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Optimal Trajectory Planning and Train Scheduling for Urban Rail Transit Systems (Hardcover, 1st ed. 2016)
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Optimal Trajectory Planning and Train Scheduling for Urban Rail Transit Systems (Hardcover, 1st ed. 2016)
Series: Advances in Industrial Control
Expected to ship within 12 - 19 working days
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This book contributes to making urban rail transport fast, punctual
and energy-efficient -significant factors in the importance of
public transportation systems to economic, environmental and social
requirements at both municipal and national levels. It proposes new
methods for shortening passenger travel times and for reducing
energy consumption, addressing two major topics: (1) train
trajectory planning: the authors derive a nonlinear model for the
operation of trains and present several approaches for calculating
optimal and energy-efficient trajectories within a given schedule;
and (2) train scheduling: the authors develop a train scheduling
model for urban rail systems and optimization approaches with which
to balance total passenger travel time with energy efficiency and
other costs to the operator. Mixed-integer linear programming and
pseudospectral methods are among the new methods proposed for
single- and multi-train systems for the solution of the nonlinear
trajectory planning problem which involves constraints such as
varying speed restrictions and maximum traction/braking force.
Signaling systems and their effects are also accounted for in the
trajectory planning model.Origin-destination passenger demand is
included in the model formulation for train scheduling. Iterative
convex programming and efficient bi-level approaches are utilized
in the solution of the train-scheduling problem. In addition, the
splitting rates and route choices of passengers are also optimized
from the system point of view. The problems and solutions described
in Optimal Trajectory Planning and Train Scheduling for Urban Rail
Transit Systems will interest researchers studying public transport
systems and logistics whether from an academic or practitioner
background as well as providing a real application for anybody
studying optimization theory and predictive control.
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