| Title | Techniques for mining truck data to improve freight operations and planning. |
|---|---|
| Record ID | 25129 |
| Personal Name Creator |
Bertini, Robert L.; Horowitz, Zachary; Tufte, Kristin; Matthews, Spicer |
| Corporate Creator | Portland State University. Department of Civil & Environmental Engineering |
| Corporate Contributor |
Transportation Northwest Regional Center X (TransNow) (UTC); Oregon. Department of Transportation |
| Publisher | Oregon. Dept. of Transportation |
| Publication Date | 20060500 |
| Language | English |
| Abstract | Freight plays an increasingly valuable role in the national economy, and a growing percentage of freight – measured by both total volume and market value - is being moved along the highway system by truck. An important part of the research process to fully understand the impacts of these increased truck volumes on the entire transportation network is by collecting and analyzing freight data. With the adoption of just-in-time supply chain management solutions, and increasing congestion on urban, rural and intercity motorways, better knowledge of freight movements can serve to improve highway operations. The real-time data generated by the development of travel time algorithms can be provided to commercial vehicle operators to enable them to minimize the delay associated with goods movement, and assist in streamlining the logistics planning process. Increased knowledge of truck travel patterns has the potential to increase overall highway safety, lead to better-managed maintenance operations, provide cost savings to public agencies, validate investments in intelligent transportation systems (ITS), and improve long-range planning and forecasting. Like other aspects of traffic engineering, efforts that result in higher quality data and improved collection methodologies generally lead to increased knowledge of the transportation system. This paper explores techniques that use current ITS technologies such as the Autoscope video processing system and loop detector data algorithms to collect and verify short and long vehicle count and length data. Three sets of traffic data for each time interval are created, and then compared using statistical analyses to produce results that that reveal new information about the freight transportation system in the Portland metropolitan region. |
| Rosap ID | dot:5538 |
| Rosap URL | https://rosap.ntl.bts.gov/view/dot/5538 |
| TRT Terms | Transportation operations; Freight service; Intermodal services; Trucking |
| Classification | NTL - FREIGHT - FREIGHT; NTL - FREIGHT - Trucking Industry; NTL - FREIGHT - Freight Planning and Policy |
| Geographical Coverage |
United States |
| Report Number | TNW2006-05 |
| Resource type | Research Paper |
| URL | https://ntlrepository.blob.core.windows.net/lib/25000/25100/25129/TNW2006-05.pdf |
| Format | |
| Database | NTL Digital Repository |