In recent years, online ride-hailing services have emerged as an important component of
urban transportation system, which not only provide significant ease for residents' travel …

Shared mobility has emerged as a sustainable alternative to both private transportation and
traditional public transport, promising to reduce the number of private vehicles on roads …

Deep Learning methods have been proven to be flexible to model complex phenomena.
This has also been the case of Intelligent Transportation Systems, in which several areas …

The estimated time of arrival (ETA) plays a vital role in intelligent transportation systems and
has been widely used as a basic service in ride-hailing platforms. Obtaining a precise ETA is …

Travel time estimation (TTE) is a crucial and challenging task due to the complex spatial and
dynamic temporal correlations between local and global traffic regions. Though many …

Accurate travel time prediction is one of the most promising intelligent transportation system
(ITS) services, which can greatly support route planning, ride‐sharing, navigation …

Travel time forecasting has become a core component of smart transportation systems,
which assists both travelers and traffic organizers with route planning, travel schedule …

With millions of people using ride-hailing platforms for daily travel, estimated time of arrival
(ETA) has become a significant problem in intelligent transportation systems and attracted …

With the rapid development of artificial intelligence and the Internet of Things technology, the
automatic music composition system has become a hot topic of research. This paper …

Predicting the estimated time of arrival (ETA) is crucial for ride-hailing platforms and
autonomous vehicle systems. Although deep neural network-based models have …