Development of Portable Wireless Measurement and Observation Station

Principal Investigator:

Panos Michalopoulos, Professor, Civil, Environmental and Geo-Engineering

Project Summary:

In spite of progress made in ITS technology over the past decade, road instrumentation for data collection purposes continues to be somewhat inadequate. Furthermore, the majority of data-collection devices depend on outdated technologies to take very limited measurements, such as volume and occupancy. Because of the extent of the roadway system, however, it is impossible to deploy sufficient instrumentation for all planning, traffic, and research needs. For this reason, there is a need for developing and testing an easily deployable, low-cost data collection and surveillance station that can be used for measuring detailed traffic data such as individual speeds, density, and other factors. Such an easily deployable, low-cost data collection and surveillance station could be used for planning and traffic management as well as for research purposes, such as simulation, modeling, and control. This "total" station capitalizes on recent advances in machine vision traffic sensors, digital video compression and transmission, and wireless communication networks. In essence, it is the first step toward the development of a highway laboratory for traffic studies and research. Because traditional, permanent systems collect data by sensors in the pavement and transmit it through land-based communications, this equipment is subject to failure in construction areas. Through advancements in wireless technology, the developed system integrates machine vision sensors to collect data, compress digital video for surveillance, and use wireless nommunications for information retrieval and remote control. This new system can be added to current installations or used to create temporary traffic monitoring systems.

Sponsor:

Project Details:

  • Start date: 01/2002
  • Project Status: Completed
  • Research Area: Transportation Safety and Traffic Flow
  • Topics: Traffic Modeling and Data