Optimal lane expansion model for a battery electric vehicle transportation network considering range anxiety and demand uncertainty

摘要: Abstract This paper investigates a novel design problem involving an optimal government lane expansion scheme for battery electric vehicle (BEV) transportation network. A model is established considering the BEV charging time, driver range anxiety and uncertain demand. aims to minimize total travel time (i.e., sum of driving time) all drivers in network optimize number location extended lanes network) under investment ceiling. To address demand uncertainty, improved adjustable robust optimization method further proposed relax by introducing two control parameters. Based on framework active set algorithm, local solution algorithm designed effectively solve abovementioned model. Column generation embedded above avoid path enumeration. Sensitivity analyses are conducted different parameters scales. The results show that we can provide theoretical basis improve traffic efficiency achieve goal sustainable transport.