Battery Swapping Station Location And Road Capacity Expansion Problem Based On Mixed Flow Network

Environmental pollution and traffic congestion caused by traditional vehicles have become urgent problems to be solved in many cities. With the improvement of people’s living standards, people are gradually aware of the importance of environmental protection. They pay more attention on the environmental problems and hope to live in a comfortable and healthy environment. If charging facilities are sufficient, electric vehicles as a kind of new energy vehicle are regard as a promising substitute for traditional vehicles to meet people’s normal travel needs. More importantly, it can improve the environmental conditions effectively. The research on the hybrid flow network design problem not only provides a perspective to observe the influence of electric vehicles on the operation of traffic network, but also is conducive to the the traffic network design.This paper presents a new continuous network design model to improve transportation network with mixed traffic flows(gasoline vehicles, GVs and electric vehicles, EVs) by expanding some links’ capacities and locating the battery swapping stations(BSSs). The upper level is a model with objective function defined as the sum of total travel time on the network and the total investment cost of link capacity expansions and station locations. The lower level problem is formulated as a certain mixed traffic assignment model with drive range limit. For the proposed model, Particles Swarm Optimization and modified Frank-Wolfe algorithm will be implemented to solve this model. The experiments are illustrated on a test network with 18 links and 9 nodes to carry on the sensitivity analysis of the proportion of EVs, the driving range, the unit expansion cost and the value of time. Through the sensitivity analysis of parameters involved in electric vehicles, the change of the operation state of traffic network and user’s travel behavior will be obtained, which plays a complementary role in the process of making decision about traffic network planning.