by Michael Pietrzyk, ITS Program Manager, CUTR

As decisionmakers in Florida and the nation have become increasingly skeptical about the ability of added roadway capacity alone to alleviate congestion and enhance mobility, the development of congestion management systems (CMS) has taken on special importance. These systems, designed to provide information on transportation system performance and alternative improvement strategies that will aid in transportation planning and decisionmaking, are now required to be developed in all states in the U.S., as stipulated in the Intermodal Surface Transportation Efficiency Act of 1991. Also, in Florida, all metropolitan planning organizations (MPOs) are required to develop a CMS.

For the first year of CMS activity in Florida, currently available traffic data will be used to the greatest extent possible. However, in subsequent years, greater reliance on real-time traffic performance data will be required, and therefore a premium will be placed on developing a real-time traffic performance monitoring system. The usefulness and success of a CMS will depend on the accuracy and timeliness of the traffic performance data collected, the ease of obtaining and analyzing the data, and the measurability of the data against pre-determined CMS objectives. CUTR believes that CMSs ultimately will require automated traffic performance data collection and monitoring because more data will have to be collected more often. Therefore, potential techniques for application should be evaluated early in the process. To assist Florida's MPOs and the state in developing effective and efficient congestion management systems, CUTR and the HIllsborough County MPO conducted a field demonstration to evaluate the feasibility of application of intelligent transportation systems (ITS) to the automation of traffic performance data gathering.

The application of ITS technologies--information processing, communications control, and electronics--to congestion management and other transportation systems can help to reduce congestion, enhance mobility, improve safety, minimize environmental impact, save energy, and promote economic productivity.

Study Elements

Key elements of the study include:

Field Demonstration

The field demonstration portion of the project was coordinated with the Hillsborough County MPO to identify and investigate a data collection automation application that is compatible with traffic performance measures needed specifically for Hillsborough County's CMS.

The CMS Work Plan for Hillsborough County was completed in November 1994 and subsequently approved by the MPO. This plan identifies performance measures that include such indicators as the following:

CUTR's technology (vendor) selection criteria for the field demonstration focused primarily on recruiting a technology (vendor) with data collection applications relating to one or more of the Hillsborough County CMS performance Measures. Feedback from the Hillsborough County CMS Steering Committee further indicated a preference for technologies able to automate the collection of average travel speeds, origin-destination patterns and related travel times, and average vehicle occupancy.

Additionally, preference was given to the proven capability of the technology (vendor), a willingness to cost-share and/or donate labor and equipment for purposes of maximizing the field demonstration activity, and, if possible, a local presence in Tampa Bay.

A number of technology options were identified and investigated for CMS application. Several of the more promising options included:

The technology (vendor) best meeting the selection criteria was the team of Huntingdon Engineering & Environmental, Inc. (Houston) and Computer Recognition Systems, Inc. (Cambridge, Massachusetts). Their Fast Image Recognition Surveys in Transport (FIRST) video-based technology was previously tested in the United States in three cities under a contract with USDOT's John A Volpe Center. FIRST also has the capability, through high-speed, high resolution video cameras, to obtain average travel speed, origin-destination, and average vehicle occupancy. Vehicle license plates were captured on videotape for automatic machine vision recognition to measure average travel speeds and origin-destination between known points, whereas vehicle occupancy automatically was captured from a front windshield perspective on videotape for manual analysis.

Evaluation Plan

The tests were conducted in Tampa at selected data collection sites that included Interstate 275 southbound, Interstate 4 westbound, and the Ashley Street exit ramp, all of which are located immediately adjacent to and flowing into downtown Tampa. These sites represent the focal point of the a.m. peak period traffic movement into the downtown area. Data were collected between 7 and 9 a.m. on three consecutive weekdays, and six video cameras were utilized for the demonstration. Classroom instruction and one day of field training were provided by CUTR and the technology vendor for the students recruited to assist in the field data collection.

One camera for each lane was positioned for license plate reading for the two I-275 southbound lanes, the two I-4 westbound lanes, and the single-lane Ashley Street exit ramp. Also, one camera was positioned for recording vehicle occupancy at the single-lane Ashley Street exit ramp. On the third day, the two I-4 westbound cameras were repositioned approximately 11 miles upstream on I-275 at an overpass location (Livingston Avenue) to obtain average southbound travel speeds (times) for the entire I-275 corridor.

The Florida Department of Transportation provided machine counts at each of the camera locations for each day to verify total size of traffic volume sample during the evaluation periods. License plates and vehicle occupancy also were recorded manually to the greatest extent possible for comparison to the automated technique.

The demonstration was conducted the week of February 20, and data analysis is currently under way. A final report on the findings will be prepared in June. The primary objective of the demonstration is to document a feasible automation technique for collection of traffic performance data for congestion management systems. This project also will compare the tradeoffs in accuracy, reliability, labor, and cost for automated versus manual (conventional) traffic data collection.

Compared to conventional techniques for traffic data collection, automation is perceived to provide greater accuracy, reliability, and is much less labor intensive (thereby eliminating or reducing human error). According to industry estimates, the total cost of automated data collection can become up to 30 percent greater than manual data collection. However, a large portion of this cost is generally attributed to the up-front, one-time capital investment in the equipment required for automation.

If automation of traffic data collection can be proven to be feasible, then other ITS applications for CMS should be explored. The direct benefit will be responsible for more comprehensive and more frequent traffic data collection as required for a CMS.

"We need to continue to explore new ways to monitor and evaluate traffic congestion in urban areas," said Lucie Ayer, Interim Executive Director of the Hillsborough County MPO. "The application of ITS technologies to data collection certainly could enhance our current methods, resulting in greater mobility."

For more information or to request copies of the final report, contact CUTR ITS Program Manager Mike Pietrzyk at

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