Benefit

Adaptive signal control systems that use connected vehicle data at a penetration rate of 60 percent can reduce average vehicle delay up to 60 percent under low demand scenarios.

Experience developing algorithms to use connected vehicle data at varied levels of market penetration


05/14/2014


Summary Information

This research evaluated the use of connected vehicle technologies to improve traffic conditions at urban intersections. An intersection traffic control algorithm was developed to use information from connected vehicles within a certain radius of an intersection and then use this information to update signal timing and discharge vehicle platoons in optimal sequences. The objective function of the algorithm optimized two separate performance metrics: minimize total delay and minimize total number of stops.

METHODOLOGY

Researchers conducted a literature review and noted that previous research on connected vehicles had some limitations analyzing impacts under conditions with less than 100 percent market penetration. To handle this the model assumed intersection loop detectors could be used in addition to connected vehicle location data to provide input on departure times of equipped and unequipped cars across varied flow and penetration rates. The intersection modeled consisted of two one-way streets with no turning.

FINDINGS

The study demonstrated the value of using connected vehicle location data as well as intersection loop detector data to support an adaptive signal control system. Benefits were achieved by discharging vehicles in platoons rather than using a first-in first-out strategy. The system worked best under low demand scenarios.
  • Impacts were limited at low connected vehicle penetration rates.
  • At penetration rates of 20 to 40 percent average vehicle delay improved significantly.
  • At a penetration rate of 60 percent average vehicle delay decreased up to 60 percent.
  • At penetration rates above 60 percent benefits started to diminish.

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Source

Using Connected Vehicle Technology to Improve the Efficiency of Intersections

Author: Guler, S.; M. Menendez; and L. Meier

Published By: Transportation Research Part C, Elsevier

Source Date: 05/14/2014

Other Reference Number: Vol 46, pp.121–131

URL: https://trid.trb.org/view.aspx?id=1325264

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Goal Areas

Mobility

Typical Deployment Locations

Metropolitan Areas

Keywords

traffic signals, adaptive signals

Benefit ID: 2016-01112