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Han  Yu  Chen  Changjie  Peng  Zhong-Ren  Mozumder  Pallab 《Transportation》2022,49(1):163-184
Transportation - Recent climatic disasters have shown the vulnerability of transportation infrastructures against natural hazards. To understand the risk of coastal hazards on urban travel...  相似文献   
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This article presents a Web-based transit information system design that uses Internet Geographic Information Systems (GIS) technologies to integrate Web serving, GIS processing, network analysis and database management. A path finding algorithm for transit network is proposed to handle the special characteristics of transit networks, e.g., time-dependent services, common bus lines on the same street, and non-symmetric routing with respect to an origin/destination pair. The algorithm takes into account the overall level of services and service schedule on a route to determine the shortest path and transfer points. A framework is created to categorize the development of transit information systems on the basis of content and functionality, from simple static schedule display to more sophisticated real time transit information systems. A unique feature of the reported Web-based transit information system is the Internet-GIS based system with an interactive map interface. This enables the user to interact with information on transit routes, schedules, and trip itinerary planning. Some map rendering, querying, and network analysis functions are also provided.  相似文献   
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交通拥挤不仅是当今许多大城市日益严重的社会问题,同时也给国家和城市造成巨大的经济损失.引发拥挤的直接原因是机动车辆保有量的迅速增加和交通设施/服务的相对落后,但对于不同的城市和地区,其深层原因存在差异.本文定位于研究宏观路网交通拥挤内在成因和演化规律,采用地理建模的仿真平台,使用地理信息系统(GIS)技术将FCD数据与深圳市地图匹配,得到城市路网不同时间点的拥挤状态,定性分析区域内交通拥挤的成因.另外,研究针对路段拥挤的相似程度,提出相关性算法进行定量分析,揭示交通拥挤的时空演变规律,为及时采取预防和疏导措施提供指导.该算法可编程实现,对交通拥挤进行统一管理与控制,提高整个交通系统的效率.  相似文献   
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In this paper we present a route-level patronage model that incorporates transit demand, supply and inter-route effects in a simultaneous system. The model is estimated at the route-segment level by time of day and direction. The results show strong simultaneity among transit demand, supply and competing routes. Transit ridership is affected by the level of service, which in turn is determined by current demand and ridership in the previous year. The model demonstrates that a service improvement has a twofold impact on ridership; it increases ridership on the route with service changes, but it also reduces the ridership on competing routes so that the net ridership change is small. The model is thus useful for both system-level analysis and route-level service planning.  相似文献   
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