摘要: |
This cooperative agreement supports the ITS Pilot project at the Ohio State University (OSU) to exploit automatically sensed data for improved transit planning and operations. For the last five years, OSU researchers have been investigating the use of remotely sensed data to augment traditional traffic data and improve estimation of traffic flow critical to transportation planning and monitoring, possibly at a substantially lower cost. The two focus areas of research are (1) Develop, test, and validate approaches to estimating origin-destination (OD) passenger flow patterns from automatic vehicle location (AVL), automatic passenger counter (APC), and, possibly, automated fare collection (AFC) data, and (2) Develop, test, and validate approaches to estimating traffic conditions from bus automatic vehicle location (AVL) data and additional bus mounted sensors. This project is currently in the process of coding OD estimation algorithms to develop a simulation framework. |