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为了有效解决城市交通中动态寻路时路况数据的安全可信问题,设计了基于路况数据分析的安全可信模型。该模型引入D-S证据理论,对不可信任的信息赋予了一定的不确定性属性,同时对相斥与相似同样界定出用于中间过渡的相容评价,在不增加数据交换的情况下,有效地实现了对路况信息信任判断,同时为了降低D-S证据理论的不确定性所引起的判断失误,该模型通过投票算法加以统计分析,增强了鲁棒性。通过仿真实验分析表明,在绝大多数情况下,该模型可以有效地优化车辆行车路线,降低行驶时间,在过滤异常路况信息、鉴别恶意信息方面,可以发挥重要作用,保证了第三方动态寻路算法的安全可信度。
In order to effectively solve the problem of safety and credibility of traffic data in dynamic road-finding in urban traffic, a safe and reliable model based on traffic data analysis is designed. This model introduces the theory of DS evidence to give untrustworthy information some indeterminacy attributes, and at the same time it can also define the compatible evaluation for the intermediate transitions between repudiation and similarity. Without increasing the data exchange, The trust judgment of traffic information is realized. In order to reduce the judgment error caused by the uncertainty of DS evidence theory, the model is statistically analyzed by voting algorithm, which enhances the robustness. Simulation results show that in most of the cases, this model can effectively optimize vehicle driving route and reduce driving time, and can play an important role in filtering abnormal traffic information and identifying malicious information, which ensures that third-party dynamic routing The safety and reliability of the algorithm.