We explore how the hypothetical provision of Wi-Fi on transit affects the willingness of non-transit commuters (solo drivers, ridesharers, and cyclists) in Northern California (N = 1402) to switch from their current mode to public transit with internet access (PTWIA). Beyond the prima facie interpretation of our survey results, they shed light on the heterogeneously-perceived utility of hands-free travel more generally, and, as such, speak to an automated-vehicle future. We develop latent class binary choice models of the likelihood of switching to PTWIA, stratified by current commute mode. Each model identifies two latent classes, based largely on work-related attitudes: solo drivers divide into the work-oriented (22%) and pleasure-oriented (78%); ridesharers into the over-traveled monotaskers (77%) and multitasking commuters (23%); and cyclists into work-oriented (28%) and non-work-oriented (72%). Thus, non-work-oriented commuters are a sizable majority of non-transit users, and also have a much lower weighted probability of switching to PTWIA (0.17, on average) compared to the work-oriented commuters (0.48). In sum, work-friendly hands-free travel can be an appealing alternative to those who are oriented toward working (and especially on the commute), but (1) not for all of them, and (2) such people only constitute about a quarter of the non-transit commuters (in Northern California). These results provide empirical insight into the extent to which the productive use of travel time made possible by automated vehicles will be exploited by future commuters.

我们探讨了假想在过境中提供Wi-Fi的方式如何影响北加利福尼亚（N = 1402）非过境通勤者（单车司机，乘车共享者和骑自行车的人）从当前模式切换为可通过互联网访问的公共交通的意愿（ PTWIA）。除了对我们的调查结果的初步表述之外，他们还更广泛地阐明了免提旅行的异类感知效用，因此，这也谈到了自动驾驶汽车的未来。我们以当前通勤模式为基础，开发了切换到PTWIA的可能性的潜在类二元选择模型。每个模型主要根据与工作相关的态度来识别两个潜在类别：单身司机分为以工作为导向（22％）和以娱乐为导向（78％）；乘车者进入过度旅行的单任务通勤者（77％）和多任务通勤者（23％）；和骑自行车的人分为工作导向型（28％）和非工作导向型（72％）。因此，与非工作通勤者相比，非工作通勤者占相当大的比例，与工作导向通勤者（0.48）相比，转换为PTWIA的加权概率要低得多（平均为0.17）。总而言之，对于那些致力于工作（尤其是上下班通勤）的人来说，工作友好的免提旅行可以是一种吸引人的选择，但（1）并非所有人都适合，并且（2）这样的人只构成一个四分之一的非过境通勤者（在北加利福尼亚州）。这些结果为未来通勤者在多大程度上利用自动驾驶汽车可能产生的旅行时间提供了经验性的见识。