Intelligent transportation (eg, intelligent traffic light) makes our travel more convenient and
efficient. With the development of mobile Internet and position technologies, it is reasonable …

The advances in location-acquisition and mobile computing techniques have generated
massive spatial trajectory data, which represent the mobility of a diversity of moving objects …

Urban spatiotemporal flow prediction is of great importance to traffic management, land use,
public safety. This prediction task is affected by several complex and dynamic factors, such …

Map-matching algorithms integrate positioning data with spatial road network data (roadway
centrelines) to identify the correct link on which a vehicle is travelling and to determine the …

The advent of the Internet of Things has witnessed tremendous success in the application of
wireless sensor networks and ubiquitous computing for diverse smart-based applications …

The sharp rise in popularity of micro-mobility poses significant challenges in terms of
ensuring its safety, addressing its social impacts, mitigating its environmental effects, and …

Matching a raw GPS trajectory to roads on a digital map is often referred to as the Map
Matching problem. However, the occurrence of the low-sampling-rate trajectories (eg one …

Map-matching algorithms that utilise road segment connectivity along with other data (ie
position, speed and heading) in the process of map-matching are normally suitable for high …

Travelling is a critical component of daily life. With new technology, personalized travel route
recommendations are possible and have become a new research area. A personalized …

Current navigation systems/services allow drivers to keep track of their precise whereabouts
and provide optimal routes to reach specified locations. A reliable map-matching algorithm …