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通过公路上安装的传感器采集数据,从而估算出车辆的行驶时间并求取最优路径,可以方便人们的出行.根据某段公路上传感器提供的数据分析了该段公路的交通状况,建立微分方程模型和关联度分析模型分析交通状况特征及相互影响,并利用ARIMA模型对速度进行了预测.通过对交通干线图进行分析,在假定各路段上的运行时间为独立的随机变量、考虑路段间的相互影响和根据给定的条件这三种情况下,分别建立模型用于估计跟路段通过时间和寻找最优路径,求解得到理想的结果.所建立模型有较强的实用性,有一定的参考作用.
Through the sensor installed on the road to collect data to estimate the vehicle’s driving time and find the optimal path, which can facilitate people’s travel.According to the data provided by sensors on a section of the road, the traffic conditions of the section of the highway are analyzed, and the differential equation Model and correlation analysis model are used to analyze the traffic characteristics and the mutual influence and the ARIMA model is used to predict the speed.According to the analysis of traffic arteries, the running time on each road segment is assumed to be an independent random variable, Mutual influence and under the given conditions under the three cases, respectively, to establish a model for estimating the passage with the passage of time and find the optimal path, the solution obtained by the ideal results of the established model has strong practicality, with some reference effect.