复杂网络链路危险度预测模型研究

Research on Prediction of Complex Networks Link Danger Level

提出了仅基于链路线形的危险链路预测模型,通过对链路线形数据的计算,得到相应的链路潜在危险程度,对新加入交通网络的链路进行预测,从而在碰撞发生之前进行相应的整治。实验选取自贡市檀木林—自来水厂路段为测试对象,通过分析其链路线形数据,探讨了该链路的危险性;同时,应用物理分析法和当量总碰撞法对结果进行验证比较。验证表明,该模型可以在不需要历史数据的情况下,有效准确地对危险链路进行预测。

Traffic networks consist of flow system, road system, and management system. From the point of complex networks, considering the road in traffic networks as link and the influx of links as node, we have measured the danger level of links. However, the methods mentioned above can only identify road black spots after traffic accidents happened and delay the time of identifying. In this paper, an improved identification model merely based on the structure of link is proposed. Our model can estimate potential danger level of link by computing the link structure data. We select a section of link from Tanmulin to Zilaishuichuang as the research object and analyze its structure and danger level. In addition, we verify the results with equivalent accident method and physics method. As results, the model can identify danger links only by the structure data of link efficiently.