A survey of traffic prediction: from spatio-temporal data to intelligent transportation
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 …
efficient. With the development of mobile Internet and position technologies, it is reasonable …
A survey of localization methods for autonomous vehicles in highway scenarios
In the context of autonomous vehicles on highways, one of the first and most important tasks
is to localize the vehicle on the road. For this purpose, the vehicle needs to be able to take …
is to localize the vehicle on the road. For this purpose, the vehicle needs to be able to take …
Transformer-based map-matching model with limited labeled data using transfer-learning approach
In many spatial trajectory-based applications, it is necessary to map raw trajectory data
points onto road networks in digital maps, which is commonly referred to as a map-matching …
points onto road networks in digital maps, which is commonly referred to as a map-matching …
Fl-amm: Federated learning augmented map matching with heterogeneous cellular moving trajectories
Map matching is a fundamental component for location-based services (LBSs), such as
vehicle mobility analysis, navigation services, traffic scheduling, etc. In this paper, we …
vehicle mobility analysis, navigation services, traffic scheduling, etc. In this paper, we …
Rntrajrec: Road network enhanced trajectory recovery with spatial-temporal transformer
GPS trajectories are the essential foundations for many trajectory-based applications. Most
applications require a large number of high sample rate trajectories to achieve a good …
applications require a large number of high sample rate trajectories to achieve a good …
Deep spatial-temporal travel time prediction model based on trajectory feature
Research on travel time prediction shows its importance in the rational planning of travel
arrangements and traffic congestion mitigation. The scale of taxi and online ride-hailing …
arrangements and traffic congestion mitigation. The scale of taxi and online ride-hailing …
DMM: Fast map matching for cellular data
Map matching for cellular data is to transform a sequence of cell tower locations to a
trajectory on a road map. It is an essential processing step for many applications, such as …
trajectory on a road map. It is an essential processing step for many applications, such as …
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 …
L2mm: learning to map matching with deep models for low-quality gps trajectory data
Map matching is a fundamental research topic with the objective of aligning GPS trajectories
to paths on the road network. However, existing models fail to achieve satisfactory …
to paths on the road network. However, existing models fail to achieve satisfactory …
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 …