Urban Bike Lane Planning with Bike Trajectories: Models, Algorithms, and a Real-World Case Study

39 Pages Posted: 29 Sep 2019 Last revised: 18 Aug 2020

See all articles by Sheng Liu

Sheng Liu

Rotman School of Management

Zuo-Jun Max Shen

University of California, Berkeley - Department of Industrial Engineering & Operations Research (IEOR)

Xiang Ji

University of California, Berkeley

Date Written: December 1, 2018

Abstract

We study an urban bike lane planning problem based on the fine-grained bike trajectory data, which is made available by smart city infrastructure such as bike-sharing systems. The key decision is where to build bike lanes in the existing road network. As bike-sharing systems become widespread in the metropolitan areas over the world, bike lanes are being planned and constructed by many municipal governments to promote cycling and protect cyclists. Traditional bike lane planning approaches often rely on surveys and heuristics. We develop a general and novel optimization framework to guide the bike lane planning from bike trajectories. We formalize the bike lane planning problem in view of the cyclists' utility functions and derive an integer optimization model to maximize the utility. To capture cyclists' route choices, we develop a bilevel program based on the Multinomial Logit model. We derive structural properties about the base model and prove that the Lagrangian dual of the bike lane planning model is polynomial-time solvable. Furthermore, we reformulate the route choice based planning model as a mixed integer linear program using a linear approximation scheme. We develop tractable formulations and efficient algorithms to solve the large-scale optimization problem. Via a real-world case study with a city government, we demonstrate the efficiency of the proposed algorithms and quantify the trade-off between the coverage of bike trips and continuity of bike lanes. We show how the network topology evolves according to the utility functions and highlight the importance of understanding cyclists' route choices. The proposed framework drives the data-driven urban planning scheme in smart city operations management.

Keywords: Smart City, Transportation, Urban Planning, Optimization, Facility Location

Suggested Citation

Liu, Sheng and Shen, Zuo-Jun Max and Ji, Xiang, Urban Bike Lane Planning with Bike Trajectories: Models, Algorithms, and a Real-World Case Study (December 1, 2018). Available at SSRN: https://ssrn.com/abstract=3453262 or http://dx.doi.org/10.2139/ssrn.3453262

Sheng Liu (Contact Author)

Rotman School of Management ( email )

105 St. George st
Toronto, ON M5S 3E6
Canada

Zuo-Jun Max Shen

University of California, Berkeley - Department of Industrial Engineering & Operations Research (IEOR) ( email )

IEOR Department
4135 Etcheverry Hall
Berkeley, CA 94720
United States

Xiang Ji

University of California, Berkeley ( email )

310 Barrows Hall
Berkeley, CA 94720
United States

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