原文传递
THE PRESENTATION OF ROAD WEATHER AND CONDITION INFORMATION TO THE PUBLIC: THE RESULTS OF AN AURORA POOLED-FUND STUDY.
| 题名： | THE PRESENTATION OF ROAD WEATHER AND CONDITION INFORMATION TO THE PUBLIC: THE RESULTS OF AN AURORA POOLED-FUND STUDY. |
| 作者： | Boselly-SE III; Roosevelt-DS |
| 关键词： | Best-practices; Canada-; Information-dissemination; Intelligent-transportation-systems; International-compacts; Public-information-programs; Road-weather-information-systems; Standardization-; Sweden-; United-States |
| 摘要： | Aurora is a consortium of agencies focused on collaborative research, evaluation, and deployment of advanced road weather information systems (RWIS) technologies. Current membership in Aurora includes 9 state departments of transportation in the United States, the ministries of transportation in two Canadian provinces and the Swedish National Road Administration. Aurora also works closely with a number of sections of the Federal Highway Administration in the U.S. The paper discusses Aurora's Standardized Road Weather and Condition Presentation project and its study and report that identifies current and planned implementation of road weather and condition information dissemination systems. Presented are some findings from the study. |
| 总页数： | Conference Title: 11th International Road Weather Conference (http://www.sirwec.org). Location: Sapporo, Japan. Sponsored by: Standing International Road Weather Commission. Held: 20020126-20020128. 2002/01. pp8 |
| 报告类型： | 科技报告 |
相关文献
- U.S. Road Weather Management Program - Sensor Siting and Weather Information Integration Projects.
- REVIEW OF THE INSTITUTIONAL ISSUES RELATING TO ROAD WEATHER INFORMATION SYSTEMS (RWIS).
- REPORT, CARS POOLED FUND STUDY : A STATEWIDE TRAFFIC MANAGEMENT AND INFORMATION SYSTEM.
- PRECIPITATION AND ROAD SURFACE INFORMATION. IS IT POSSIBLE TO MAKE A ROAD WEATHER CLIMATOLOGY WITH RWIS DATA? A PROSPECTIVE STUDY.
- RESULTS OF AV WINTER ROAD CONDITION SENSOR PROTOTYPE.
- ADVANCED TRANSPORTATION WEATHER INFORMATION SYSTEM : LESSONS LEARNED.
检索历史
应用推荐
