Abstract
Real vehicle tracking data play an important role in the research of routing in vehicle sensor networks. Most of the vehicle tracking data, however, were collected periodically and could not meet the requirements of real-time by many applications. Most of the existing trace interpolation algorithms use uniform interpolation methods and have low accuracy problem. From our observation, intersection vehicle status is critical to the vehicle movement. In this paper, we proposed a novel trace interpolation algorithm. Our algorithm used intersection vehicle movement modeling (IVMM) and velocity data mining (VDM) to assist the interpolation process. The algorithm is evaluated with real vehicle GPS data. Results show that our algorithm has much higher accuracy than traditional trace interpolation algorithms.
Highlights
Vehicular AdHoc Network (VANET) is a special kind of Delay-tolerant Network (DTN)
Intersection vehicle status is critical to the vehicle movement
We proposed a novel trace interpolation algorithm
Summary
Vehicular AdHoc Network (VANET) is a special kind of Delay-tolerant Network (DTN). Because of the uncertainty and high mobility of VANET, routing and data sharing in VANET are quite different from MANET. Most published works [8] about vehicle trace interpolation use uniform interpolation method It assumes that the vehicle moves with the same velocity or with a uniform acceleration/deceleration velocity between two consecutive real records. Uniform interpolation method has one obvious problem: it cannot represent the actual vehicle trace, for the vehicle may had a process of deceleration and acceleration or even stops between two consecutive records. Some routing and data delivering algorithms [9,10,11] in VANET uses a special technique which was mostly called “intersection buffering”, this method relies on the underlying feature of vehicle mobility: vehicles tend to emerge at intersections because of the intersection traffic light.
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