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Non-linear relationship between built environment and non-motorized travel efficiency under the traffic
Xiaoyuan Dong1, Lining Wang1, Sen Du1
1School of Architecture and Urban Planning, Lanzhou Jiaotong University, Gansu, Lanzhou, China.
Plos One
|January 30, 2025
Summary
Urban planning significantly impacts non-motorized travel efficiency. This study reveals complex, non-linear relationships between built environment factors and travel efficiency, offering key insights for optimizing urban design and traffic management.
Area of Science:
- Urban Planning and Transportation Science
- Geographic Information Systems (GIS) and Spatial Analysis
- Data Science and Machine Learning
Background:
- The built environment is a critical factor influencing travel demand and mode choices.
- Previous research often modeled the relationship between urban design and transportation linearly, potentially oversimplifying complex interactions.
- Understanding non-linear effects is crucial for effective traffic policy and urban development.
Purpose of the Study:
- To investigate the non-linear influence mechanisms and threshold effects of the built environment on non-motorized travel efficiency.
- To identify and rank the most influential built environment factors affecting non-motorized travel.
- To provide data-driven recommendations for urban planning and traffic management.
Main Methods:
- Utilized multi-source big data, including Points of Interest (POI), OpenStreetMap, street view imagery, and built environment data for Chengguan District, Lanzhou City.
- Employed ArcGIS spatial analysis tools and the Extreme Gradient Boosting (XGBoost) model to analyze complex relationships.
- Conducted non-linear analysis and identified threshold effects of built environment variables on travel efficiency.
Main Results:
- Identified key built environment factors influencing non-motorized travel efficiency, including branch road density, land-use mix, land-use density, neighborhood entrance/exit density, bus station density, and dead-end road density.
- Revealed significant non-linear relationships and threshold effects, indicating that the impact of these factors is not uniform.
- Established a relative importance ranking for various built environment factors.
Conclusions:
- The study highlights the complex, non-linear nature of the built environment's impact on non-motorized travel efficiency.
- Proposed optimization strategies for road network patterns, land use, and public transport accessibility based on identified non-linear thresholds.
- Offers valuable decision-making references for urban planners and traffic managers to enhance sustainable transportation.
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