As a special case of multitasking, travel-based multitasking typically refers to conducting a set of in-vehicle activities while traveling. Travel-based multitasking has an indisputable influence on offering a pleasant travel experience to transit users during their rides, given that they can use their travel time to perform desirable activities and gain benefits in various form. For instance, the in-activities could help the rider free up time from his/her schedule for the day (i.e., a worthwhile use of travel time). In this study, we investigate how the worthwhileness of a travel-based multitasking could be under the influence of: (1) the transit user’s lifestyle, and (2) socio-demographics, and (3) the characteristics of the transit trip. Towards this, we conducted an intercept survey focusing on the transit trips in the Chicago metropolitan area and analyzed it using latent class modeling approach. Per the results, two classes of transit users could be identified: (1) worthwhileness seekers, productively travelers and (2) leisure seekers, occasional worthwhile travelers. The results also suggest travel time, waiting time and walking distance to the transit station, and the set of in-vehicle activities as significant predictors of worthwhile use of travel time. The findings provide insights to policymakers for improving public transit systems in the current form, as well as designing an autonomous mobility system as the future form of public transit.

作为多任务的一种特殊情况，基于旅行的多任务通常是指在旅行时进行一组车载活动。基于旅行的多任务处理对于为过境用户在乘车期间提供愉悦的旅行体验具有无可争议的影响，因为他们可以利用其旅行时间来进行所需的活动并以各种形式获得收益。例如，不活动可以帮助骑手从他/她的日程安排中腾出时间（即，值得利用旅行时间）。在这项研究中，我们调查了基于旅行的多任务处理的价值如何受到以下因素的影响：（1）过境用户的生活方式，以及（2）社会人口统计数据，以及（3）过境旅行的特征。为此，我们针对芝加哥市区的过境旅行进行了拦截调查，并使用潜在类建模方法对其进行了分析。根据结果​​，可以识别出两类过境用户：（1）值得追求的人，有生产力的旅行者；（2）寻求休闲的人，偶有有价值的旅行者。结果还表明出行时间，等待时间和到公交车站的步行距离，以及一系列的车载活动，这些都可以作为有价值的出行时间预测指标。研究结果为决策者提供了见识，以改进当前形式的公共交通系统，以及设计自动驾驶系统作为未来公共交通的形式。