Research On Reversible Lane Setting Of The Highway Reconstruction And Expansion Work Zone Considering Carbon Emission Factor

The highway reconstruction and expansion work zones as construction and maintenance and upgrading activities,often close part of the lane to ensure normal construction,resulting in traffic congestion and frequent acceleration and deceleration of vehicles and other phenomena,resulting in the general driving time of vehicles become longer,the vehicle exhaust carbon emissions increased dramatically.This not only reduces the efficiency of vehicle traffic but also brings about greater energy consumption and pollution.Based on the above background,this paper takes the setting of reversible lanes in the opposite direction of the work zone as the entry point of the study,constructs a bi-level programming model with the lowest total system travel cost and the lowest total system carbon dioxide emission cost as the optimization objective,designs a quantum particle swarm solution algorithm,and obtains the reversible lane setting scheme under three typical closed forms of the highway work zone by solving the model through macroscopic simulation.The effectiveness of the corresponding reversible lane setting schemes is verified by microscopic simulation.The main research contents of this paper are as follows:（1）A bi-level programming model considering the factor of vehicle carbon emissions is constructed.The traditional bi-level programming model only considers the element of travel cost of the system road network,but this paper further considers the cost of vehicle carbon dioxide emission in the system road network based on the consideration of travel cost.The bi-level programming model with the introduction of the CO₂ emission model is constructed,and the objective of reversible lane setting in this model is to minimize the sum of total system travel time and total system CO₂ emission.The richness and multiplicity of the bi-level programming model are enhanced,and the optimization of the system road network is realized from two dimensions operational efficiency and energy saving and emission reduction.（2）A quantum particle swarm solution algorithm with a nested Frank-Wolfe algorithm is designed.Compared with other common intelligent optimization algorithms,the quantum particle swarm optimization algorithm converges faster and has higher intelligence.With the objective function of minimizing the total travel time cost and the total CO₂ emission cost of the system and different lane allocation methods as the independent variables,the quantum particle swarm algorithm is used to solve the upper model of the bi-level programming model and the Frank-Wolfe algorithm to solve the lower model of the bi-level programming model.The computational efficiency is effectively improved while ensuring the reliability of the solution algorithm.（3）A lane optimization scheme for the work zone of highway reconstruction and expansion is proposed.With the help of the classical Sioux Falls road network parameters,macroscopic simulation experiments are carried out for three typical closure forms of seven two-way six-lane highway sections in the road network where the work zones can be set,taking into account the differences in the operation and emission characteristics of two types of typical vehicles:large trucks and small cars,from both macroscopic and microscopic simulations.According to the experimental results,the best reversible lane setting scheme is given for each of the three typical closure forms to verify the effectiveness and credibility of the optimized scheme are further simulated through microscopic simulation to achieve the optimal configuration of lanes in each road section.The research results of this paper can significantly reduce the total system travel cost and CO₂ emissions,improve the utilization of road resources,and alleviate the potential congestion and pollution hazards due to highway reconstruction and expansion.It further provides a valuable reference solution for traffic management and control in the future and makes a useful exploration for improving the operational efficiency of the road traffic network and promoting the green and sustainable development of the transportation system.