In this paper, a new practice-ready method for the real-time estimation of traffic conditions
and travel times on highways is introduced. First, after a principal component analysis …

Forecasting short-term ridership of different origin-destination pairs (ie, OD matrix) is crucial
to the real-time operation of a metro system. However, this problem is notoriously difficult …

Travel time analysis and prediction are keystones for building intelligent transportation
systems in the new era, which has gained wide attention from the research community. Over …

Predicting how long a trip will take may allow travelers plan ahead, save money, and avoid
traffic congestion. The journey time estimation model should take into account three crucial …

One of the main lines of research in the discipline of mobility mining is the development of
predictors able to anticipate human travel behaviour in great detail. However, access to the …

Travel time is a major information in support of Transportation System Management and
Operations (TSMO). Accurate travel time information extracted from probe data sources …

Nowadays, the anticipation of human mobility flow has important applications in many
domains ranging from urban planning to epidemiology. Because of the high predictability of …

This paper presents a distribution-free reliability-based prediction approach for estimating
journey time intervals with multi-source data using a two-stream deep learning framework …

We are witnessing an increasing need to accurately measure people's mobility as it has
become an instrumental factor for the development of innovative services in multiple …

Accurate short-term traffic prediction plays a pivotal role in various smart mobility operation
and management systems. Currently, most of the state-of-the-art prediction models are …