| _version_ | 1866902092030935040 |
|---|---|
| author | Couder-Castañeda, Carlos Padilla Pérez, Diego Alfredo Meléndez-Martínez, Jaime Saucedo-Jimenez, David |
| author_facet | Couder-Castañeda, Carlos Padilla Pérez, Diego Alfredo Meléndez-Martínez, Jaime Saucedo-Jimenez, David |
| contents | <p>This video presents a high-fidelity simulation of the baseline (normal operation) scenario for Mexico City Metro Line 4, developed using a discrete spatiotemporal modeling framework based on cellular automata and operational rules of urban rail systems.</p> <p>The simulation explicitly incorporates a <strong>progressive fleet deployment strategy</strong>, where trains are not initially distributed along the line but instead <strong>enter the system sequentially from terminal stations</strong>, one by one, during the early phase of operation. This reproduces realistic start-of-service conditions, where the system transitions from an empty state toward a steady operational regime.</p> <p>As the simulation evolves, trains gradually populate the network, leading to the emergence of stable headways and balanced directional service. This initialization phase is critical to capture transient dynamics that are typically ignored in steady-state analyses.</p> <p>The model reproduces the dynamic interaction between trains, stations, and passenger demand along the full corridor, considering infrastructure constraints, service frequencies, dwell times, and directional flow imbalances.</p> <p>The video illustrates the temporal evolution of key operational variables, including:</p> <ul> <li>Sequential train dispatch and network loading phase</li> <li>Train distribution along the line</li> <li>Passenger accumulation at stations</li> <li>Boarding and alighting processes</li> <li>Platform congestion levels</li> <li>Directional fleet balance</li> <li>Service regularity and headway stabilization</li> </ul> <p>The baseline scenario represents nominal operating conditions without disruptions and serves as a reference for comparative analysis against perturbation and recovery scenarios.</p> <p>The model was implemented computationally and validated through consistency checks with expected system behavior under progressive system loading and steady-state conditions.</p> <p>This material is intended as supplementary audiovisual content supporting research on urban rail system resilience, operational modeling, and intelligent transport systems.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19489515 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Simulation of Passenger Flow and Train Dynamics in Mexico City Metro Line 4 Using a Cellular Automaton Model Couder-Castañeda, Carlos Padilla Pérez, Diego Alfredo Meléndez-Martínez, Jaime Saucedo-Jimenez, David <p>This video presents a high-fidelity simulation of the baseline (normal operation) scenario for Mexico City Metro Line 4, developed using a discrete spatiotemporal modeling framework based on cellular automata and operational rules of urban rail systems.</p> <p>The simulation explicitly incorporates a <strong>progressive fleet deployment strategy</strong>, where trains are not initially distributed along the line but instead <strong>enter the system sequentially from terminal stations</strong>, one by one, during the early phase of operation. This reproduces realistic start-of-service conditions, where the system transitions from an empty state toward a steady operational regime.</p> <p>As the simulation evolves, trains gradually populate the network, leading to the emergence of stable headways and balanced directional service. This initialization phase is critical to capture transient dynamics that are typically ignored in steady-state analyses.</p> <p>The model reproduces the dynamic interaction between trains, stations, and passenger demand along the full corridor, considering infrastructure constraints, service frequencies, dwell times, and directional flow imbalances.</p> <p>The video illustrates the temporal evolution of key operational variables, including:</p> <ul> <li>Sequential train dispatch and network loading phase</li> <li>Train distribution along the line</li> <li>Passenger accumulation at stations</li> <li>Boarding and alighting processes</li> <li>Platform congestion levels</li> <li>Directional fleet balance</li> <li>Service regularity and headway stabilization</li> </ul> <p>The baseline scenario represents nominal operating conditions without disruptions and serves as a reference for comparative analysis against perturbation and recovery scenarios.</p> <p>The model was implemented computationally and validated through consistency checks with expected system behavior under progressive system loading and steady-state conditions.</p> <p>This material is intended as supplementary audiovisual content supporting research on urban rail system resilience, operational modeling, and intelligent transport systems.</p> |
| title | Simulation of Passenger Flow and Train Dynamics in Mexico City Metro Line 4 Using a Cellular Automaton Model |
| url | https://doi.org/10.5281/zenodo.19489515 |