Design of Robust and Energy-Efficient ATO Speed Profiles of Metropolitan Lines Considering Train Load Variations and Delays

Metropolitan railway operators' strategic plans include nowadays actions to reduce energy consumption. The application of ecodriving initiatives in lines equipped with automatic train operation (ATO) systems can provide important savings with low investments. Previous studies carried out under...

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Published in:	IEEE transactions on intelligent transportation systems Vol. 16; no. 4; pp. 2061 - 2071
Main Authors:	Fernandez-Rodriguez, Adrian, Fernandez-Cardador, Antonio, Cucala, Asuncion P., Dominguez, Maria, Gonsalves, Tad
Format:	Journal Article
Language:	English
Published:	IEEE 01.08.2015
Subjects:	Communication-based train control (CBTC) Delays Energy consumption energy saving Linear programming multi objective particle swarm optimization (MOPSO) Optimization Particle swarm optimization Robustness subway systems train load variations train operation Uncertainty multi objective particle swarm optimization (MOPSO) train load variations subway systems Communication-based train control (CBTC) uncertainty energy saving train operation
ISSN:	1524-9050, 1558-0016
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Abstract	Metropolitan railway operators' strategic plans include nowadays actions to reduce energy consumption. The application of ecodriving initiatives in lines equipped with automatic train operation (ATO) systems can provide important savings with low investments. Previous studies carried out under the ATO framework have not considered the main uncertainties in the traffic operation: the train load and delays in the line. This paper proposes a method to design robust and efficient speed profiles to be programmed in the ATO equipment of a metro line. First, an optimal Pareto front for ATO speed profiles that are robust to changes in train load is constructed. There are two objectives: running time and energy consumption. A robust optimization technique and an alternative method based on the conservation of the shape of the speed profiles (pattern robustness) are compared. Both procedures make use of a multi objective particle swarm optimization algorithm. Then, the set of speed profiles to be programmed in the ATO equipment is selected from the robust Pareto front by means of an optimization model. This model is a particle swarm optimization algorithm (PSO) to minimize the total energy consumption considering the statistical information about delays in the line. This procedure has been applied to a case study. The results showed that the pattern robustness is more restrictive and meaningful than the robust optimization technique as it provides information about shapes that are more comfortable for passengers. In addition, the use of statistical information about delays provides additional energy savings between 3% and 14%.
AbstractList	Metropolitan railway operators' strategic plans include nowadays actions to reduce energy consumption. The application of ecodriving initiatives in lines equipped with automatic train operation (ATO) systems can provide important savings with low investments. Previous studies carried out under the ATO framework have not considered the main uncertainties in the traffic operation: the train load and delays in the line. This paper proposes a method to design robust and efficient speed profiles to be programmed in the ATO equipment of a metro line. First, an optimal Pareto front for ATO speed profiles that are robust to changes in train load is constructed. There are two objectives: running time and energy consumption. A robust optimization technique and an alternative method based on the conservation of the shape of the speed profiles (pattern robustness) are compared. Both procedures make use of a multi objective particle swarm optimization algorithm. Then, the set of speed profiles to be programmed in the ATO equipment is selected from the robust Pareto front by means of an optimization model. This model is a particle swarm optimization algorithm (PSO) to minimize the total energy consumption considering the statistical information about delays in the line. This procedure has been applied to a case study. The results showed that the pattern robustness is more restrictive and meaningful than the robust optimization technique as it provides information about shapes that are more comfortable for passengers. In addition, the use of statistical information about delays provides additional energy savings between 3% and 14%.
Author	Fernandez-Rodriguez, Adrian Cucala, Asuncion P. Fernandez-Cardador, Antonio Dominguez, Maria Gonsalves, Tad
Author_xml	– sequence: 1 givenname: Adrian surname: Fernandez-Rodriguez fullname: Fernandez-Rodriguez, Adrian email: adrian.fernandez@iit.upcomillas.es organization: Inst. for Res. in Technol., Comillas Pontifical Univ., Madrid, Spain – sequence: 2 givenname: Antonio surname: Fernandez-Cardador fullname: Fernandez-Cardador, Antonio email: antonio.fernandez@iit.upcomillas.es organization: Inst. for Res. in Technol., Comillas Pontifical Univ., Madrid, Spain – sequence: 3 givenname: Asuncion P. surname: Cucala fullname: Cucala, Asuncion P. email: paloma.cucala@iit.upcomillas.es organization: Inst. for Res. in Technol., Comillas Pontifical Univ., Madrid, Spain – sequence: 4 givenname: Maria surname: Dominguez fullname: Dominguez, Maria email: maria.dominguez@iit.upcomillas.es organization: Inst. for Res. in Technol., Comillas Pontifical Univ., Madrid, Spain – sequence: 5 givenname: Tad surname: Gonsalves fullname: Gonsalves, Tad email: tad-gonsal@sophia.jp organization: Dept. of Inf. & Commun. Sci., Sophia Univ., Tokyo, Japan
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Keywords	multi objective particle swarm optimization (MOPSO) train load variations subway systems Communication-based train control (CBTC) uncertainty energy saving train operation
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SubjectTerms	Communication-based train control (CBTC) Delays Energy consumption energy saving Linear programming multi objective particle swarm optimization (MOPSO) Optimization Particle swarm optimization Robustness subway systems train load variations train operation Uncertainty
Title	Design of Robust and Energy-Efficient ATO Speed Profiles of Metropolitan Lines Considering Train Load Variations and Delays
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