Trip information and navigation systems are expected to become key components of future traffic management strategies, which, if properly exploited, may contribute to the mitigation of car usage externalities. In this study, we investigate social routing recommendations, which could be associated with nudges, and delivered via a navigation app, aiming at promoting sustainable routing behavior, where some drivers are asked to take longer routes and make travel time sacrifices (TTS). In particular, we propose a framework including data collection and behavioral modeling to identify the impacts of various types of information delivered to drivers, goals of the detour, and personal characteristics on drivers’ TTS behavior. The methodology includes stated choice and revealed choice experiments in two European cities, Amsterdam and Helsinki, and a mixed ordered-response logit model to provide insights into TTS behavior. Our analyses show that delivering different information and nudges results in different levels of TTS. However, regardless of the goal of the detour, offering incentives to drivers enables achieving a higher level of TTS. Comparing the stated and revealed data, regarding TTS and compliance rate, also clarifies significant differences between these two types of data.

出行信息和导航系统预计将成为未来交通管理策略的关键组成部分，如果利用得当，可能有助于减轻汽车使用的外部性。在这项研究中，我们研究了社交路线建议，这些建议可能与轻推相关，并通过导航应用程序提供，旨在促进可持续的路线行为，其中一些驾驶员被要求走更长的路线并牺牲出行时间（TTS）。特别是，我们提出了一个包括数据收集和行为建模的框架，以识别传递给驾驶员的各种类型的信息、绕行目标和个人特征对驾驶员 TTS 行为的影响。该方法包括在阿姆斯特丹和赫尔辛基这两个欧洲城市进行的陈述选择和揭示选择实验，以及混合有序响应 logit 模型，以提供对 TTS 行为的洞察。我们的分析表明，提供不同的信息和推动会产生不同级别的 TTS。然而，无论绕道的目标是什么，为驾驶员提供激励都可以实现更高水平的 TTS。比较有关 TTS 和合规率的陈述数据和披露数据，也阐明了这两类数据之间的显着差异。