{"id":{"repo_id":"njit","oai_identifier":"oai:digitalcommons.njit.edu:dissertations-1242"},"canonical_url":"https://search.dev.ndltd.org/etd/njit/oai:digitalcommons.njit.edu:dissertations-1242","repository":{"repo_id":"njit","name":"NJIT","base_url":"https://digitalcommons.njit.edu/do/oai/"},"display":{"title":"Optimal train control on various track alignments considering speed and schedule adherence constraints","abstract":"The methodology discussed in this dissertation contributes to the field of transit operational control to reduce energy consumption. Due to the recent increase in gasoline cost, a significant number of travelers are shifting from highway modes to public transit, which also induces higher transit energy consumption expenses. This study presents an approach to optimize train motion regimes for various track alignments, which minimizes total energy consumption subject to allowable travel time, maximum operating speed, and maximum acceleration/deceleration rates. The research problem is structured into four cases which consist of the combinations of track alignments (e.g., single vertical alignment and mixed vertical alignment) and the variation of maximum operating speeds (e.g., constant and variable). The Simulated Annealing (SA) approach is employed to search for the optimal train control, called \"golden run\". To accurately estimate energy consumption and travel time, a Train Performance Simulation (TPS) is developed, which replicates train movements determined by a set of dynamic variables (e,g., duration of acceleration and cruising, coasting position, braking position, etc.) as well as operational constraints (e.g., track alignment, speed limit, minimum travel time, etc.) The applicability of the developed methodology is demonstrated with geographic data of two real world rail line segments of The New Haven Line of the Metro North Railroad: Harrison to Rye Stations and East Norwalk to Westport Stations. The results of optimal solutions and sensitivity analyses are presented. The sensitivity analyses enable a transit operator to quantify the impact of the coasting position, travel time constraint, vertical dip of the track alignment, maximum operating speed, and the load and weight of the train to energy consumption. The developed models can assist future rail system with Automatic Train Control (ATC), Automatic Train Operation (ATO) and Positive Train Control (PTC), or conventional railroad systems to improve the planning and operation of signal systems. The optimal train speed profile derived in this study can be considered by the existing signal system for determining train operating speeds over a route.","abstract_html":"The methodology discussed in this dissertation contributes to the field of transit operational control to reduce energy consumption. Due to the recent increase in gasoline cost, a significant number of travelers are shifting from highway modes to public transit, which also induces higher transit energy consumption expenses. This study presents an approach to optimize train motion regimes for various track alignments, which minimizes total energy consumption subject to allowable travel time, maximum operating speed, and maximum acceleration/deceleration rates. The research problem is structured into four cases which consist of the combinations of track alignments (e.g., single vertical alignment and mixed vertical alignment) and the variation of maximum operating speeds (e.g., constant and variable). The Simulated Annealing (SA) approach is employed to search for the optimal train control, called "golden run". To accurately estimate energy consumption and travel time, a Train Performance Simulation (TPS) is developed, which replicates train movements determined by a set of dynamic variables (e,g., duration of acceleration and cruising, coasting position, braking position, etc.) as well as operational constraints (e.g., track alignment, speed limit, minimum travel time, etc.) The applicability of the developed methodology is demonstrated with geographic data of two real world rail line segments of The New Haven Line of the Metro North Railroad: Harrison to Rye Stations and East Norwalk to Westport Stations. The results of optimal solutions and sensitivity analyses are presented. The sensitivity analyses enable a transit operator to quantify the impact of the coasting position, travel time constraint, vertical dip of the track alignment, maximum operating speed, and the load and weight of the train to energy consumption. The developed models can assist future rail system with Automatic Train Control (ATC), Automatic Train Operation (ATO) and Positive Train Control (PTC), or conventional railroad systems to improve the planning and operation of signal systems. The optimal train speed profile derived in this study can be considered by the existing signal system for determining train operating speeds over a route.","abstract_has_math":false,"creators":["Kim, Kitae"],"institution":null,"degree_name":"Doctor of Philosophy in Civil Engineering - (Ph.D.)","degree_level":null,"degree_discipline":"Civil and Environmental Engineering","degree_department":null,"school":null,"contributors":["I-Jy Steven Chien","Lazar Spasovic","Athanassios K. Bladikas"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2010,"date_issued":"2010-01-31T08:00:00Z","date_published":"2010-01-31T08:00:00Z","updated_at":"2026-07-24T03:22:07Z","subjects":["Train control","Simmulated annealing","Energy consumption","Train performance simulation","Civil Engineering"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://digitalcommons.njit.edu/dissertations/187","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["I-Jy Steven Chien","Lazar Spasovic","Athanassios K. 