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    Posted in January 2019

    Passenger Travel Time Reliability for Multi-Modal Public Transport Journeys

    Urban transit networks typically consist of multiple modes and the journeys may involve a transfer within or across modes. Hence, the passenger experience of travel time reliability is based on the whole journey experience including the transfers. Although the impact of transfers on reliability has been highlighted in the literature, the existing indicators either focus on uni-modal transfers only or fail to include all components of travel time in reliability measurement. This study extends the existing ‘Reliability Buffer Time’ metric to journeys with multi-modal transfers and develops a methodology to calculate it using a combination of smartcard and automatic vehicle location data. The developed methodology is applied to a real-life case study for the Amsterdam transit network consisting of bus, metro and tram services. By using a consistent method for all journeys in the network, reliability can be compared between different modes or between multiple routes for the same origin-destination pair. The developed metric can be used to study the reliability impacts of policies affecting multiple modes. It can also be used as an input to behavioral models such as mode, route or departure time choice models.

    Find the TRB paper and presentation of Malvika Dixit HERE and HERE

    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

    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

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