Economic analysis of vehicle infrastructure cooperation for driving automation
Economic analysis of vehicle infrastructure cooperation for driving automation
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驾驶自动化车辆基础设施合作经济分析
DOI：
10.1016/j.trc.2022.103757
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发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Laberteaux, Ken
中科院分区：
文献类型：
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作者：
Vignon, Daniel A.;Yin, Yafeng;Bahrami, Sina;Laberteaux, Ken
目前的驾驶自动化方法主要是以车辆为中心的。然而，车辆-基础设施协作方法（其中基础设施和车辆协作以执行不同的驾驶任务）可以在实现自动驾驶中占优势。本文对自动驾驶车辆基础设施合作进行了经济分析。在此过程中，我们提出了一个模型，该模型可以捕捉车辆自动化和基础设施数字化的投资决策及其对旅行者购买和旅行决策的影响。我们的分析表明，在某些条件下，装备基础设施和车辆是社会最优的。然而，通过分析基础设施支持服务提供商和汽车制造商之间的战略互动，我们发现这两个参与者之间缺乏协调会导致车辆自动化和基础设施数字化的投资不理想。特别是，当这两种技术互补时，服务提供商不愿意投资数字基础设施，汽车制造商倾向于过度装备车辆，以避免依赖基础设施技术。因此，我们的结论是，汽车制造商和服务提供商之间更好的协调-以利润分享的形式-是福利改善，并可能产生社会最佳水平的自动化和数字化。
The current approach to driving automation has been primarily vehicle-centric. However, a vehicle-infrastructure cooperative approach, in which infrastructure and vehicles cooperate to perform the different driving tasks, may prevail in enabling automated driving. This paper conducts an economic analysis of vehicle infrastructure cooperation for automated driving. In doing so, we present a model that captures investment decisions in vehicle automation and infrastructure digitalization and their effect on travelers’ purchase and travel decisions. Our analysis shows that, under certain conditions, equipping both infrastructure and vehicles is socially optimal. However, by analyzing strategic interactions between infrastructure support service providers and automakers, we show that lack of coordination between these two actors results in suboptimal investment in vehicle automation and infrastructure digitalization. Especially, when these two technologies are complementary, service providers are reluctant to invest in digital infrastructure and vehicle manufacturers tend to over equip their vehicles so as to avoid relying on infrastructure technology. Thus, we conclude by showing that better coordination between automakers and service providers – under the form of profit sharing – is welfare-improving and could potentially yield the socially optimal levels of automation and digitalization.