High market penetration of autonomous vehicles (AVs) and connected-autonomous vehicles (CAVs) is expected to impact transportation network performance, which is an important determinant of residential location decisions, especially for households who commute to work by personal vehicle. This study examines and compares the impacts of privately owned AVs and CAVs on the location and commute characteristics as well as the spatial distribution of households within the Triangle Region in North Carolina. A Mixed Multinomial Logit model is developed using recent household survey data to capture household preferences. In addition, the region’s travel demand model, the Triangle Regional Model, is used to predict the network-level impacts of AV and CAV adoption, and cluster analysis is conducted to explore how network performance changes vary with transportation demand and supply zone characteristics at a local and regional level. Residential location patterns are predicted for a number of AV and CAV scenarios for the year 2045 using the outputs of the econometric analysis and the Triangle Regional Model. We find that extensive adoption of private CAVs improves network conditions and encourages households to live farther from work, leading up to a 5.6% increase in suburban and rural households that commute to work by personal vehicles. A high market share of AVs is associated with deteriorated transportation network performance and up to a 2.8% increase in urban households. Results vary by market penetration rate of each technology, mix of AVs, CAVs, and human driven vehicles in the traffic stream, and fuel type (conventional-fuel versus electric vehicles).

自动驾驶汽车 (AV) 和联网自动驾驶汽车 (CAV) 的高市场渗透率预计会影响交通网络性能，这是住宅选址决策的重要决定因素，尤其是对于乘坐私家车上下班的家庭而言。本研究检查并比较了私有 AV 和 CAV 对位置和通勤特征以及北卡罗来纳州三角地区家庭空间分布的影响。混合多项式 Logit 模型是使用最近的家庭调查数据开发的，以捕捉家庭偏好。此外，该地区的出行需求模型，三角区域模型，用于预测 AV 和 CAV 采用的网络级影响，并进行聚类分析，以探索网络性能变化如何随本地和区域级别的运输需求和供应区域特征而变化。使用计量经济学分析和三角区域模型的输出，预测了 2045 年许多 AV 和 CAV 情景的住宅区位模式。我们发现，私人 CAV 的广泛采用改善了网络状况并鼓励家庭住得离工作地点更远，导致使用私家车上下班的郊区和农村家庭增加了 5.6%。自动驾驶汽车的高市场份额与交通网络性能恶化和城市家庭增加高达 2.8% 有关。结果因每种技术的市场渗透率、交通流中 AV、CAV 和人类驾驶车辆的组合而异，