An Efficient IoV Trajectory Compression Method in Vehicle Terminals Using Width-Direction-Angle

A highly efficient online compression of vehicle trajectories is important to the application of the Internet-of-Vehicles (IoV) system. However, the high time–space complexity of existing vehicle trajectory compression algorithms makes them unable to adapt effectively to actual IoV applications under the condition of a resource-constrained mobile vehicle terminal, bandwidth cost, and latency. This paper addresses these issues by proposing a trajectory compression algorithm using a combination of road width (
$W$
), vehicle driving direction (
$D$
), and swerve angle (
$A$
). The proposed WDA compression algorithm determines whether the vehicle trajectory points are rectilinear within a permitted error range according to
$W$
and
$D$
and then determines the trajectory points where a vehicle swerves significantly according to
$A$
. The algorithm considers the constraints of road shape on vehicle trajectories according to whether the trajectory forms an approximately straight line or a curve indicative of a swerving trajectory. It adopts different compression methods for rectilinear and swerving vehicle trajectories, which allows for highly efficient compression and high similarity between the compressed and original trajectories. In addition, the algorithm preserves direction information regarding
$D$
. Testing employing a Microsoft GeoLife dataset demonstrates that the proposed algorithm attains an average compression ratio of 4.03% for vehicle trajectory data, and the average compression time is 1.15 m/each. Relative to the existing compression algorithms, the proposed algorithm reduced compression time and storage space to adapt for the development of the large-scale IoV applications.