Recurrent Neural-Based Vehicle Demand Forecasting and Relocation Optimization for Car-Sharing System: A Real Use Case in Thailand
A car-sharing system has been playing an important role as an alternative transport mode in order to avoid traffic congestion and pollution due to a quick growth of usage of private cars. In this paper, we propose a novel vehicle relocation system with a major improvement in threefolds: (i) data pre...
Saved in:
| Main Authors: | Peerapon Vateekul, Panyawut Sri-iesaranusorn, Pawit Aiemvaravutigul, Adsadawut Chanakitkarnchok, Kultida Rojviboonchai |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
|
| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2021/8885671 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
vConnect: V2V Connectivity Prediction and Independent Task Offloading Framework in Vehicular Edge Computing
by: Adsadawut Chanakitkarnchok, et al.
Published: (2025-01-01) -
Demand Management of Station-Based Car Sharing System Based on Deep Learning Forecasting
by: Daben Yu, et al.
Published: (2020-01-01) -
Location deployment of depots and resource relocation for connected car-sharing systems through mobile edge computing
by: Xiaolu Zhu, et al.
Published: (2017-06-01) -
Explainable Spatio-Temporal Inference Network for Car-Sharing Demand Prediction
by: Nihad Brahimi, et al.
Published: (2025-04-01) -
Relocation Optimization for Shared Electric Vehicles: A Literature Review
by: Ye Zou, et al.
Published: (2025-02-01)