Behavioral Reactions and Adaptations of Manual Drivers in Mixed Traffic on the Highway – A Longitudinal Driving Simulator Study

高速公路混合交通中手动驾驶员的行为反应和适应——纵向驾驶模拟器研究

• 批准号: 514331715
• 负责人: Dr. Vanessa Stange
• 金额: --
• 依托单位: Abteilung Ingenieur- und Verkehrspsychologie
• 依托单位国家: 德国
• 项目类别: Research Grants
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/514331715?language=en
• 关键词: Behavioral; Reactions; Adaptations; Manual; Drivers

Today, vehicles controlled by partial automation (Level 2, SAE International, 2021) are travelling on the road alongside vehicles manually driven by human drivers. Recently, the manufacturer Mercedes-Benz started selling an automated Level 3 (L3) vehicle. As a result, "mixed traffic" is emerging in which manually driven drivers will share the highway with these L3 vehicles and increasingly interact with them. Since these L3 systems are expected to be introduced in the premium segment first, it is likely that human drivers will continue to be in the majority for a long time. In mixed traffic, manual drivers face the challenge of interacting not only with other human drivers, but with L3 vehicles in certain driving situations. These vehicles always comply with the rules. In contrast, among manual drivers there is probably only a small fraction of drivers, e.g. novice drivers, who show equally rule-compliant driving behavior. Upon the introduction of L3 vehicles, manual drivers will initially rarely encounter this rule-compliant driving behavior, just as in all-manual traffic today. However, as the penetration rate of L3 vehicles increases, it can be assumed that manual drivers will encounter this rule-compliant driving behavior more and more often. To date, there is limited empirical evidence on mixed traffic interactions on the highway. These studies primarily examine single, brief interactions in initial contact with L3 vehicles on the highway. Beyond that, there are practically no results available so far. The goal of this research project is a longitudinal investigation of the driving behavior of manual drivers in mixed traffic on the highway in a driving simulator. Two learning processes will be investigated. On the one hand, it will be investigated whether manual drivers adapt their existing schemes and scripts, and thus their behavior in the presence of these vehicles, accordingly in subsequent driving, so that potentially dangerous behavior of manual drivers in interaction with L3 vehicles is avoided in the longer term. The second learning process relates to the potential role model function of L3 vehicles for manual drivers with respect to rule-compliant driving behavior even when driving without L3 vehicles immediately present. If this learning takes place, this could represent an indirect contribution of automation to higher traffic safety and better traffic flow. As a possible factor promoting learning, but also possibly reinforcing negative reactions, the external labeling of the automated driving mode is included in the investigation. Thus, this research project contributes to closing this research gap, which has also been identified by different authors in the current literature and described as very relevant for future research.

今天，由部分自动化控制的车辆（SAE International，2021年2级）与人类驾驶员手动驾驶的车辆一起行驶在道路上。最近，制造商梅赛德斯-奔驰开始销售自动化3级（L3）车辆。因此，“混合交通”正在出现，其中手动驾驶的司机将与这些L3车辆共享高速公路，并越来越多地与他们互动。由于这些L3系统预计将首先在高端市场推出，因此人类驾驶员可能会在很长一段时间内继续占多数。在混合交通中，手动驾驶员不仅要与其他人类驾驶员互动，还要在某些驾驶情况下与L3车辆互动。这些车辆总是遵守规则。相反，在手动驾驶员中，可能只有一小部分驾驶员，例如新手驾驶员，表现出同样符合规则的驾驶行为。在引入L3车辆后，手动驾驶员最初很少会遇到这种符合规则的驾驶行为，就像今天的全手动交通一样。不过，随着L3级车辆普及率的提高，可以假设手动驾驶员会越来越频繁地遇到这种不遵守规则的驾驶行为。到目前为止，有有限的经验证据混合交通互动的高速公路。这些研究主要研究在高速公路上与L3车辆初次接触时的单一短暂互动。除此之外，迄今为止几乎没有任何结果。本研究的目的是在驾驶模拟器中对高速公路上混合交通中手动驾驶员的驾驶行为进行纵向调查。将研究两个学习过程。一方面，将调查人工驾驶员是否适应其现有的方案和脚本，从而在这些车辆存在的情况下，相应地在随后的驾驶中调整其行为，以便长期避免人工驾驶员与L3车辆交互的潜在危险行为。第二个学习过程涉及L3车辆对于手动驾驶员的潜在角色模型功能，即使在没有L3车辆立即存在的情况下驾驶时，也是关于符合规则的驾驶行为。如果这种学习发生，这可能代表自动化对更高的交通安全和更好的交通流量的间接贡献。作为促进学习的一个可能因素，但也可能加强负面反应，自动驾驶模式的外部标签被纳入调查。因此，本研究项目有助于缩小这一研究差距，这也被不同的作者在当前的文献中确定，并被描述为与未来的研究非常相关。