为解决传统旅游交通管理缺乏广泛互联互通而存在管理滞后、资源分配不合理等问题,建立智慧旅游公路平台系统架构。将地理信息系统(geographic information systems,GIS)、大数据与人工智能等新一代信息技术概念引入旅游公路管理,旨在构...为解决传统旅游交通管理缺乏广泛互联互通而存在管理滞后、资源分配不合理等问题,建立智慧旅游公路平台系统架构。将地理信息系统(geographic information systems,GIS)、大数据与人工智能等新一代信息技术概念引入旅游公路管理,旨在构建一个集感知设备、数据通信、决策中心和可视界面于一体的智慧旅游公路平台,实现实时感知交通情况、高效数据通信、智能决策支持和直观可视化展示,以提升旅游公路的管理效能、交通安全性和游客体验。结果表明,该研究对于推动旅游业的创新发展和可持续发展具有重要意义。展开更多
To explore the influence of intelligent highways and advanced traveler information systems(ATIS)on path choice behavior,a day-to-day(DTD)traffic flow evolution model with information from intelligent highways and ATIS...To explore the influence of intelligent highways and advanced traveler information systems(ATIS)on path choice behavior,a day-to-day(DTD)traffic flow evolution model with information from intelligent highways and ATIS is proposed,whereby the network reliability and experiential learning theory are introduced into the decision process for the travelers’route choice.The intelligent highway serves all the travelers who drive on it,whereas ATIS serves vehicles equipped with information systems.Travelers who drive on intelligent highways or vehicles equipped with ATIS determine their trip routes based on real-time traffic information,whereas other travelers use both the road network conditions from the previous day and historical travel experience to choose a route.Both roadway capacity degradation and travel demand fluctuations are considered to demonstrate the uncertainties in the network.The theory of traffic network flow is developed to build a DTD model considering information from intelligent highway and ATIS.The fixed point theorem is adopted to investigate the equivalence,existence and stability of the proposed DTD model.Numerical examples illustrate that using a high confidence level and weight parameter for the traffic flow reduces the stability of the proposed model.The traffic flow reaches a steady state as travelers’routes shift with repetitive learning of road conditions.The proposed model can be used to formulate scientific traffic organization and diversion schemes during road expansion or reconstruction.展开更多
文摘为解决传统旅游交通管理缺乏广泛互联互通而存在管理滞后、资源分配不合理等问题,建立智慧旅游公路平台系统架构。将地理信息系统(geographic information systems,GIS)、大数据与人工智能等新一代信息技术概念引入旅游公路管理,旨在构建一个集感知设备、数据通信、决策中心和可视界面于一体的智慧旅游公路平台,实现实时感知交通情况、高效数据通信、智能决策支持和直观可视化展示,以提升旅游公路的管理效能、交通安全性和游客体验。结果表明,该研究对于推动旅游业的创新发展和可持续发展具有重要意义。
基金Project(71801115)supported by the National Natural Science Foundation of ChinaProject(2021M691311)supported by the Postdoctoral Science Foundation of ChinaProject(111041000000180001210102)supported by the Central Public Interest Scientific Institution Basal Research Fund,China。
文摘To explore the influence of intelligent highways and advanced traveler information systems(ATIS)on path choice behavior,a day-to-day(DTD)traffic flow evolution model with information from intelligent highways and ATIS is proposed,whereby the network reliability and experiential learning theory are introduced into the decision process for the travelers’route choice.The intelligent highway serves all the travelers who drive on it,whereas ATIS serves vehicles equipped with information systems.Travelers who drive on intelligent highways or vehicles equipped with ATIS determine their trip routes based on real-time traffic information,whereas other travelers use both the road network conditions from the previous day and historical travel experience to choose a route.Both roadway capacity degradation and travel demand fluctuations are considered to demonstrate the uncertainties in the network.The theory of traffic network flow is developed to build a DTD model considering information from intelligent highway and ATIS.The fixed point theorem is adopted to investigate the equivalence,existence and stability of the proposed DTD model.Numerical examples illustrate that using a high confidence level and weight parameter for the traffic flow reduces the stability of the proposed model.The traffic flow reaches a steady state as travelers’routes shift with repetitive learning of road conditions.The proposed model can be used to formulate scientific traffic organization and diversion schemes during road expansion or reconstruction.
