networks: Integration of bus networks with walking and cycling

    Demand for (public) transportation is subject to dynamics affected by technological, spatial, societal and demographic aspects. The political environment, together with financial and spatial constraints limit the possibilities to address transit issues arising from growing demand through the construction of new infrastructure. Upgrading of existing services and improving integration over the entire trip chain (including cycling) are two options that can address these transport issues. However, transport planners and transport service operators often fail to include the entire trip when improving services, as improvement is normally achieved through the adaptations of characteristics (e.g. speeds, stop distances) of the services.
    Our developed framework consists of two parts: one to assess the characteristics of the different bus services and their access and egress modes, and one to assess the effects of integration of these services, which includes the modelling and analysis in a regional transit model. The framework has successfully been applied to a case study showing that bus systems with higher frequencies and speeds can attract twice the amount of cyclists on the access and egress sides. It also shows that passengers accept longer access and egress distances with more positive characteristics of the bus service (higher speeds, higher frequencies).

    Find the presentation of Judith Brand at MT-ITS in Napoli HERE

    Find our paper HERE

    © 2011 TU Delft