Centre for Computational Economics, Department of Economics, University of Copenhagen, 1353 Copenhagen K, Denmark.
Department of Technology, Management and Economics, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark.
Proc Natl Acad Sci U S A. 2023 Apr 18;120(16):e2220515120. doi: 10.1073/pnas.2220515120. Epub 2023 Apr 11.
To what extent is the volume of urban bicycle traffic affected by the provision of bicycle infrastructure? In this study, we exploit a large dataset of GPS trajectories of bicycle trips in combination with a fine-grained representation of the Copenhagen bicycle-relevant network. We apply a model for bicyclists' choice of route from origin to destination that takes the complete network into account. This enables us to determine bicyclists' preferences for a range of infrastructure and land-use types. We use the estimated preferences to compute a generalized cost of bicycle travel, which we correlate with the number of bicycle trips across a large number of origin-destination pairs. Simulations suggest that the extensive Copenhagen bicycle lane network has caused the number of bicycle trips and the bicycle kilometers traveled to increase by 60% and 90%, respectively, compared with a counterfactual without the bicycle lane network. This translates into an annual benefit of €0.4M per km of bicycle lane owing to changes in generalized travel cost, health, and accidents. Our results thus strongly support the provision of bicycle infrastructure.
城市自行车交通量在多大程度上受到自行车基础设施的影响？在这项研究中，我们利用了一个大型的自行车出行 GPS 轨迹数据集，并结合哥本哈根自行车相关网络的细粒度表示，应用了一种考虑完整网络的自行车出行者路径选择模型。这使我们能够确定自行车出行者对一系列基础设施和土地利用类型的偏好。我们使用估计的偏好来计算自行车出行的广义成本，并将其与大量起点-终点对的自行车出行次数进行相关分析。模拟结果表明，广泛的哥本哈根自行车道网络使自行车出行次数和自行车行驶里程分别增加了 60%和 90%，与没有自行车道网络的情况相比。这相当于由于广义出行成本、健康和事故的变化，每公里自行车道带来 0.4 万欧元的年度效益。因此，我们的研究结果强烈支持自行车基础设施的建设。
