摘要: |
Increased use of public transportation services is an effective means of achieving sustainable transportation in cities around the world. To increase the use of public transportation under resource constraints, it is important to improve the understanding of public transportation supply characteristics and demand behavior and make use of this understanding to improve service planning, design, and operations functions. Analyzing and interpreting in situ public transportation conditions that are readily accessible and observable can greatly improve this understanding. Project investigators previously worked with The Ohio State University (OSU) Campus Area Bus Service (CABS) and a private technology provider to equip the CABS network with state-of-the-art sensing, communications, and passenger information systems that are presently used to provide real-time bus arrival information to CABS users and ridership and location information to CABS operators and planners. In addition to being used for service planning, design, and operations, automatic vehicle location (AVL) and automatic passenger count (APC) data are downloaded nightly and archived by project investigators. The investigators couple these high-resolution and extensive data with manually collected field data (using a variety of techniques) and data obtained from web-based surveys for research, education, and outreach. The physical and data infrastructure and the strong partnership between service providers and project investigators, which developed over many years, have led to the establishment of the OSU Campus Transit Lab (CTL), a unique living lab that supports multiple internally and externally funded activities (CTL, 2017). This project is devoted to continued general data collection and targeted outreach, research, and educational activities designed to take advantage of existing CTL infrastructure and to sustain and to expand the infrastructure. |