Mobility Network logo

Dr. Sheng Liu presents 'Planning Bike Lanes with Data'

event graphic with text details, logos and wordmarks
Warning: Undefined variable $event_id in /code/wp-content/plugins/oxygen/component-framework/components/classes/code-block.class.php(133) : eval()'d code on line 2 March 31, 2023. 11:00 am to 12:00 pm EDT

In this presentation, we present a method and empirical study for planning bike lane networks using data.

We first present an estimator for recovering unknown parameters of a traffic equilibrium model from features of a road network and observed vehicle flows, which we show asymptotically recovers ground-truth parameters as the network grows large. We then present a prescriptive model that recommends paths in a road network for bike lane construction while endogenizing cycling demand, driver route choice, and driving travel times. In an empirical study on the City of Chicago, we bring together data on the road and bike lane networks, vehicle flows, travel mode choices, bike share trips, driving and cycling routes, and taxi trips to estimate the impact of expanding Chicago's bike lane network. We estimate that adding 25 miles of bike lanes as prescribed by our model can lift ridership from 3.9% to 6.9%, with at most an 8% increase in driving times. We also find that three intuitive heuristics for bike lane planning can lead to lower ridership and worse congestion outcomes, which highlights the value of a holistic and data-driven approach to urban infrastructure planning.

About the speaker

head shot of Dr. Sheng Liu
Dr. Sheng Liu

Sheng Liu is an Assistant Professor of Operations Management and Statistics at the Rotman School of Management. His research interests lie in supply chain and logistics, smart city operations (especially sustainable/climate-resilient system design), and data-driven decision-making (the integration of predictive and prescriptive analytics). His recent work explores the effective use of data to prescribe operational decisions for logistics and mobility systems. He received a PhD in Operations Research from UC Berkeley in 2019 and a BSc in Industrial Engineering from Tsinghua University in 2014. He has contributed to the development of advanced decision-making tools for leading companies, including Amazon, Lyft,, and CNPC.

* * *

Presented by University of Toronto ITE Student Chapter, UT-ITE. Free. All are welcome.

If any specific accommodations are needed, please contact Requests should be made as early as possible.


March 31, 2023
11:00 am to 12:00 pm EDT
Event Category:
Event Tags:
, , , ,


View Organizer Website


ITS Lab and Testbed, SF3103
Sandford Fleming Building, University of Toronto, 10 King's College Road, 3rd Floor, Room SF3103
Toronto, ON M5S 1A4 Canada
+ Google Map
crossmenu-circlecross-circle linkedin facebook pinterest youtube rss twitter instagram facebook-blank rss-blank linkedin-blank pinterest youtube twitter instagram