The two fields of urban planning and artificial intelligence (AI) arose and developed
separately. However, there is now cross-pollination and increasing interest in both fields to …

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

Driving behaviour understanding is of vital importance in improving transportation safety and
promoting the development of Intelligent Transportation Systems (ITS). As a long-standing …

Transportation simulation is non-trivial due to the co-existence of thousands of
heterogeneous decision makers (or vehicles). Such large-scale decision making is …

Urban planning refers to the efforts of designing land-use configurations. Effective urban
planning can help to mitigate the operational and social vulnerability of a urban system …

Urban planning refers to the efforts of designing land-use configurations given a region.
However, to obtain effective urban plans, urban experts have to spend much time and effort …

Predicting traffic accidents can help traffic management departments respond to sudden
traffic situations promptly, improve drivers' vigilance, and reduce losses caused by traffic …

Trajectory-User Linking (TUL) is crucial for human mobility modeling by linking different
trajectories to users with the exploration of complex mobility patterns. Existing works mainly …

Despite the tremendous growth of the transportation sector, the availability of systems that
ensure safe, efficient, sustainable transportation reduces traffic congestion, maintenance …

Accurate urban flow prediction (UFP) is crucial for a range of smart city applications such as
traffic management, urban planning, and risk assessment. To capture the intrinsic …