Trace Interpolation Algorithm Based on Intersection Vehicle Movement Modeling

Jinwei Shen, Guangtao Xue
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引用次数: 3

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.
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基于交叉口车辆运动建模的轨迹插值算法
真实车辆跟踪数据在车辆传感器网络路由研究中起着重要作用。然而,大多数车辆跟踪数据是周期性采集的,不能满足许多应用对实时性的要求。现有的轨迹插值算法大多采用均匀插值方法,存在精度低的问题。从我们的观察来看,交叉口车辆的状态对车辆的运动至关重要。本文提出了一种新的轨迹插值算法。该算法利用交叉口车辆运动建模(IVMM)和速度数据挖掘(VDM)辅助插值处理。用车载GPS实测数据对该算法进行了验证。结果表明,该算法比传统的轨迹插值算法具有更高的精度。
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