Dynamic pricing for integrated energy-traffic systems from a cyber-physical-human perspective

Abstract

This paper solves the vehicle assignment problem of an operating entity with dispatchable vehicles (e.g., an urban Integrated Energy-Traffic System (IETS) coordinator or an e-hailing company) in the context of energy-traffic coordinated modeling and analysis. Current research on electric vehicle (EV) scheduling and optimization has broadly assumed that human beings are rational decision-makers and obey the scheduling plan. In contrast, we proposed a user-centric dynamic pricing scheme that improves the system performance by incentivizing human participants to follow the expected behavioral patterns from a Cyber-Physical-Human System (CPHS) perspective. The interdisciplinary fields of power systems, traffic systems, and human decision-making were used to study the interactions in the CPHS. The proposed incentive scheme was applied to the urban IETS scenarios based on real-world Global Positioning System (GPS) data of EV taxis, and the results showed that it effectively optimized the integrated system.