Accurate traffic state (ie, flow, speed, density, etc.) on an urban road network is important
information for urban traffic control and management strategies. However, due to the …

The Internet of Things (IoT) holds great promises to provide an edge cutting technology that
enables numerous innovative services related to healthcare, manufacturing, smart cities and …

When planning routes, drivers usually consider a multitude of different travel costs, eg,
distances, travel times, and fuel consumption. Different drivers may choose different routes …

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 …

Innovations in transportation, such as mobility-on-demand services and autonomous driving,
call for high-resolution routing that relies on an accurate representation of travel time …

The monitoring of a system can yield a set of measurements that can be modeled as a
collection of time series. These time series are often sparse, due to missing measurements …

Different uses of a road network call for the consideration of different travel costs: in route
planning, travel time and distance are typically considered, and green house gas (GHG) …

Motivated by the increasing availability of vehicle trajectory data, we propose learn-to-route,
a comprehensive trajectory-based routing solution. Specifically, we first construct a graph …

With the growing volumes of vehicle trajectory data, it becomes increasingly possible to
capture time-varying and uncertain travel costs, eg, travel time, in a road network. The …

Data are increasingly available that enable detailed capture of travel costs associated with
the movements of vehicles in road networks, notably travel time, and greenhouse gas …