A multiphase optimal control method for multi-train control and scheduling on railway lines

Ye, Hongbo; Liu, Ronghui

doi:10.1016/j.trb.2016.08.002

Cited by 89 publications

(48 citation statements)

References 67 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The model complex M evolves and generalizes the dynamic models of scheduling theory [2][3][4]6,15]. The main distinctive feature (as apposed to [3]) of the complex is that nonlinear technological constraints are actualized in the convex domain of allowable control inputs rather DOI: 10.1051/ , 02012 (2017)than in differential equations.…”

Section: Resultsmentioning

confidence: 99%

Mathematical model and algorithm of operation scheduling for monitoring situation in local waters

2017

View full text Add to dashboard Cite

Abstract. A multiple-model approach to description and investigation of control processes in regional maritime security system is presented. The processes considered in this paper were qualified as control processes of computing operations providing monitoring of the situation adding in the local water area and connected to relocation of different ships classes (further the active mobile objects (AMO)). Previously developed concept of active moving object (AMO) is used. The models describe operation of AMO automated monitoring and control system (AMCS) elements as well as their interaction with objects-inservice that are sources or recipients of information being processed. The unified description of various control processes allows synthesizing simultaneously both technical and functional structures of AMO AMCS. The algorithm for solving the scheduling problem is described in terms of the classical theory of optimal automatic control.

show abstract

Section: Resultsmentioning

confidence: 99%

Mathematical model and algorithm of operation scheduling for monitoring situation in local waters

2017

View full text Add to dashboard Cite

show abstract

“…Additionally, the requirements of network operation and various passengers demand should be satisfied [10][11][12][13][14][15]. Lastly, energy conservation and environmental protection should be considered [16][17][18][19][20][21]. Hence, TSSTT should not only meet the demands of compiling a working diagram at the network level under different passenger needs, but also should consider energy conservation and environmental protection while ensuring that the TSRT on the same railway section falls within the neighborhood of TSSTT.…”

Section: Introductionmentioning

confidence: 99%

“…TSRT based on traction calculation is determined by equations of motion combined with the relationship between train tractive and braking forces, the sum of mechanical and aerodynamic resistances, and force caused by the track gradient, which reflect the train's section traction, idling, and brake operation process [16][17][18][19]. Hence, noise factors such as weather and power supply [9] on the railway line are considered less in the calculation process.…”

Section: Introductionmentioning

confidence: 99%

Suitability Evaluation of a Train’s Scheduled Section Travel Time

Qing

Yao

et al. 2020

Sustainability

View full text Add to dashboard Cite

Two methods used to evaluate the suitability of a train's scheduled section travel time (TSSTT) are theoretical modeling and data analysis. The first is suitable for newly constructed railway projects, the second can reveal the reliability of the train section running time (TSRT) under an instruction of TSSTT in cases where the train operation data are provided. A suitability evaluation method of TSSTT is proposed by calculating the possibility that a train completes a task within the time windows, centering on the TSSTT given in advance. The TSRTs between two adjacent stations are classified into four groups based on whether the train dwells at the two end stations of the railway section, and then subdivided secondly into subgroups by the instruction of TSSTT given. The kurtosis of each subgroup data of TSRT is larger than 3, so Weibull distribution is selected to fit the TSRT distribution of subgroup data due to good fitness based on root measurement of the least square (SRLSM). A busy high-speed railway line in the Wuhan area of China is used to validate the presented approach. Each railway section has its own suitable TSSTT in which TSRT might achieve 96% reliability of arriving within 2.5 minutes centering on suitable TSSTT, otherwise which might not obtain 10% reliability.

show abstract

“…Chevrier et al [1], Shoichiro and Koseki [2], Yang et al [3,4], Wang and Goverde [5], Ning et al [6], Zhang et al [7] and Yang et al [8] optimized the train timetable by adjusting the train running path, the arrival and departure time or the passing time of the train, and realized energy-saving operation. Albrecht et al [9][10][11], Scheepmaker and Goverde [12], Yan et al [13], Ye and Liu [14], Luan et al [15], Yang et al [16], Fernández-Rodríguez et al [17] under the constraints of train characteristics, ramps, curves and speed limits, achieved optimal operating conditions and reduced energy consumption by adjusting the acceleration, cruising, coasting and braking phase.…”

Section: Introductionmentioning

confidence: 99%

“…However, considering energy-saving issues from a single view of train timetables or train control methods, it may be di cult to nd a suitable energysaving strategy. erefore, the energy-saving schemes that combine these two angles are gradually becoming research focus Ye and Liu [14] established the multiphase optimal control problem to make the train's optimal strategy change with line conditions, and got the optimal train arrival and departure time under the condition of ensuring the safety interval. Ning et al [6] optimized the distribution of running time on the section and appropriately adopted a coasting state to reduce the energy consumption of the train during the speci ed total running time.…”

Section: Introductionmentioning

confidence: 99%

Optimal High-Speed Railway Timetable by Stop Schedule Adjustment for Energy-Saving

Chen

et al. 2019

Journal of Advanced Transportation

View full text Add to dashboard Cite

Timetable optimization techniques offer opportunity for saving energy and hence reducing operational costs for high-speed rail services. The existing energy-saving timetable optimization is mainly concentrated on the train running state adjustment and the running time redistribution between two stations. Not only the adjustment space of timetables is limited, but also it is hard for the train to reach the optimized running state in reality, and it is difficult to get feasible timetable with running time redistribution between two stations for energy-saving. This paper presents a high-speed railway energy-saving timetable based on stop schedule optimization. Under the constraints of safety interval and stop rate, with the objective of minimizing the increasing energy consumption of train stops and the shortest travel time of trains, the high-speed railway energy-saving timetable optimization model is established. The fuzzy mathematics programming method is used to design an efficient algorithm. The proposed model and algorithm are demonstrated in the actual operation data of Beijing-Shanghai high-speed railway. The results show that the total operating energy consumption of the train is reduced by 3.7%, and the total travel time of the train is reduced by 11 minutes.

show abstract

A multiphase optimal control method for multi-train control and scheduling on railway lines

Cited by 89 publications

References 67 publications

Mathematical model and algorithm of operation scheduling for monitoring situation in local waters

Mathematical model and algorithm of operation scheduling for monitoring situation in local waters

Suitability Evaluation of a Train’s Scheduled Section Travel Time

Optimal High-Speed Railway Timetable by Stop Schedule Adjustment for Energy-Saving

Contact Info

Product

Resources

About