Trajectory data collected from probe vehicles become increasingly important for urban traffic
operation and management. However, current data tend to be sparse in time and space due …

Data from connected probe vehicles can be critical in estimating road traffic conditions.
Unfortunately, current available data is usually sparse due to the low reporting frequency …

With trajectory data, a complete microscopic and macroscopic picture of traffic flow
operations can be obtained. However, trajectory data are difficult to observe over large …

Vehicle behavior learning can be used in video surveillance systems to identify normal and
abnormal vehicle motion patterns for the management of traffic operations, public services …

Automatic vehicle identification (AVI) can provide partial vehicle path data by matching the
vehicle license plate on the detected links. However, the matched samples will rapidly …

Accurate information of path followed by vehicles at several real-life scenarios is essential
for modeling and testing the optimal path for autonomous vehicles, analyzing the lateral …

Vehicle trajectories can provide a clear picture of the traffic flow that plays a pivotal role in
traffic management and control. Two types of traffic sensors, ie, fixed and mobile sensors …

The paper develops a novel approach to construct vehicle trajectories using real-time and
historical traffic data to predict dynamic travel times. The approach combines real-time and …

The origin–destination (OD) matrix and the vehicle trajectory data are critical to
transportation planning, design, and operation management. On the basis of the deployment …

Vehicle trajectories with high spatial and temporal resolution are known as the most ideal
source of data for developing innovative microscopic traffic models. Aside from the method …