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A Conceptual Framework for Developing the Smart Routing Recommendation Model on Flexible Public Transport (FPT) |
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| รหัสดีโอไอ | |
| Creator | Warattapop Thapatsuwan |
| Title | A Conceptual Framework for Developing the Smart Routing Recommendation Model on Flexible Public Transport (FPT) |
| Contributor | Patchanee Patitad, Jaruwat Patmanee, Sirikarn Chansombat |
| Publisher | Faculty of Logistics and Digital Supply Chain |
| Publication Year | 2566 |
| Journal Title | Journal of Logistics and Digital Supply Chain |
| Journal Vol. | 1 |
| Journal No. | 1 |
| Page no. | 37-49 |
| Keyword | Flexible public transport, Flexible routing, Vehicle routing model, Optimization method, Artificial Intelligence |
| URL Website | https://ph03.tci-thaijo.org/index.php/JLDSC/ |
| Website title | https://ldsc.nu.ac.th/?p=2725 |
| ISSN | ISSN 2985-0088 (Print) ISSN 2985-0096 (Online) |
| Abstract | A flexible public transportation system has the flexibility in the routing to pick up and drop off passengers with no fixed routes. Maximizing the efficiency of the transportation system requires the flexible routing that can direct a vehicle in the system to pick up passengers on request and re-routing the vehicles in the system in real time. This article discusses the model for the flexible vehicle routing for a flexible public transportation system and the application of artificial intelligence for forecasting the passenger demand. An artificial intelligence model, Long-Short-Term Memory (LSTM) is proposed for the forecast of the passenger demands and their locations. The flexible vehicle routing with LSTM will help improve the utilization of vehicles and the service level for the passengers. They can get picked up and drop-offs with the minimized time within the time-limit constraints. In addition, the model can be further developed into an algorithm, which can be implemented with information technologies to better manage a flexible public transportation system. |
