V2I data used to support adaptive signal control applications can reduce rear-end conflicts by 46 to 54 percent in scenarios with 10 percent CV market penetration.
The benefits of early deployment of connected vehicle infrastructure at signalized intersections was demonstrated and explained to help state DOTs and local agencies.
Made Public Date


United States
    In this research paper, a connected vehicle infrastructure framework was presented in five steps.
  1. Upstream detectors were used to collect upstream arrival vehicle profiles for each approach and Basic Safety Messages (BSMs) were transmitted to Roadside Units (RSU) and forwarded to the model.
  2. Upcoming traffic data was predicted based on real-time traffic data. The predicted traffic data for a signalized intersection included incoming traffic demands, vehicle queue length of all phases, and average approach travel time, etc.
  3. Based on predicted data, splits were adjusted to clear the queues on all approaches. In the state of practice approach, cycle length was adjusted based on the critical intersection method.
  4. Alternatively, cycle length and offset were optimized to minimize queue lengths of all phases at all intersections.
  5. The adjusted splits, optimized offsets and cycle length were implemented for all signalized intersections
The framework was simulated on a network modeled after four signalized intersections along Dolley Madison Boulevard in McLean, VA. The Virginia Department of Transportation provided the Synchro file that the traffic signal timing plan had been optimized to. Connected vehicle penetration rates simulated included: 10 percent, 25 percent, 50 percent, 60 percent and 70 percent.


A penetration rate of just 10 percent resulted in reductions of about 46-54 percent of rear end collision conflicts and 76-86 percent of crossing conflicts.
Goal Areas