Train traffic planning in intelligent transportation systems

Aim. To suggest a new method of energy-efficient traffic planning for subways. Traffic planning is understood as passenger train scheduling in compliance with all the applicable requirements and restrictions involving hourly performance in terms of the specified number of handled train pairs, efficient use of the theoretical and practical capacity of a given subway line, safety of vehicle traffic ensured by timely technical diagnostics of the rolling stock in the form of scheduled repairs and inspections in depots and/or lineside technical inspection stations, passenger comfort expressed in the uniformity of train delivery to stations, which, in turn, ensures the redistribution of passenger flows at stations and prevents congestion on platforms.

Methods. The paper uses methods of automated construction of target metro train schedules that are based on the criteria of train spacing uniformity, as well as uniformity of rolling stock distribution in the process of transition planning, with subsequent redistribution of delay times defined by the automation algorithm over the station-to-station travel times. The method of uniform travel times is based on minimizing the sum of square deviations of departure times for all stations and all trains. The method of vehicle uniformity within transition processes is based on the application of the Euclidean integer division algorithm. When preparing the paper, the authors took into account the fact that metro lines feature systems of various levels of automation regulated by the IEC 62290-1-2014 international standard. Attention was paid not only to transportation systems with high degrees of automation (classified as GoA3 and GoA4 in the standards), but those with low automation (classified as GoA0, GoA1 and GoA2) as well.

Results. The method proposed in the paper clearly shows reduced power consumption associated with train traction that is proportional to the durations of delayed departures defined by the automation algorithms of the intelligent automated system for target metro train schedule construction.

Conclusions. The presented approach clearly indicates a direct correlation between the energy efficiency of a train schedule and the uniformity of distribution of control actions that adjust train spacing and the durations of the adopted delays, defines the sequences of added/removed units of rolling stock within transition processes, as well as rational night-time train allocation. The materials presented in the paper extend the available knowledge in the field of automation of metro train traffic planning, thus enabling further improvement of the methods of intelligent transportation system design that take into account the deployed highly automated train driving systems (GoA3 and GoA4).

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