Using metro smart card data to model location choice of after-work activities: An application to Shanghai

A location choice model explains how travellers choose their trip destinations especially for those activities which are flexible in space and time. The model is usually estimated using travel survey data; however, little is known about how to use smart card data (SCD) for this purpose in a public transport network. Our study extracted trip...

A robust transfer inference algorithm for public transport journeys during disruptions

Disruptions in public transport have major impact on passengers and disproportional effects on passenger satisfaction. The availability of smart card data gives opportunities to better quantify disruption impacts on passengers’ experienced journey travel time and comfort. For this, accurate journey inference from raw transaction data is required...

The construction of purpose-specific OD matrices using public transport smart card data

Around the world, more and more public transport operators opt for automated fare collection systems by means of smart cards. The data registered by such a system contain valuable information for transport planning. This research aims at increasing the usability of this data for the description of public transport travel demand. Travel demand is...

Data-driven public transport ridership prediction approach including comfort aspects

Data-driven public transport ridership prediction approach including comfort aspects

The most important aspects on which passengers base their choice whether to travel by public transport are the perceived travel time, costs, reliability and comfort. Despite its importance, comfort is often not explicitly considered when predicting demand for public transport. In this paper, we include comfort level in a modelling framework by...