Massive and redundant vehicle trajectory data are continuously sent to the data center via
vehicle-mounted GPS devices, causing a number of sustainable issues, such as storage …

With the growing use of crowdsourced location data from smartphones for transportation
applications, the task of map-matching raw location sequence data to travel paths in the …

This work shows how map-matching helps to minimize errors in GPS data by finding the
most probable corresponding points of the recorded waypoints of a trajectory on a road …

Abstract Massive and passive Automatic Vehicle Identification (AVI) data provides samples
of whereabouts and movements of vehicles, which is a potential source of information for …

With an ever-increasing deployment density of probe and fixed sensors, massive vehicular
trajectory data is available and show a promising foundation to improve the observability of …

Lane-level road network updating is crucial for urban traffic applications that use geographic
information systems contributing to, for example, intelligent driving, route planning and traffic …

Map matching is to locate GPS trajectories onto the road networks, which is an important
preprocessing step for many applications based on GPS trajectories. Currently, hidden …

Background With the growth of trajectory data, the large amount of data causes a lot of
problems with storage, analysis, mining, etc. Most of the traditional trajectory data …

A myriad of connected vehicles collects large-scale telematics data throughout cities,
enabling data-based infrastructure planning. To truly benefit from this emerging technology …

Daily itinerary, consisting of an individual's trips and activities on a day, is usually
fundamental input for many travel demand models. However, current research lacks …