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    Understanding the difference in travel patterns between docked and dockless bike-sharing systems: a case study in Nanjing, china

    The co-existence of dockless and traditional docked bike-sharing systems presents new opportunities for sustainable transportation in cities all over the world, both serving door to door trips and access and egress to and from transit. To compare travel patterns of these two systems, we explored the GPS data of a dockless bike-sharing scheme and the smart card data of a docked bike-sharing scheme in the city of Nanjing, China over the same time period. In order to obtain information from different perspectives, such as user perception and opinions, an intercept survey on bike-sharing mode choice was conducted. A mode choice model was estimated to reveal the effects of personal information, user perception and experience on bike-sharing usage. Results show that dockless bike-sharing systems have a shorter average travel distance and travel time but a higher use frequency and hourly usage volume compared to docked bike-sharing systems. Trips of docked and dockless bike-sharing on workdays are more frequent than those on weekends, especially during the morning and evening rush hours from 7:00-9:00 and 17:00-19:00, respectively. As to the factors influencing travelers’ mode choice, results show that retirees, enterprise staff and users with E-bikes are less likely to use docked sharing-bikes than dockless bikes. In contrast, high-income travelers and people who are highly sensitive to discounts, internet technology and online payment service are more likely to use the dockless bike-sharing. Finally, policy implications are discussed for cities to improve the performance of docked and dockless bike-sharing systems.

    Find our poster HERE

    Insights into factors affecting the combined bicycle-transit mode

    The combination of bicycle and transit is an upcoming, sustainable multimodality. The flexibility of the bicycle combined with the speed and comfort of good transit can be a highly competitive alternative to the car. This study shows that many factors influence the uptake and attractiveness of the bicycle-transit combination. An in-depth literature review resulted in over thirty unique factors: six transit related factors, twenty first-last mile factors and fifteen context related factors. All these factors might influence the demand for this ‘new’ mode positively or negatively. An exploratory choice modelling study showed that Dutch bicycle-train users in our sample are willing to pay €0.11 for a minute less bicycle time, €0.08 for a minute less train time, €0.11 for a minute of less time to park and €0.60 per avoided transfer. These kinds of insights give the bicycle and transit sector valuable information to be used in modelling multimodality and cost-benefit analyses, thereby supporting improved decision making and integrated design of bicycle and transit networks.

    Read the full CASPT paper HERE and find the presentation HERE

    Wat gaat MaaS ons brengen?

    MaaS congres 2018: Niels van Oort is assistant professor public transport aan de TU Delft en doet onderzoek naar de effecten van nieuwe vervoerssytemen. Hij gaat de mogelijke impact van MaaS op reizigers en maatschappij toelichten, met voorbeelden van verschillende pilots en onderzoeken.

    Zie HIER zijn bijdrage aan het MaaS congres 2018

    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.

    Urban Demand Responsive Transport in the Mobility as a Service ecosystem: its role and potential market share

    Mobility as a Service (MaaS) is entering the transportation market. MaaS aims at the full
    integration of the existing transportation services and it offers tailored mobility packages to
    the user. In MaaS ecosystems, on-demand services play an important role as complement to
    public transport due to their flexibility. However, to date, most attention has been placed on
    individual on-demand services. This study focuses on Demand Responsive Transport (DRT):
    collective on-demand services. Using an on-line survey, we analysed the characteristics of
    the respondents who chose different modes of transport among their selected modes.
    Results find a distinctive pattern in the willingness of users to use different modes, with
    different levels in what could be considered as a multimodality ladder. The different rungs of
    it would be: 1st car (if available), 2nd public transport, 3rd DRT and 4th taxi-like services.
    This way, a person standing on the third rung would include car, public transport and DRT in
    their consideration set, but not taxi. This finding suggests that, if implemented in the right
    way, DRT services can attract a larger number of users than taxi-like services, especially in a
    MaaS ecosystem where initial barriers to try this service can be lessened.

    Find the paper presented by Maria Alonso Gonzalez at the Thredbo conference in Stockholm HERE

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