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Study suggests that as few as 5% autonomous cars can enable flow control to dampen traffic waves

Stop-and-go traffic waves—“phantom traffic jams”—emerge when small perturbations—such as a lane change, merge, or just because of natural osciallations in human driving—amplify and grow backwards along the road. A new study to be published in Transportation Research - part C provides experimental evidence that these waves can be reduced by the presence of less than 5% of autonomous vehicles in the traffic stream.

The researchers found that by controlling the pace of the autonomous car in their field experiments, the autonomous car controlled the traffic flow by dissipating the stop-and-go waves so that traffic wasn’t oscillating as it does when all of the cars are driven by humans. They found that the presence of even the small percentage of autonomous vehicles could have a significant impact in eliminating waves and reducing the total fuel consumption by up to 40% and the braking events by up to 99%.

Recent advancements in vehicular automation and communication technologies provide new possibilities and opportunities for traffic control in which these smart vehicles act as Lagrangian actuators of the bulk traffic steam. When a series of adjacent vehicles on a roadway are connected and automated, it is possible to form dense platoons of vehicles which leave very small gaps.

A key challenge for vehicle platoons is to design control laws in which the vehicle platoon remains stable, for which significant theoretical and practical progress has been made. In contrast to the vehicle platoon setting, in which all vehicles are controlled, or the variable speed limit and ramp metering strategies which actuate the flow at fixed locations, this research aims to dissipate congestion-based stop-and-go traffic waves using only a sparse number of autonomous vehicles already in the flow, without changing how the other, human-driven, vehicles operate.

The notion to dissipate stop-and-go waves via controlling vehicles in the stream represents a shift from stationary to Lagrangian control, mirroring the transition to Lagrangian sensing that has already occurred. The key advantage in mobile sensing projects is that a very small number of vehicles being measured (3-5%) suffices to estimate the traffic state on large road networks. In the same spirit, our research experimentally demonstrates that a small number of Lagrangian controllers suffices to dampen traffic waves.

—Stern et al.

In their study, the researchers used a circular track with 22 vehicles to show that traffic waves emerge consistently, and that they can be dampened by controlling the velocity of a single vehicle in the flow. They compared metrics for velocity, braking events, and fuel economy across experiments.

They ran three experiments with two distinct control strategies that can be used to dampen stop-and-go waves created by human drivers. The first control strategy is to follow a fixed average velocity. The second type of control strategy is a proportional-integral (PI) controller with saturation, which is a natural extension of the PI controller, a simple and widely used controller in industrial applications. The controller is only based on the knowledge of the autonomous vehicle speed over a time horizon. The control action is saturated at small gaps to avoid collisions, and long gaps to avoid slowing down of traffic.


  • Raphael Stern et al. (2017) “Dissipation of Stop-and-Go Waves via Control of Autonomous Vehicles: Field experiments,” arXiv:1705.01693 [cs.SY]



This is one reason Economics is not a hard science..people.
Expectations and behaviors are not always rational.

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