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  • 1.
    Häll, Carl Henrik
    et al.
    Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.
    Ceder, Avishai (Avi)
    Department of Civil and Environmental Engineering, University of Auckland, New Zealand, and International Development and Cooperation (IDEC), Hiroshima University, Hiroshima, Japan.
    Ekström, Joakim
    Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.
    Quttineh, Nils-Hassan
    Linköping University, Department of Mathematics, Optimization . Linköping University, Faculty of Science & Engineering.
    Adjustments of public transit operations planning process for the use of electric buses2019In: Journal of Intelligent Transportation Systems / Taylor & Francis, ISSN 1547-2450, E-ISSN 1547-2442, Vol. 23, no 3, p. 216-230Article in journal (Refereed)
    Abstract [en]

    This work investigates and discusses how the introduction of electric buses (EB), both battery and plug-in hybrid EB, will and should change the operations planning of a public transit system. It is shown that some changes are required in the design of a transit route network, and in the timetabling and vehicle scheduling processes. Other changes are not required, but are advisable, using this opportunity upon the introduction of EB. The work covers the main characteristics of different types of EB with a short description, including the most popular charging technologies, and it presents the generally accepted transit operations planning process. Likewise, it describes and analytically formulates new challenges that arise when introducing EB. The outcome of the analyses shows that multiple new considerations must take place. It is also shown that the different charging techniques will influence the operations planning process in different ways and to a varying extent. With overnight, quick and continuous charging, the main challenges are in the network route design step, given the possibility of altering the existing network of routes, with efficient and optimal changes of the timetabling and vehicle scheduling components. An illustrative example, based on four bus lines in Norrköping, Sweden, is formulized and introduced using three problem instances of 48, 82, and 116 bus trips. The main results exhibit the minimum number of vehicles required using different scenarios of charging stations.

    The full text will be freely available from 2019-10-17 14:47
  • 2.
    Khoshniyat, Fahimeh
    et al.
    Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.
    Peterson, Anders
    Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.
    Improving Train Service Reliability by Applying an Effective Timetable Robsutness Strategy2017In: Journal of Intelligent Transportation Systems / Taylor & Francis, ISSN 1547-2450, E-ISSN 1547-2442, Vol. 21, no 6, p. 525-543Article in journal (Refereed)
    Abstract [en]

    To avoid propagation of delays in dense railway timetables, it is important to ensure robustness. One strategy to improve robustness is to provide adequate amount of buffer times between trains. This study concerns how “scheduled minimum headways” should be determined in order to improve robustness in timetables. Scheduled minimum headways include technical minimum headway plus some buffer time. We propose a strategy to be implemented in timetables at the final stages of planning and prior to the operations.  The main contributions of this study are 1) to propose a strategy where the size of the scheduled minimum headways is dependent on trains' travel times instead of a fixed-sized time slot and it is called “travel time dependent scheduled minimum headways” or TTDSMH, 2) to evaluate the effects of the new strategy on heterogeneity, speed, and the number of trains in timetables, 3) to show that a simple strategy can improve robustness without imposing major changes in timetables. The strategy is implemented in an Mixed Integer Linear Programming framework for timetabling and tested for some problem instances from Sweden. Results show that TTDSMH can improve robustness. The proposed strategy can be applied in intelligent transportation tools for railway timetabling.

  • 3.
    Tapani, Andreas
    Linköping University, Department of Science and Technology. Linköping University, The Institute of Technology.
    Vehicle Trajectory Impacts of Adaptive Cruise Control2012In: Journal of Intelligent Transportation Systems / Taylor & Francis, ISSN 1547-2450, E-ISSN 1547-2442, Vol. 16, no 1, p. 36-44Article in journal (Refereed)
    Abstract [en]

    Adaptive Cruise Control (ACC) is assumed to have a potentialto improve quality-of-service and safety and to reduce the environmentalimpact of the road traffic system. This paper use vehicletrajectories from traffic simulation to study impacts of ACCon vehicle acceleration and deceleration rates. The analysis isbased on traffic simulations with car-following models includingACC functionality and driver behaviour in ACC-equipped as wellas standard non-equipped vehicles. The simulation results showthat ACC can improve the traffic situation in terms of reduced accelerationand deceleration rates even though macroscopic trafficproperties may remain uninfluenced. This supports the hypothesisedpositive road safety and environmental effects of ACC. It isalso established that the results are largely dependent on the assumptionsmade regarding driver behaviour in ACC-equipped andstandard vehicles. It is consequently crucial to include appropriateassumptions regarding driver behaviour in traffic simulation basedanalyses of ACC.

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