山区高速公路团雾路段行车风险耦合关系解构与前馈诱导控制研究

团雾被称为高速公路上的“流动杀手”。对于道路线形复杂的山区高速公路，由于不确定性因素众多，团雾危害更甚，行车安全和运输效率受到显著影响。本项目拟在资料收集和交通事故数据统计分析基础上，综合采用驾驶模拟试验和实车试验、数值模拟等手段，首先分析团雾路段典型特征和影响行车安全的主要因素，以及各主要因素之间的拓扑关系，进行团雾路段行车风险耦合关系解构，构建团雾段行车风险评估模型；然后从时间、空间、团雾环境和人因四个维度，分析驾驶人在遭遇团雾后出现的视觉心理变化特征，结合能见度及多维参数突变耦合作用后的驾驶视觉诱导需求，构建诱导需求模型；最后分析动态团雾环境下，驾驶人视觉信息的传导阻滞原因，阐明突发团雾环境下诱导系统与驾驶人之间的动态沟通和反馈信息传导机制，构建团雾环境前馈诱导信息传导控制模型。研究结果可为高速公路低能见度环境的行车诱导提供新思路，有助于最大限度地降低山区高速公路团雾段的行车风险。

Local fog is known as the "flow killer" on the expressway. For the mountainous expressway with complex road alignment, due to many uncertain factors, the harm of local fog is more serious, and the driving safety risk and transportation efficiency are significantly affected. Based on data collection and traffic accident data statistics and analysis and comprehensively adopt driving simulation test, real vehicle test and numerical simulation, this project firstly analyzes the typical characteristics of local fog section and the main factors affecting driving safety, as well as the topological relationship between the main factors, deconstructs the driving risk coupling relationship of local fog section, deduces the traffic accidents possibly induced by local fog, and construct risk assessment model of driving in the expressway local dense fog; Then, from the four dimensions of time, space, local fog environment and human factors, the characteristics of drivers' visual psychological changes after encountering local fog are analyzed. Combined with the coupling effect of visibility and mufti-dimensional parameter mutation, the driving visual guidance demand model is constructed. Finally, the causes of visual information conduction block in the dynamic local fog environment are analyzed, the dynamic communication and feedback information transmission mechanism between the guidance system and the driver in sudden local fog environment are clarified, and the feed-forward guidance information transmission control model in the local fog environment is constructed. The research results can provide a new idea for traffic guidance in low visibility environment, and help to minimize the driving risk in the local fog section of mountainous expressway.