原文传递 CAVC Classification System. PENNDOT Partnership. Project Task 39: Automatic Traffic Data Collection System Modernization; Final rept
题名: CAVC Classification System. PENNDOT Partnership. Project Task 39: Automatic Traffic Data Collection System Modernization; Final rept
作者: Goulias, K. G.; Chung, J. H.; Viswanathan, K.
关键词: Transportation management; Traffic surveys; Data managment; Automation; Highway transportation; Databases; Motor vehicles; Quality control; Computer architecture; Computer programs; Statistical analysis
摘要: One of PennDOT's long-term objectives was to develop a comprehensive and integrated data management process. This objective presented several challenges: weigh-in-motion (WIM) data were not utilized in Pennsylvania, and there are operational difficulties with some of the permanent systems; one system is a strategic highway research program (SHRP) site. In addition, the portable systems are rapidly deteriorating, requiring replacement in the near future. Pennsylvania has begun securing continuous automatic vehicle classification (CAVC) data by installing equipment at 6 of the 19 portable WIM sites. In addition, reliability problems with the axle-sensing components of the system are a major concern. Recognizing that data management is a primary component in any system, Pennsylvania initiated the design of a database for CAVC data in Paradox. Because of the desirability of merging data from 19 CAVC sites with data from 60 automatic traffic recorder (ATR) sites, PEnnDOT wanted to convert the ATR database from IBM to Paradox. To meet this objective, MAUTC assisted PennDOT with the tasks of reviewing vehicle classification technology and recommending a course of action for 19 sites regarding CAVC, reviewing portable and semi-permanent technology and recommending a course of action for 19 replacement sites, addressing software requirements and preparing appropriate programming steps for ATR and CAVC data processing and storage, and reviewing literature on environmental detection technology and on vehicle detection technology.
总页数: 100p
报告类型: 科技报告
检索历史
应用推荐