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

• DOI: 10.1287/msom.2021.1023
• Publication Date: 2021-10-27T17:51:15Z
• Authors: Sheng Liu; Zuo-Jun Max Shen; Xiang Ji
• Keywords: Heuristics; Bike Sharing; Transportation planning

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