Connected vehicles with a market penetration rate of 33 percent or more can support V2I applications and significantly reduce delays at urban intersections.

Using vehicle to infrastructure (V2I) data to support decentralized adaptive traffic signal control in urban networks

3-9 October 2009

Summary Information

This study used a simulation model to examine the potential benefits of using vehicle location data and intersection queue length detection systems to improve performance of decentralized adaptive signal control systems in an urban network.

An AIMSUN NG model was developed to represent morning peak period traffic conditions on three routes with nine intersections in Hannover, Germany. The model was calibrated based on empirical driver and vehicle performance data.

Researchers compared the performance of optimized fixed time signal control using TRANSYT-7F scenarios against adaptive signal control scenarios, with and without connected vehicle data and queue length detection across a range of connected vehicle market penetration levels. At low market penetration rates it was assumed that adaptive signal control would function based on intersection queue length data.


Comparing the performance of a reference optimized fixed time signal control network to an adaptive signal control network equipped "with and without" connected vehicle queue length estimation data, modelers concluded the following:
  • Overall, enhanced adaptive signal control systems that use connected vehicle data for queue length estimation had better performance than optimized fixed time signal control systems.
  • At 100 percent market penetration a connected vehicle network with intersection queue length estimation capabilities had 25 percent less delay and a five percent increase in average speeds.
  • At 33 to 100 percent market penetration, average delay and speeds were significantly improved.
  • At penetration rates below 33 percent, queue length estimation features were functional, but limited.
  • At penetration rates below 20 percent, performance was nearly equal to or less than that of optimized fixed time signal control.

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A Decentralized Adaptive Traffic Signal Control Using V2I Communication Data

Author: Priemer, Christian and Bernhard Friedrich

Published By: Proceedings of the 12th International IEEE Conference on Intelligent Transportation Systems

Source Date: 3-9 October 2009



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Goal Areas


Typical Deployment Locations

Metropolitan Areas, Statewide


traffic signals, adaptive signals

Benefit ID: 2015-01025