While there is a global shift to electric vehicles (EVs), few studies have comprehensively quantified the relative contribution of individuals' demographic characteristics, alternative transportation choices, and built environment (BE) attributes to EV ownership. Applying extreme gradient boosting decision trees to the 2020 regional household travel data in Wuhan, this study estimate the respective effects of these factors on EV ownership. The results emphasize the contribution of the BE and alternative travel options in predicting EV ownership and reveal a nonlinear relationship between variables. The distance to the city center, density and charging station facilities are identified as key factors influencing EV ownership. The study revealed a positive correlation between household ownership of conventional cars and EVs, indicating a tendency for households possessing conventional cars to acquire extra EVs, thereby transitioning into multi-car households. The findings also suggest that, in addition to the emissions reduction benefits, planners should be concerned about the potential urban issues that may result from vehicle electrification. The study provides empirical evidence for urban planners to inform policy interventions aimed at guiding the sustainable development of emerging mobility modes.

中文翻译：

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检查家庭电动汽车拥有量的相关性：新兴出行和规划的见解


尽管全球范围内正在转向电动汽车 (EV)，但很少有研究全面量化个人人口特征、替代交通选择和建筑环境 (BE) 属性对电动汽车拥有量的相对贡献。本研究将极端梯度提升决策树应用于 2020 年武汉地区家庭出行数据，估计了这些因素对电动汽车拥有量的各自影响。结果强调了 BE 和替代出行选项在预测电动汽车拥有量方面的贡献，并揭示了变量之间的非线性关系。距市中心的距离、密度和充电站设施被认为是影响电动汽车保有量的关键因素。该研究显示，家庭拥有传统汽车和电动汽车之间存在正相关关系，这表明拥有传统汽车的家庭倾向于购买额外的电动汽车，从而转变为多车家庭。研究结果还表明，除了减排效益外，规划者还应该关注车辆电气化可能带来的潜在城市问题。该研究为城市规划者提供了经验证据，以指导旨在指导新兴出行方式可持续发展的政策干预措施。