When it comes to views on bike lanes, most people have a strong opinion. Whether you love them or dislike them, new studies show that applying scientific reasoning can help identify the best locations for these lanes. This approach helps reduce traffic congestion while encouraging more individuals to switch from cars to bicycles, which produce no emissions.
In collaboration with two other researchers, smart city expert Sheng Liu gathered data and consulted with city planners from Vancouver and Chicago to create a model that guides municipalities in selecting the ideal spots for expanding their cycling lane networks in response to increasing demand.
“Our model serves as a structured decision-making framework for municipalities looking to design new bike lanes based on available data,” explained Prof. Liu, who works as an assistant professor in operations management and statistics at the Rotman School of Management, University of Toronto. “It aids policymakers in quantifying and assessing the potential advantages and drawbacks of bike lane installations. Specifically, it can forecast the likely effects on traffic conditions and emission levels depending on the lane locations.”
Bike lanes have become increasingly popular across North America, contributing to fewer traffic fatalities, more cost-effective personal transportation options, and enhanced physical fitness for cyclists. However, as many commuters have noted, “neglecting traffic dynamics when planning bike lanes can lead to unnecessary congestion,” the researchers point out, with minimal increase in cycling participation.
One challenge is that city planners often use overly simplified methods that fail to consider all factors affecting the impact of bike lanes on specific roads—or across an entire road network.
The researchers’ model harnesses a city’s traffic and commuter movement data to forecast how cycling rates and traffic congestion will be impacted by the placement of bike lanes. It calculates changes in driving times based on vehicle volume and road characteristics, evaluates the appeal of cycling versus driving based on expected travel durations, and determines which roads in a network will experience the highest bike usage and least traffic congestion when new bike lanes are introduced.
When applied to Chicago, one of the most congested cities in the U.S. where expanding the cycling network is a key policy goal, the model projected that adding 40 km of bike lanes in targeted areas could boost cycling ridership from 3.6% to 6.1% in the downtown area, while increasing driving times by no more than 9.4%.
“With the expansion of bike lanes, some roads might experience increased congestion, while others could actually become less congested,” noted Prof. Liu. “On a broader scale, our findings suggest that the overall travel time for all commuters could be reduced under the proposed plan for expanding bike lanes. This also indicates potential decreases in emissions.”
Recognizing that discussions about bike lanes can become quite contentious, Prof. Liu emphasized the importance of allowing data to guide decisions, advocating for a scientific approach to assess their effectiveness. “Simply removing bike lanes from the streets won’t resolve our congestion issues and may even exacerbate them.”
