Battery electric vehicle transportation network robust pricing-infrastructure location model with boundedly rational travelers

Abstract

With the increasingly stringent energy saving and emission reduction policies of governments, the promotion of battery electric vehicles (BEVs) has emerged as a pivotal sustainable transportation strategy. Consequently, the design of BEV transportation networks has become a current focus of academic attention. This paper investigates a robust pricing-infrastructure location problem for a BEV transportation network considering charging time, BEV drivers' range anxiety and bounded rationality behavior. Furthermore, a robust BEV transportation network pricing–infrastructure location model is developed. The aforementioned model aims to minimize the regional travel time while simultaneously optimizing the lane expansion scheme (i.e., the location and number of expanded lanes) and the pricing scheme (i.e., tolls and subsidies on each link). A heuristic algorithm is developed on the basis of the active set algorithm framework. Numerical experiments are performed on the classical Sioux Falls network. The experimental results can provide useful policy recommendations for the government in formulating a reasonable sustainable transportation strategy.