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Due to the recent increase in gasoline cost, a significant number of travelers are shifting from highway modes to public transit, which also induces higher transit energy consumption expenses. This study presents an approach to optimize train motion regimes for various track alignments, which minimizes total energy consumption subject to allowable travel time, maximum operating speed, and maximum acceleration/deceleration rates. The research problem is structured into four cases which consist of the combinations of track alignments (e.g., single vertical alignment and mixed vertical alignment) and the variation of maximum operating speeds (e.g., constant and variable). The Simulated Annealing (SA) approach is employed to search for the optimal train control, called \"golden run\". To accurately estimate energy consumption and travel time, a Train Performance Simulation (TPS) is developed, which replicates train movements determined by a set of dynamic variables (e,g., duration of acceleration and cruising, coasting position, braking position, etc.) as well as operational constraints (e.g., track alignment, speed limit, minimum travel time, etc.) The applicability of the developed methodology is demonstrated with geographic data of two real world rail line segments of The New Haven Line of the Metro North Railroad: Harrison to Rye Stations and East Norwalk to Westport Stations. The results of optimal solutions and sensitivity analyses are presented. The sensitivity analyses enable a transit operator to quantify the impact of the coasting position, travel time constraint, vertical dip of the track alignment, maximum operating speed, and the load and weight of the train to energy consumption. The developed models can assist future rail system with Automatic Train Control (ATC), Automatic Train Operation (ATO) and Positive Train Control (PTC), or conventional railroad systems to improve the planning and operation of signal systems. The optimal train speed profile derived in this study can be considered by the existing signal system for determining train operating speeds over a route."]},{"key":"dc:title","label":"Title","values":["Optimal train control on various track alignments considering speed and schedule adherence constraints"]}]}],"canonical_facts":{"dc:contributor":["I-Jy Steven Chien","Lazar Spasovic","Athanassios K. Bladikas"],"dc:creator":["Kim, Kitae"],"dc:description.abstract":["The methodology discussed in this dissertation contributes to the field of transit operational control to reduce energy consumption. Due to the recent increase in gasoline cost, a significant number of travelers are shifting from highway modes to public transit, which also induces higher transit energy consumption expenses. This study presents an approach to optimize train motion regimes for various track alignments, which minimizes total energy consumption subject to allowable travel time, maximum operating speed, and maximum acceleration/deceleration rates. The research problem is structured into four cases which consist of the combinations of track alignments (e.g., single vertical alignment and mixed vertical alignment) and the variation of maximum operating speeds (e.g., constant and variable). The Simulated Annealing (SA) approach is employed to search for the optimal train control, called \"golden run\". To accurately estimate energy consumption and travel time, a Train Performance Simulation (TPS) is developed, which replicates train movements determined by a set of dynamic variables (e,g., duration of acceleration and cruising, coasting position, braking position, etc.) as well as operational constraints (e.g., track alignment, speed limit, minimum travel time, etc.) The applicability of the developed methodology is demonstrated with geographic data of two real world rail line segments of The New Haven Line of the Metro North Railroad: Harrison to Rye Stations and East Norwalk to Westport Stations. The results of optimal solutions and sensitivity analyses are presented. The sensitivity analyses enable a transit operator to quantify the impact of the coasting position, travel time constraint, vertical dip of the track alignment, maximum operating speed, and the load and weight of the train to energy consumption. The developed models can assist future rail system with Automatic Train Control (ATC), Automatic Train Operation (ATO) and Positive Train Control (PTC), or conventional railroad systems to improve the planning and operation of signal systems. The optimal train speed profile derived in this study can be considered by the existing signal system for determining train operating speeds over a route."],"dc:identifier":["https://digitalcommons.njit.edu/dissertations/187"],"dc:subject":["Train control","Simmulated annealing","Energy consumption","Train performance simulation","Civil Engineering"],"dc:title":["Optimal train control on various track alignments considering speed and schedule adherence constraints"],"dc:type":["Dissertation"],"thesis:degree_discipline":["Civil and Environmental Engineering"],"thesis:degree_name":["Doctor of Philosophy in Civil Engineering - (Ph.D.)"]},"updated_at":"2026-07-24T03:22:07Z"}