随着交通安全、尾气排放及路权公平性问题日益获得重视，信号交叉口的管控目标逐渐从“畅通”过渡到“畅通、安全、绿色、和谐”。本课题基于仿真优化框架，研究融合多准则考量的路网信控鲁棒优化方法。首先，搭建多精度交通仿真平台，并采用多源异构交通数据从多角度对其进行标定和验证，保证交通仿真平台的可靠性与推广性。然后，选取合理的效率、安全、排放与公平评价方法，建立不确定环境下多目标路网信控优化模型，并与多精度交通仿真平台构成仿真优化系统。之后，引入宏、微观交通仿真模型的切换机制、替代模型及其更新管理机制，设计低成本的多目标鲁棒优化算法，获取关于多准则考量的帕累托最优解，并比较分析不同场景下信号控制参数及控制效果的差异，为满足多样化管控目标的信控鲁棒优化提供理论依据和技术支撑。

With growing attention paid to the traffic safety, vehicular emissions and equity of right of way, the management and control target for signalized intersections gradually changes from “Smooth” to “Smooth, Safe, Green, Harmonious”. This project studies the multi-criteria oriented robust optimization method for road network signal control, based on the simulation-based optimization framework. Firstly, the multi-fidelity traffic simulation platform is built, and then calibrated and validated from various aspects with multi-source heterogeneous traffic data. This aims to guarantee the reliability and generalization of this traffic simulation platform. Later, with the reasonable choices of evaluation methods for traffic efficiency, safety, emissions and equity, the multi-objectives oriented road network signal control optimization model is constructed under uncertainties, along with which the multi-fidelity traffic simulation platform is used to set up the simulation-based optimization system. After that, with the introduction of switch mechanism between macro- and micro- traffic simulation models, surrogate models and their updating management mechanism, the low-cost multi-objective robust optimization algorithm is designed to obtain the Pareto optimality with respective to multi-criteria. Finally, the signal control parameters and consequents under various scenarios are compared and analyzed. These methods and results will provide theoretical basis and technical foundation for robust optimization of signal control that satisfies the diversified management and control objectives.