Vehicle-to-vehicle (V2V) communications alone could provide enough information to replace or supplement existing traffic monitoring systems.
Researchers developed and assessed a distributed framework for network-wide traffic monitoring and platoon information aggregation from V2V communications via dedicated short-range communications (DSRC).
Made Public Date

Impacts Of Traffic Signal Controls On A Distributed Traffic Monitoring System Using V2V Communications: Final Report


These researchers previously developed a distributed framework designed for network-wide traffic monitoring and platoon information aggregation using V2V communications sent via DSRC. In this distributed system, each DSRC-equipped vehicle keeps track of the average traffic density and speed within a certain range, flags itself under a particular traffic group when appropriate, and cross-checks its flag status with its immediate up- and down-stream vehicles. Building on that previous work, this study uses simulation to assess the system’s performance under different traffic signal timing plans.


The researchers assess the performance of the distributed monitoring system with respect to different traffic signal timing plans while fixing the traffic scenario and market penetration rate (MPR). Specifically, this study focuses on the impacts of different phase times for a pre-timed signal timing plan with fixed cycle length on the performance of the V2V monitoring system. Different phase times are captured by varying the amount of green time per cycle length (i.e., g/C ratio), keeping cycle length (C) constant. The monitoring system’s performance is assessed under combinations of five different market penetration rates (MPRs) and four different traffic scenarios. These combinations and g/C ratios are simulated in VISSIM, which is a microscopic multi-model traffic flow simulation software package.

Lessons Learned

Speed accuracy: Simulation results show that a positive correlation exists between speed estimation accuracy and the g/C ratio. When g/C<1 (with traffic signals), results show very large relative errors in speed compared to when g/C=1 (without traffic signals). Traffic signals lead to speed fluctuations from stop-and-go traffic and make it more difficult for algorithms in the distributed monitoring system to split platoons.

Density accuracy: While the researchers found clear patterns between g/C and speed accuracy, no clear patterns were found between g/C ratio and density estimation accuracy. Generally, dense and uniformly distributed traffic lead to high density estimation accuracy.

Coverage ratio: Finally, except for one of the four traffic scenarios (high speed low demand), a positive correlation was found between the coverage ratio and the g/C ratio for the downstream segment only. The g/C ratio did not appear to significantly affect the upstream coverage ratio.