Microsimulation of A Signalized Intersection in Florida Estimated that Connected Vehicles Can Reduce Travel Times by up to 17 Percent at Full Penetration Due to Increased Likelihood of Arriving-On-Green.

The Study Examined Different Scenarios of the Presence and Coexistence of Connected Vehicles, Automated Vehicles and Connected and Automated Vehicles at a Signalized Intersection. 

Date Posted

Evaluation of Advanced & Communication Technologies through Traffic Microsimulation

Summary Information

Advancements in automated vehicle (AV) technologies, along with improved connectivity and interactive capabilities with future-generation traffic systems, can drive transformative changes in how vehicles navigate city roads and highways. The objective of this study was to develop a robust microscopic simulation extension to allow the evaluation of traffic operations considering the presence and coexistence of AVs, connected vehicles (CVs), and connected/ automated vehicles (CAVs). An isolated four-legged signalized intersection in Florida was modeled under several traffic scenarios of various demand and CAV penetration levels to assess the impact on energy, fuel consumption, and greenhouse gas emissions.


The study leveraged the existing application programming interface (API) capabilities of the traffic simulation tool to emulate the CAV operations. Three simulation cases were considered: (i) AV and conventional vehicle (CNV), (ii) CV and CNV, and (iii) CAV and CNV. A model adopted from a 2016 study was used to replicate AV logic, which assumed that an AV would have information about all vehicles within its sensor range. An Infrastructure to Vehicle (I2V) application based on a 2017 study, which allowed the CVs to access signal timing information was used to replicate CV logic. The CV logic sought to maximize the likelihood of arrival-on-green by changing a vehicle’s speeds within certain bounds. The CAV scenario implemented both the AV and CV logic.

Scenarios were designed for each simulation case with volume-to-capacity (V/C) ratios of 0.7 and 0.9, and penetration rates for AV, CV, and CAV at 20 percent increments ranging from zero to 100. Trajectory data from the model were used to calculate travel times and Carbon Dioxide (CO2) emissions, estimated using EPA’s Motor Vehicle Emission Simulator (MOVES) model for the 2017 fleet mix.


  • In general, the simulation results indicated that travel times decreased with rising penetration levels of AV, CV, and CAV, particularly in the AV and CAV scenarios compared to CV. The reduction in travel times was relatively larger at higher demand levels for the modeled intersection. For example, at 100 percent CV penetration and 0.9 V/C, the average time to travel through the intersection in the Northbound direction decreased by approximately 17 percent (as estimated from figure 5-7(b)).
  • Emissions did not experience the same improvements and in some cases (i.e., CV and CAV scenarios) were worse. This performance drop was attributed to the frequency of acceleration decisions which could happen multiple times per second.
  • Because this study only looked at a single intersection, it was concluded that larger network studies could reveal different outcomes. 

Evaluation of Advanced & Communication Technologies through Traffic Microsimulation

Evaluation of Advanced & Communication Technologies through Traffic Microsimulation
Source Publication Date
Manjunatha, Pruthvi; Lily Elefteriadou; Michael P. Hunter; Xi Duan; Clark Letter; Somdut Roy; Chelsea "Chip" White; Deborah Postma; Angshuman Guin
Prepared by Southeastern Transportation Research, Innovation, Development, and Education Center (STRIDE) for USDOT Office of Research, Development, & Tech
Results Type
Deployment Locations