Real-time vehicle scheduling in bus rapid transit systems using distributed artificial intelligence
This project is focused on Bus Rapid Transits Systems (BRTS), which is a modem transportation System important for urban traffic development. In fact, BRT Systems have become popular in many countries, reaching 160 cities around the world. BRT systems have two components, design and operational plan...
| Autor Principal: | Galindo Acuña, David Esteban |
|---|---|
| Otros Autores: | Plazas Bernat, Sylvia Paola |
| Formato: | Trabajo de grado |
| Publicado: |
Pontificia Universidad Javeriana
2018
|
| Materias: | |
| Acceso en línea: |
http://hdl.handle.net/10554/38377 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| Sumario: |
This project is focused on Bus Rapid Transits Systems (BRTS), which is a modem transportation System important for urban traffic development. In fact, BRT Systems have become popular in many countries, reaching 160 cities around the world. BRT systems have two components, design and operational planning. One key problem of operational planning is the Vehicle Scheduling Problem (VSP), which aims to plan vehicle trips. If the VSP is solved in an effective way, it can also have a positive impact on operation costs such as fuel consumption, the carbon foot-print, driver’s wages, number of purchased vehicles, and by all means, the quality of service. In this project, the VSP will be analyzed through a decentralized architecture using Distributed Artificial Intelligence (DAI). The main purpose is to allow the VSP to work in real time, making each part of the system capable to adapt and evolve, thus favoring reactivity to perturbations and constant changes. The propose approach will be validated using a case study based on a Colombian BRT. |
|---|