Urban function classification at road segment level using taxi trajectory data: A graph convolutional neural network approach
Extracting hidden information from human mobility patterns is one of the long-standing
challenges of urban studies. In addition, exploring the relationship between urban functional …
challenges of urban studies. In addition, exploring the relationship between urban functional …
Analytical review of map matching algorithms: analyzing the performance and efficiency using road dataset of the indian subcontinent
Precise position information of moving entities on digital road networks is a vital requirement
of location-based applications. Location information received from Global Positioning …
of location-based applications. Location information received from Global Positioning …
Deep learning for trajectory data management and mining: A survey and beyond
Trajectory computing is a pivotal domain encompassing trajectory data management and
mining, garnering widespread attention due to its crucial role in various practical …
mining, garnering widespread attention due to its crucial role in various practical …
Learning effective road network representation with hierarchical graph neural networks
Road network is the core component of urban transportation, and it is widely useful in
various traffic-related systems and applications. Due to its important role, it is essential to …
various traffic-related systems and applications. Due to its important role, it is essential to …
Self-supervised trajectory representation learning with temporal regularities and travel semantics
Trajectory Representation Learning (TRL) is a powerful tool for spatial-temporal data
analysis and management. TRL aims to convert complicated raw trajectories into low …
analysis and management. TRL aims to convert complicated raw trajectories into low …
STGNN-TTE: Travel time estimation via spatial–temporal graph neural network
Estimating the travel time of urban trajectories is a basic but challenging task in many
intelligent transportation systems, which is the foundation of route planning and traffic …
intelligent transportation systems, which is the foundation of route planning and traffic …
Synmob: Creating high-fidelity synthetic gps trajectory dataset for urban mobility analysis
Urban mobility analysis has been extensively studied in the past decade using a vast
amount of GPS trajectory data, which reveals hidden patterns in movement and human …
amount of GPS trajectory data, which reveals hidden patterns in movement and human …
Identifying spatiotemporal characteristics and driving factors for road traffic CO2 emissions
Road traffic is an important contributor to CO 2 emissions. Previous studies lack enough
spatiotemporal resolution in emission calculation at the road level and ignore the impact of …
spatiotemporal resolution in emission calculation at the road level and ignore the impact of …
Traffic light optimization with low penetration rate vehicle trajectory data
Traffic light optimization is known to be a cost-effective method for reducing congestion and
energy consumption in urban areas without changing physical road infrastructure. However …
energy consumption in urban areas without changing physical road infrastructure. However …
Empowering A* search algorithms with neural networks for personalized route recommendation
Personalized Route Recommendation (PRR) aims to generate user-specific route
suggestions in response to users' route queries. Early studies cast the PRR task as a …
suggestions in response to users' route queries. Early studies cast the PRR task as a …