Trip-level household travel surveys (HTS) are an efficient and widely used instrument in transport planning and research and are expected to remain in this role for at least the near future. Mode information is typically assigned to trips in these surveys based on a hierarchy of transport modes that hides important information on the individual stages which is particularly relevant for walking. This study develops a methodology for estimating detailed stage-level information for trip-level HTS that contain some information on stages, this is the sequence of used transport modes and the number of transfers in Public Transport (PT) trips. The methodology is developed based on detailed stage-level data from a sub-sample in the German National HTS MiD 2017 and directly applied to the German city-based HTS SrV 2018 which is a trip-level survey but contains stage-level information on modes and PT transfers. Linear Regression Models for estimating walking stage duration in PT and car trips are combined with simple heuristic estimations for the less frequent types of intermodal trips. Trip purpose, accompaniment and total trip duration are important predictors for walking stage duration. Trip-level and stage-level modal-split figures for the number, duration, and distance of trips and stages in SrV 2018 are computed with the developed methodology. About half of all stages and 30% of trips are done by walking. Walking stage duration is with around 38% considerable, this share drops to around 12% for walking stage distance.

旅行级别的家庭旅行调查 （HTS） 是交通规划和研究中一种有效且广泛使用的工具，预计至少在不久的将来将继续发挥这一作用。在这些调查中，通常根据交通方式的层次结构为出行分配模式信息，该层次结构隐藏了各个阶段的重要信息，这与步行特别相关。本研究开发了一种方法来估计行程级 HTS 的详细阶段级信息，其中包含一些阶段信息，即使用的交通方式的顺序和公共交通 （PT） 行程中的换乘次数。该方法是根据德国国家 HTS MiD 2017 中子样本的详细阶段级数据开发的，并直接应用于基于德国城市的 HTS SrV 2018，这是一项行程级调查，但包含有关模式和 PT 转移的阶段级信息。用于估计 PT 和汽车出行中步行阶段持续时间的线性回归模型与不太频繁的多式联运类型的简单启发式估计相结合。旅行目的、陪伴和总旅行持续时间是步行阶段持续时间的重要预测指标。SrV 2018 中行程和阶段的数量、持续时间和距离的行程级别和阶段级别模态拆分数字是使用开发的方法计算的。大约一半的阶段和 30% 的行程是通过步行完成的。步行阶段持续时间约为 38%，步行阶段距离的这一份额下降到 12% 左右。