Optimal Model Of Road Pricing In Network Considering Fuel Consumption

With the increasing traffic demand,the efficiency of road network travel is low,and resulting in an increase in energy consumption in the transportation system year by year.Road pricing can effectively regulate the route choice behavior of travelers,optimize the operation efficiency of motor vehicles in the road network,and provide effective solutions for traffic energy consumption problems.This study combines two-stage planning,bi-level programming,uncertain planning,multi-objective optimization and other theoretical methods to consider the fuel consumption factors to propose different charging schemes for different decision-making objectives,which provides feasible strategies for the fair formulation for highway network charging schemes and the system's energy saving and consumption reduction.Firstly,this article analyzes the difference of fuel consumption among different types of vehicles,and the main types of vehicles in the highway network are classified.And proposed a fuel consumption model with random uncertainties of 100 km for multiple models.Combined with the method of network designing and road pricing principle,a two-stage pricing model with minimum fuel consumption for multi-vehicle models is constructed.Among them,the first stage establishes the multi-vehicle minimum fuel consumption network design model with random chance constraint under uncertain conditions,and the second stage establishes the multi-model minimum income charging model with social welfare as the main optimization target based on the equivalent constraint of the first stage,then the stochastic simulation algorithm,random chance constrained linearization algorithm and Frank-Wolfe algorithm are used to solve the model.When the same OD pair chooses different paths for the same vehicle,it has the smallest and equal generalized cost.Therefore,the travel route of the motor vehicle is planned by means of charging,the flow distribution of the road network is adjusted,and the total energy consumption of the system is controlled to achieve the purpose of energy saving and consumption reduction.Then,considering the travel time and the energy consumption of the system,the travel time reliability and energy saving index are proposed.Based on this,a multi-objective optimization model is established,the travel efficiency and energy consumption level of the road network are optimized,and the weighted summation method is adopted to convert multi-objective planning into a single-objective plan as an upper-level model.When different travelers make decisions,the main factors to consider are travel time,fuel cost and road pricing.Based on the analysis of the user's general line expenses,the user equilibrium model under generalized travel cost is established as the lower model.The multi-objective multi-vehicle bi-level charging model is constructed to optimize the performance of the road network,and the algorithm combining genetic algorithm and continuous average method was used to solve the model.Finally,through the calculation and analysis of the abstract highway network,the difference between the travel time,total fuel consumption,user equilibrium and system optimal state of the road network under different charging strategies is compared.The results show that different charging strategies have different impacts on road network energy consumption,but have significant effects on traffic energy optimization.