考虑驾驶员动态响应行为的城市快速路群体交通诱导理论研究

Understanding realistic drivers’ group dynamic response behavior exactly and in real time, and providing effective and reliable routing message to improve travel reliability and system performance of urban expressway network, is a key scientific issue of implementing active group traffic routing. In view of the fact that exactly describing drivers’ group dynamic response behavior in realistic complex traffic conditions is lack in previous group routing theory and application, this project will put forward an improved new model. Firstly, the interaction mechanism of group routing message, drivers’ response behavior, and network traffic state will be analyzed, a network traffic state evolution model considering drivers’ group dynamic response behavior for group traffic routing will be proposed. Secondly, the method of providing effective and reliable routing message is studied, and a group traffic routing mechanism that is consistent with drivers’ dynamic response behavior will be founded. Thirdly, a method and theory for calibrating drivers’ group dynamic response behavior based on multi-source detected traffic data and travel scenario reconstructing in realistic complex traffic conditions will be studied, and a drivers’ group dynamic response behavior model will be founded. Fourthly, a group traffic routing model that is consistent with drivers’ dynamic response behavior will be founded and a spatio-temporal coordination method for traffic routing strategies will be proposed. Finally, a group traffic coordination routing theory considering drivers’ dynamic response behavior on urban expressway will be finished, and the goal of improving travel reliability and system performance of urban expressway will be achieved by providing effective and reliable routing message. The prospective results of this project can academically enrich and improve the group traffic routing theory and also provide theoretical support for active traffic management in practice.

实时、准确地掌握驾驶员群体的动态响应行为，进而提供有效可靠的诱导信息来提升城市快速路出行可靠性和系统性能，是实施主动式群体交通诱导的核心问题。本项目针对以往群体交通诱导理论研究和实践中，对驾驶员群体实际动态响应行为考虑不足问题，解析群体诱导信息、驾驶员响应行为和网络交通状态的相互作用机理，建立以驾驶员群体动态响应行为为输入变量的网络交通状态演化模型；研究提供有效、可靠诱导信息的方法，提出与驾驶员动态响应行为一致的群体交通诱导机制；研究现实复杂交通环境下，基于多源检测数据和出行场景重构的驾驶员群体响应行为辨识方法，并建立动态模型；以此建立群体交通诱导模型，提出诱导策略时空协同优化方法，形成考虑驾驶员动态响应行为的城市快速路群体交通诱导理论，实现提升城市快速路出行可靠性和系统性能的目的。项目研究成果在学术上可以丰富和完善群体交通诱导理论体系，在实践中为管理者制定主动式交通管理策略提供理论支持。

实时、准确地掌握驾驶员群体的动态响应行为，进而提供有效可靠的诱导信息来提升城市快速路出行可靠性和系统性能，是实施主动式群体交通诱导的核心问题。解析群体诱导信息、驾驶员响应行为和网络交通状态的相互作用机理，采用一个双层决策结构来描述群体交通诱导控制器和驾驶员行为决策，提出与驾驶员动态响应行为一致的群体交通诱导机制，建立以驾驶员群体动态响应行为为输入变量的网络交通状态演化模型。利用多源检测数据和出行场景重构的方法来辨识驾驶员群体响应行为，建立现实交通环境下驾驶员响应行为模型，并提出模型参数动态更新方法。以此建立与驾驶员动态响应行为一致的群体交通诱导模型，提出诱导策略时空协同优化方法，形成考虑驾驶员动态响应行为的城市快速路群体交通诱导理论。研究结果表明群体诱导信息下驾驶员的响应行为除了和信息内容有关外，还与时段、实际道路交通状况、信息提供策略等因素有关，驾驶员动态响应行为模型可以追踪驾驶员响应行为的演化过程。考虑驾驶员响应行为的交通状态预测模型能够准确地估计驾驶员对交通信息的反应，以及真实交通状态对交通预测的影响，提高了信息提供下交通状态预测的准确性。考虑驾驶员动态响应行为对诱导信息下网络流量状态的影响，是保证群体交通诱导系统可持续利用的必要条件。与传统的诱导模型相比，考虑驾驶员动态响应行为的群体交通诱导模型考虑了系统的目标和实际的路径分流行为，能够提供更好的系统性能，并保证群体交通诱导系统的可持续性。项目研究成果在学术上可以丰富和完善群体交通诱导理论体系，在实践中为管理者制定拥挤交通条件下的主动式交通管理策略提供依据，实现考虑驾驶员动态响应行为的区域群体交通时空协同诱导，对于提高交通运行效率和出行可靠度，提升智慧化交通管理水平具有重要现实意义，将会产生良好的经济和社会效益。