本文对移动互联交通诱导信息下的出行者路径选择行为进行SP调查，利用SPSS软件对影响因素进行筛选、剔除，并通过建立Logit回归模型预测出行者改变路径的概率，基于研究结果得出对制定交通诱导控制协同管理策略的启示。以路网行驶时间和延误时间最小之和为目标函数，建立交通诱导控制协同模型，通过遗传算法对协同模型算法进行优化设计，以桂林市一个包含四个交叉口的小型路网对模型进行实例分析，优化前后结果对比分析表明模型实现了路网总行程时间的减少，验证了模型的可行性。
The paper conducts SP survey on the traveler’s path selection behavior under the mobile Internet traffic guidance information, uses SPSS software to screen and eliminates the influencing factors, and predicts the probability of the traveler changing the path by establishing a Logit regression model. Enlightenment from the collaborative control strategy of induced control is concluded. Taking the minimum sum of road network travel time and delay time as the objective function, a traffic guidance control collaborative model is established, and the collaborative model algorithm is optimized by genetic algorithm. A small road network with four intersections in Guilin is used as an example to analyze the model. Comparative analysis of the results before and after optimization shows that the model achieves a reduction in the total travel time of the road network, which verifies the feasibility of the model.
