Ride-hailing platforms (eg, Uber and Didi Chuxing) have become increasingly popular in
recent years. Efficiency has always been an important metric for such platforms. However …

Trajectory computing is a pivotal domain encompassing trajectory data management and
mining, garnering widespread attention due to its crucial role in various practical …

Self-supervised representation learning (SSRL) concerns the problem of learning a useful
data representation without the requirement for labelled or annotated data. This …

Recent years have witnessed a large amount of decentralized data in various (edge)
devices of end-users, while the decentralized data aggregation remains complicated for …

Estimating the time of arrival is a crucial task in intelligent transportation systems. Although
considerable efforts have been made to solve this problem, most of them decompose a …

Service time is a part of time cost in the last-mile delivery, which is the time spent on
delivering parcels at a certain location. Predicting the service time is fundamental for many …

The ride-hailing service offered by mobility-on-demand platforms, such as Uber and Didi
Chuxing, has greatly facilitated people's traveling and commuting, and become increasingly …

Estimated time of arrival (ETA) prediction, also known as travel time estimation, is a
fundamental task for a wide range of intelligent transportation applications, such as …

Estimated time of arrival (ETA) is one of the critical services offered by navigation and hailing
providers. The majority of existing solutions approach ETA as a regression problem and …

Mobile map apps such as the Baidu Maps app have become a ubiquitous and essential tool
for users to find optimal routes and get turn-by-turn navigation services while driving …