Left turn traffic signal

(© sparkia - stock.adobe.com)

STATE COLLEGE, Pa. — Every driver has likely felt the occasional tension while making a left-hand turn. Whether it’s being stuck behind cars that miss an opportunity to go or feeling anxious about when to make the turn yourself, the left turn lane can be a daunting part of a drive. Well, it turns out there is something that can be done to relieve some of this stress and make for a smoother commute.

According to a study out of Penn State University, eliminating some left-hand turns in downtown intersections can help keep traffic flowing and reduce accident hazards. Before we moan about having to drive farther to get there, consider the benefits.

“We have all experienced that feeling of getting stuck waiting to make a left turn,” says lead study author Vikash Gayah, an associate professor of civil engineering at the university, in a statement. “And if you allow these turns to have their own green arrow, you have to stop all other vehicles, making the intersection less productive.”

Penn State researchers have come up with a method to improve traffic flow that involves a few well-placed left-turn restrictions. The advantages go beyond freeing up traffic. “Left turns are also where you find the most severe crashes, especially with pedestrians,” Gayah adds. “Our idea is to get rid of these turns when we can to create safer and more efficient intersections.”

The team’s approach is based on heuristic algorithms. The idea is to implement shortcuts that lead to better and better outcomes. “We make a guess, we learn from that guess, and then we make better guesses,” Gayah says. “Over time, we can get really, really close to the best answer.”

Urban planners have the burden of weighing traffic flow and additional travel distance when deciding to place restrictions at specific intersections.

“For example, if you just have 16 intersections to consider, each with a choice to allow or not allow left turns, that is already 65,000 different configurations,” Gayah notes. “It gets even more complicated when you consider that traffic flows from one intersection to the next.”

This creates multiple potential outcomes on the overall grid, he says.

The future of left turns?

The Penn State team used two different heuristic algorithms and then used a hybrid of the two. The first was a population-based incremental learning algorithm that randomly sampled possible traffic configurations, looking for the best options. The second was a Bayesian optimization algorithm that analyzed how the optimal restrictions would impact traffic at nearby intersections. The Bayesian approach updates results as new information is added to lead to better conclusions.

Researchers tested each of the methods alone and then in combination on a simulated grid network. All three options were able to come up with more efficient traffic patterns that included the use of left-turn restrictions. But when the simulations included more realistic traffic flow information, the hybrid method was the standout.

The authors say the combined algorithm method is something like a driving experience. The first method is where you start, and the second method is like a choice of multiple maps, with one being the most efficient and safest possible way to get to your destination.

So what were the final results?

“The most efficient configurations tended to ban left turns in the middle of the city and allowed them more often on the periphery,” Gayah concludes.

Researchers say that the tests were done on a simulated grid network, but the basic concepts could be used for any city. “I cannot take the best configuration for New York and apply it to San Francisco, but this generalized approach could be configured for any network with a little bit of coding.”

The study is published in Transportation Research Record.

About Terra Marquette

Terra is a Denver-area freelance writer, editor and researcher. In her free time, she creates playlists for every mood.

Our Editorial Process

StudyFinds publishes digestible, agenda-free, transparent research summaries that are intended to inform the reader as well as stir civil, educated debate. We do not agree nor disagree with any of the studies we post, rather, we encourage our readers to debate the veracity of the findings themselves. All articles published on StudyFinds are vetted by our editors prior to publication and include links back to the source or corresponding journal article, if possible.

Our Editorial Team

Steve Fink


Chris Melore


Sophia Naughton

Associate Editor