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  • Feng, Xiaoyun  (4)
  • Mobility and traffic research  (4)
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  • Mobility and traffic research  (4)
  • 1
    Online Resource
    Online Resource
    Model for Optimal Selection of Projects to Improve Running Time and Operating Cost Efficiency on Passenger Rail Corridors
    SAGE Publications ; 2016
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 2546, No. 1 ( 2016-01), p. 33-42
    Details
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 2546, No. 1 ( 2016-01), p. 33-42
    Abstract: Recent proposals for expanded intercity passenger rail service in the United States have included plans for incremental improvements to existing Amtrak service. Improvements to existing services aim to accommodate faster and more frequent passenger train operation, generally on track owned and operated by freight railways. Various projects and approaches can be considered when the running time of passenger trains is being decreased on a particular corridor. Raising the maximum operating speed can yield different benefits on different sections of the route, and conditions on adjacent sections can interact. For instance, the marginal travel time benefit of improving segments of a line from a maximum speed of 79 to 110 mph is less than the benefit of other improvements to eliminate segments currently restricted to lower speeds. Therefore, to maximize the potential of limited resources, project investments must be selected carefully to improve performance in a cost-effective manner. This paper presents a methodology for optimally selecting projects or establishing program budgets to reduce running time on a passenger rail corridor with consideration of capital, maintenance, and operating costs. The proposed project selection model is formulated with genetic algorithms. In the model, a route is divided into sections that can be independently upgraded, and the objective function is formulated as minimization of running time along the route. This model can aid in quickly and efficiently developing a strategic plan for improving running time on passenger rail corridors.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.3141/2546-05
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2016
    detail.hit.zdb_id: 2403378-9
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    Online Resource
  • 2
    Online Resource
    Online Resource
    Train Scheduling Method to Reduce Substation Energy Consumption and Peak Power of Metro Transit Systems
    SAGE Publications ; 2021
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 2675, No. 4 ( 2021-04), p. 201-212
    Details
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 2675, No. 4 ( 2021-04), p. 201-212
    Abstract: The rapid development of metro transit systems brings very significant energy consumption, and the high service frequency of metro trains increases the peak power requirement, which affects the operation of systems. Train scheduling optimization is an effective method to reduce energy consumption and substation peak power by adjusting timetable parameters. This paper proposes a train timetable optimization model to coordinate the operation of trains. The overlap time between accelerating and braking phases is maximized to improve the utilization of regenerative braking energy (RBE). Meanwhile, the overlap time between accelerating phases is minimized to reduce the substation peak power. In addition, the timetable optimization model is rebuilt into a mixed integer linear programming model by introducing logical and auxiliary variables, which can be solved by related solvers effectively. Case studies based on one of Guangzhou Metro Lines indicate that, for all-day operation, the utilization of RBE would likely be improved on the order of 23%, the substation energy consumption would likely be reduced on the order of 14%, and the duration of substation peak power would likely be reduced on the order of 66%.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.1177/0361198120974677
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2021
    detail.hit.zdb_id: 2403378-9
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  • 3
    Online Resource
    Online Resource
    Multi-Objective Trajectory Optimization for Freight Trains Based on Quadratic Programming
    SAGE Publications ; 2020
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 2674, No. 11 ( 2020-11), p. 466-477
    Details
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 2674, No. 11 ( 2020-11), p. 466-477
    Abstract: The overspeed protection, smooth driving, punctuality, and energy efficiency of freight trains largely depend on their trajectory optimization. This paper proposes a multi-objective optimization model, which maximizes the weighted sum of energy efficiency, punctuality, and driving smoothness. Model constraints systematically cover many practical conditions, including varying line resistance, overspeed protection, discrete neutral zones, and nonlinear traction and electric braking characteristics. Electric braking and pneumatic braking are distinguished in the freight train model, and the utilization of feedback braking energy is also considered. By nonlinear approximation, the proposed multi-objective optimization model is solved by the quadratic programming (QP) algorithm, and optimized trajectories are obtained. Numerical simulation demonstrates the correctness and effectiveness of the proposed method. Comparisons with two actual trials show that the energy efficiency and driving smoothness of the proposed method are better than that of the drivers’ operation with the same journey time. In addition, the algorithm has a short computation time, which has the potential to be integrated for on-board devices such as the driver advisory system (DAS).
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.1177/0361198120937307
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2020
    detail.hit.zdb_id: 2403378-9
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  • 4
    Online Resource
    Online Resource
    Improving Regenerative Energy Receptivity in Metro Transit Systems : Coordinated Train Control Algorithm
    SAGE Publications ; 2015
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 2534, No. 1 ( 2015-01), p. 48-56
    Details
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 2534, No. 1 ( 2015-01), p. 48-56
    Abstract: Algorithms for current automatic train operation (ATO) focus mainly on reducing the mechanical energy of motion for a single train within an existing timetable. However, the reuse of regenerative energy is another factor that contributes to energy consumption and conservation in multitrain networks. To improve regenerative energy receptivity and energy savings in a bidirectional metro transit network, this study formulated a coordinated train control algorithm that was based on genetic algorithm techniques. The energy saving potential of different station departure time intervals between two opposing trains (synchronization time) was tested. Simulation on the Visual C++ platform demonstrated that the algorithm could provide an optimal train speed profile with better energy performance while also satisfying operational constraints. Different synchronization times have different optimization ratios. This research was another step to facilitate the development of an ATO control algorithm that considers overall energy consumption. Increased knowledge of the influence of synchronization time at stations on energy consumption in regenerative multitrain networks will also aid in the design of more energy-efficient timetables.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.3141/2534-07
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2015
    detail.hit.zdb_id: 2403378-9
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