Stop plan optimisation for three-pattern skip-stop schemes for urban rail transit systems
Publikation: Beitrag in Fachzeitschrift › Forschungsartikel › Beigetragen › Begutachtung
Beitragende
Abstract
Mass rapid transit systems around the world are typically designed for all-stop operation schemes, in which train overtaking is not possible. To accelerate transit operation, the conventional A/B skip-stop scheme may be planned. This research explores alternative skip-stop schemes with three stop patterns, aiming to better match transit services with the spatial distribution of travel demand. The proposed generalised skip-stop operation model considers both the total cost of passengers and operator. A genetic algorithm is employed to solve the stop-plan optimisation problem, and a heuristic is tailored to determine an optimal dispatch headway for the respective stop plan. Based on computational experiments using synthetic data, the results suggest that skip-stop schemes have the potential to reduce total time costs by about 10%, particularly when there are structured demand concentrations, transit systems can operate safely with low time headway and short-distance demand is low. Although the total-cost saving of the best A/B skip-stop plan found is generally superior to those of other three-pattern skip-stop schemes, a three-pattern skip-stop scheme was found to offer a better total-cost saving in a scenario without short-distance travel demands. Overall, this research offers valuable insights into the potential benefits and limitations of different skip-stop schemes, contributing to a better understanding of their impact on passengers and operators.
Details
| Originalsprache | Englisch |
|---|---|
| Aufsatznummer | 100149 |
| Fachzeitschrift | EURO Journal on Transportation and Logistics |
| Jahrgang | 14 |
| Publikationsstatus | Veröffentlicht - 2025 |
| Peer-Review-Status | Ja |
| Extern publiziert | Ja |
Externe IDs
| Scopus | 85212196926 |
|---|
Schlagworte
Ziele für nachhaltige Entwicklung
ASJC Scopus Sachgebiete
Schlagwörter
- Genetic Algorithm, Public transportation, Skip-stop operation, Stop-plan optimisation, Urban rail transit