An Explainable Network-wide Metro Passenger Delay Prediction Model

Integrated Synchromodal Transport Planning and Preference Learning

A comprehensive understanding of shippers’ preferences can help transport freight forwarders create targeted transport services and enhance long-term business relationships. Nevertheless, limited research examined the benefit of considering shippers’ preferences in the decision-making of synchromodal transport planning and the collection of...

Public Transport Delay Pattern Analysis By Unsupervised Learning Approach

To analyze latent multiple specific patterns in the line-based public transport daily delay occurrence, a data-driven explorative analysis of public transport daily delay spatial-temporal distribution pattern is performed based on the k-means clustering algorithm. Firstly, we used aggregated daily delay profile to visualize how the delay is...

Extracting insights from black box neural networks for network-wide traffic predictions

Accurate and trustworthy short-term traffic prediction is crucial in the modern world for the comfort of drivers and decision-makers as it is used to improve the performance of traffic management systems, lessen congestion, increase safety, and shorten journey times. It is possible to discover useful information for network transportation...

Integrated fast-charging facility planning: a case study in Amsterdam

With the electrification in freight transportation, fast-charging facilities are crucial to support enroute charging for long-distance freight trips. The goal of this study is to develop an integrated fast-charging facility planning framework to prepare for the increasing enroute freight charging demand in the Netherlands. Based on highway...

Including service information in a topological comparison of metro networks worldwide: A comparison of 51 metro networks worldwide using GTFS static data

Public transport (PT) plays a vital role in commuting billions of travellers in cities all over the world, providing a mode that is both sustainable and accessible. Metro networks are especially apt at this considering their high-capacity and high-speed operation in urban environments. Comparing different metro networks to one another is a...

Improving the Service of E-bike Sharing by Demand Pattern Analysis: A Data-driven Approach

E-bike sharing has gradually gained popularity in recent years, while the research in this field is still quite limited. This study applies data-driven methods, mainly demand pattern analysis, to facilitate the development of operational strategies in a cost-effective and operator-friendly way. Demand pattern is analysed in an innovative spatial...

Exploring Demand Patterns of a Ride-Sourcing Service using Spatial and Temporal Clustering

On-demand transit has become a common mode of transport with ride-sourcing companies like Uber, Lyft, Didi transforming the way we move. With the increase in popularity for such services, the supply needs to adapt according to the demand. For this, the demand needs to analyzed to examine if there are recurrent patterns in them; making it...