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一种支持城市路网交通关系自动化的智能模型
  • 期刊名称:测绘学报
  • 时间:0
  • 页码:520-526
  • 语言:中文
  • 分类:P208[天文地球—地图制图学与地理信息工程;天文地球—测绘科学与技术]
  • 作者机构:[1]中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室,北京100101, [2]北京四维图新科技股份有限公司,北京100083
  • 相关基金:基金项目:国家863计划(2006AA122209,2007AA122241);国家自然科学基金(40871184);国家重点实验室自主创新团队计划(088RA400SA)
  • 相关项目:自然语言表达城市交通信息的融合与应用技术研究
作者: 陆锋|申排伟|
中文摘要:

针对车载导航、地图网站等应用中路网要素之间交通关系维护的难题,提出一种支持路网要素交通关系自动化的智能过程模型,将路网要素交通关系自动化过程理解为由路网要素间的空间和语义关系、规则集和控制系统组成的产生式系统。该产生式系统可在路网要素空间和语义信息基础上,通过定义可扩展的交通关系规则集,自动化地生成符合应用需求的路网要素间的交通关系。此外,在该产生式系统中引入触发器概念监控和响应几何网络及其交通关系规则集的变更,实时更新逻辑网络中的连通关系信息,实现几何网络、规则集和逻辑网络三者的一致性。同时,提出路网要素交通关系处理的控制策略和关键流程,并对该智能网络模型的有效性进行了验证。

英文摘要:

Maintai task for in-vehicle commonly conduc intrinsic rules of t ning the traffic connectivity relations between road features has always been a time consuming navigation, mapwebsite, and other traveling service related applications. Sucha task has been ted artificially and inevitably inefficient, yet makes data quality control difficult. Considering the raffic connectivity formed by the geometrical structures, spatial and semantic relationships be- tween road features in city road networks, an intelligent processing model is set forward in this paper for traffic connectivity automation. It is argued that traffic connectivity automation between rood features is fundamentallya production system composed of the spatial and semantic relations between road features, connectivity rules and control system. With the implementation of an extendable connectivity rule set, the traffic connectivity relations between road network features are built automatically based on the spatial and semantic information of road network. The trigger concept is adopted to monitor and respond the changes in geometrical network and connectivity rules, and then dynamically updates the traffic connectivity between road network features in logical network so as to guarantee the consistence between geometrical network, connectivity rules and logical network. A series of control strategies and a conducting engine are developed to maintain the traffic connectivity relations. A case study conducted on a real road network verifies the effects of the proposed intelligent model.

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