Connected Vehicle Applications Focused on Signalized Intersection Safety Have Estimated Median Benefit-Cost Ratio of 3.38.
Study Finds that Connected Vehicle-Based Applications Have a Higher Benefit-Cost Ratio than Non-CV-Based Applications.
Made Public Date

Florida, United States

Miami-Dade County: Florida,
United States

Connected Vehicle Vehicle-to-Infrastructure Support of Active Traffic Management

Summary Information

This study was primarily conducted to inform the Florida Department of Transportation’s (FDOT) decision to implement Vehicle-to-Infrastructure (V2I)-based Active Traffic Management (ATM) strategies. Researchers identified connected vehicle (CV) applications that improve transportation mobility and driver safety on urban arterials. A methodology was developed for selecting between CV-based applications and other applications, based on stochastic return on investment (ROI) analysis and multi-criteria decision analysis (MCDA). To estimate benefits and costs of CV-based and non-CV-based applications, a case study was conducted using a road segment along Florida State Road 924 (SR-924) in Miami-Dade County; the 2.79-mi-long segment has six lanes, a speed limit of 40 mph, and a total of 12 signalized and nine unsignalized intersections. The project demonstrates the use of micro-simulation modeling to assess the safety and mobility of one CV-application, Signalized Left Turn Assist (SLTA). The mobility performance of base conditions was estimated using Highway Capacity Software (HCS) and the safety performance of base conditions was estimated using a statewide crash database with collected data from January 2015 to December 2017.

Return on Investment Analysis

The benefits and costs of CV applications were calculated for the selected road segment and used in the stochastic ROI analysis. The benefits utilized estimated crash modification factors (CMFs) and safety and mobility impacts in dollar values. The safety benefits were obtained by first identifying the rate, frequency, and severity of the crash types that are expected to be influenced by the implementation of CV technology utilizing crash data for a three- to five-year period. The cost estimates for the Vehicle-to-Infrastructure (V2I) applications deployment were identified based on the Near-Term V2I Transition and Phasing Analysis Life Cycle Cost Model (LCCM) tool[1]. In addition, other resources were considered in the estimates, such as the cost data reported in the United States Department of Transportation (USDOT) Joint Program Office (JPO) benefit database. Equipment lifetime was assumed to be five years. The lognormal distribution was used for estimating benefits while considering uncertainty and the uniform distribution was used for the costs of V2I deployments. The parameters of the distributions were estimated based on the highest and lowest values reported in the literature. About 1,000 simulations were conducted to graph benefit-cost ratio (BCR) distributions for various CV applications.


  • Safety applications: The BCR for CV-based applications are higher than non-CV-based applications. For CV-based signalized intersection applications, the 15th percentile for the BCR is 2.73, the 50th percentile is 3.38, and the 85th percentile is 4.82. For unsignalized intersection applications, the BCR at the 15th, 50th, and 85th percentiles are 1.79, 2.26, and 3.31, respectively. The BCR for hazard warning at the 15th, 50th, and 85th percentiles are 1.00, 1.18 and 1.86, respectively.
  • Mobility applications: The BCR of adaptive signal control and transit signal priority applications is higher when CV-based than non-CV-based. The median BCR of adaptive signals is 4.12 for the CV-based application, compared with 1.67 for the non-CV-based application. The median BCR for CV-based transit signal priority systems is 1.47, compared with 0.85 for the non-CV-based application.


Demonstration of the use of micro-simulation modeling of SLTA

The mobility benefits were assessed based on the examination of the output of the utilized microscopic simulation model in this study. Simulation runs were performed to assess the impacts of the SLTA for different market penetration rates (10%, 20%, 50%, 80%, and 100%). The safety benefits of SLTA were determined using surrogate safety measures through a combination of the micro-simulation model and the Surrogate Safety Assessment Model (SSAM).


  • At 100 percent market penetration rates, utilizing SLTA will reduce the average delay for all vehicles by approximately 38 percent. SLTA could also improve the overall left-turn average capacity by approximately 42.6 percent by increasing the SLTA utilization from 10 percent to 100 percent.
  • Intersection safety can be improved by approximately 33 percent (reduced conflicts) by increasing SLTA utilization from 10 percent to 100 percent


[1] Federal Highway Administration (FHWA). (2015). Near-Term V2I Transition and Phasing Analysis, Life Cycle Cost Model User’s Guide, Washington, D.C.

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