Endogenous market penetration dynamics of automated and connected vehicles: Transport-oriented model and its paradox

Abstract

Abstract Automated and connected vehicles (ACVs) have received a great deal of attention. Indeed, their full market penetration will be desirable in terms of traffic efficiency, as ACVs can efficiently drive by precisely and instantaneously communicating, recognizing, and reacting to other ACVs. However, it is not yet certain whether traffic efficiency is improved in mixed traffic where ratio of manual vehicles is substantially high. This is because, for example, ACVs in mixed traffic may require excessive safety clearance, as they have to rely on relatively imperfect vision/radar-based vehicle recognition. Meanwhile, relative benefit of ACVs compared to manual vehicles would be proportional to travel time (because the most significant merit of ACVs for their driver is comfortable in-vehicle experience) and therefore severity of congestion. Consequently, equilibrium states of a myopic car market may suffer severer congestion and higher social cost than the current state—this is congestion paradox. This kind of phenomena can be considered as a consequence of market penetration of a good with network externality or social interaction, where market penetration of ACVs is endogenously determined based on their cost/benefit which depend on current number of ACVs users. This study analyzes this problem under idealized conditions. Specifically, a theoretical model of endogenous market penetration of ACVs considering changes in value of time, travel time, and transportation fare, which are the most direct impacts of ACVs to the society, is formulated. Then, its market dynamics is analyzed. Finally, strategic policies to avoid congestion paradox and achieve social optimum are proposed.