Graph neural networks as strategic transport modelling alternative‐A proof of concept for a surrogate
S Narayanan, N Makarov… - IET Intelligent Transport …, 2024 - Wiley Online Library
Practical applications of graph neural networks (GNNs) in transportation are still a niche
field. There exists a significant overlap between the potential of GNNs and the issues in …
field. There exists a significant overlap between the potential of GNNs and the issues in …
Specifics of Creating a Public Transport Demand Model for Low-Density Regions: Lithuanian Case
J Ranceva, R Ušpalytė-Vitkūnienė - Sustainability, 2024 - mdpi.com
A transport model usually consists of a demand model and an available transport network
model. The purpose of this article is to identify the key specifics for the development of a …
model. The purpose of this article is to identify the key specifics for the development of a …
Graph neural network surrogate for strategic transport planning
As the complexities of urban environments continue to grow, the modelling of transportation
systems become increasingly challenging. This paper explores the application of advanced …
systems become increasingly challenging. This paper explores the application of advanced …
Who does new trips and why?: An analysis toward the modeling of induced demand
V Kalliga, S Narayanan, C Antoniou - Transportation Letters, 2024 - Taylor & Francis
Improvements in infrastructure capacity and travel conditions including the introduction of a
new transport mode can induce changes in traffic. Although this can occur through a variety …
new transport mode can induce changes in traffic. Although this can occur through a variety …