High quality, reliable data and robust models are central to the development and appraisal
of transportation planning and policy. Although conventional data may offer good 'content', it …

ABSTRACT New Big Data sources such as mobile phone call data records, smart card data
and geo-coded social media records allow to observe and understand mobility behaviour on …

Recent advances in communication technologies have enabled researchers to collect travel
data based on ubiquitous and location-aware smartphones. These advances hold out the …

Mobility Patterns, Big Data and Transport Analytics provides a guide to the new analytical
framework and its relation to big data, focusing on capturing, predicting, visualizing and …

Traditional data acquisition methods, such as surveys and diaries, used in transportation
studies have become burdensome and inefficient in comparison to the emerging sources of …

Abstract Demand Responsive Transport (DRT), covering the first/last mile of a journey, plays
a pivotal role in the delivery of a seamless integrated door-to-door service, which is a …

The increasing demand for advanced modelling methods, which can reflect complex travel
activities of individuals, requires enhanced travel data collection methods. The introduction …

Traditional methods of travel data collection are often limited by high costs, infrequent
updates, or small sample sizes. Several emerging technologies, such as mobile phone …

Traditional approaches to trip generation modelling rely on household travel surveys which
are expensive and prone to reporting errors. On the other hand, mobile phone data, where …

Data play an indispensable role in transport modelling. The availability of data from non-
conventional sources, such as mobile phones, social media, and public transport smart …