In recent years, roadway congestion and traffic bottlenecks have grown to critical dimension in many areas of the United States. Eliminating traffic bottlenecks and reducing congestion has numerous benefits including saving lives, improving environment, conserving fuel, saving time and enhancing productivity. Mitigating congestion and eliminating bottlenecks requires basic information on how, where, why and to what extent congestion and bottlenecks occur.

This project developed a methodology to identify bottlenecks on Florida’s Strategic Intermodal System (SIS) using vehicle probe data and congestion performance measures. Recently, FHWA acquired National Performance Measure Research Data Set (NPMRDS) vehicle probe data and made it available to DOTs and MPOs. This vehicle probe data provided speed and travel time for passengers and freight on roadways at five-minute increments. NCHRP Report 398: Quantifying Congestion noted that while it is difficult to conceive of a single value that will describe all of the travelers’ concerns about congestion, there are four components that interact in a congested roadway or system: duration, extent, intensity and reliability. Using the vehicle probe data, four performance measures were developed, one for each component of congestion – frequency of congestion, congested vehicle miles traveled, vehicle hours of delay and planning time index. A statistical validation of the performance measures was also conducted. The roadway segments for which the margin of error is greater than 10 percent are not accounted for in the estimation of bottlenecks.

Bottlenecks are identified as those portions of the roadway network with a high combination of the above congestion performance measures. The bottlenecks are displayed on easy-to-understand graphics and the top five bottlenecks at the statewide and district-wide level are identified. This methodology can be used to update the bottleneck locations on Florida’s SIS with the latest vehicle probe data. Applying the methodology routinely over time allows the identification of new bottlenecks and monitoring of existing ones to discern congestion trends. This methodology provides a practical and innovative solution to identify bottlenecks and helps to prioritize the investments on the top bottlenecks.