1. Baranov L. A., Golovicher Ya. M., Erofeev E. V. et al. Mikroprotsessornyye sistemy avtovedeniya podvizhnogo sostava [Microprocessor systems for auto-matic guidance of rolling stock]. Moscow: Transport Publ., 1990, 272 p. (In Russian), Baranov L. A., Golovicher Ya. M., Erofeev E. V. et al. Mikroprotsessornyye sistemy avtovedeniya podvizhnogo sostava [Microprocessor systems for auto-matic guidance of rolling stock]. Moscow: Transport Publ., 1990, 272 p. (In Russian)
2. Muginshtein L. A., Vinogradov S. A., Yabko I. A. et al. Energooptimal'nyy tyagovyy raschet dvizheniya poyezdov [Energy-optimal traction calculation of the movement of trains]. Zheleznodorozhnyy transport [Railway transport]. 2010, vol. 2, pp. 24–29. (In Russian), Muginshtein L. A., Vinogradov S. A., Yabko I. A. et al. Energooptimal'nyy tyagovyy raschet dvizheniya poyezdov [Energy-optimal traction calculation of the movement of trains]. Zheleznodorozhnyy transport [Railway transport]. 2010, vol. 2, pp. 24–29. (In Russian)
3. Baranov L. A., Sidorenko V. G., Balakina E. P. et al. Intellektual'noye tsen-tralizovannoye upravleniye dvizheniyem vneulichnogo gorodskogo zheleznodorozhnogo transporta v usloviyakh intensivnogo dvizheniya [In-telligent centralized traffic control of off-street urban railway transport in conditions of heavy traffic]. Nadezhnost' [Reliability]. 2021, vol. 2, pp. 17–23. DOI: doi.org/10.21683/1729-2646-2021-21-2-17-23. (In Russian), Baranov L. A., Sidorenko V. G., Balakina E. P. et al. Intellektual'noye tsen-tralizovannoye upravleniye dvizheniyem vneulichnogo gorodskogo zheleznodorozhnogo transporta v usloviyakh intensivnogo dvizheniya [In-telligent centralized traffic control of off-street urban railway transport in conditions of heavy traffic]. Nadezhnost' [Reliability]. 2021, vol. 2, pp. 17–23. DOI: doi.org/10.21683/1729-2646-2021-21-2-17-23. (In Russian)
4. Su R., Gu Q., Wen T. et al. Optimization of High-Speed Train Control Strategy for Traction Energy Saving Using an Improved Genetic Algorithm. Journal of Applied Mathematics, vol, 2014. DOI: doi.org/10.1155/2014/507308. URL: https://www.hindawi.com/journals/jam/2014/507308/., Su R., Gu Q., Wen T. et al. Optimization of High-Speed Train Control Strategy for Traction Energy Saving Using an Improved Genetic Algorithm. Journal of Applied Mathematics, vol, 2014. DOI: doi.org/10.1155/2014/507308. URL: https://www.hindawi.com/journals/jam/2014/507308/.
5. Liu P., Han B. Optimizing the train timetable with consideration of different kinds of headway time. Journal of Algorithms & Computational Technology, 2017, vol. 11(2), pp. 148–162. DOI: 10.1177/1748301816689685., Liu P., Han B. Optimizing the train timetable with consideration of different kinds of headway time. Journal of Algorithms & Computational Technology, 2017, vol. 11(2), pp. 148–162. DOI: 10.1177/1748301816689685.