Study On Reasonable Traffic Capacity Of Congested Road Based On Network Design Problem

With the continuous acceleration of urbanization level in China,the number of motor vehicle ownership of urban residents has increased dramatically.So the supply capacity of some urban roads can not meet the actual travel demand.It is easy to form congested roads,and it is difficult to dredge the congestion through effective management and control.Therefore,the research of reasonable traffic capacity of urban congestion road is of great significance to determine the traffic capacity of the reconstructed road and transform the urban congestion road.The reasonable traffic capacity of the congested road can not only satisfy the needs of the Resident,but also avoid the overload of the surrounding road in the road network.In the study of the reasonable traffic capacity of congested roads under the current road network and social environment,the upper limit of traffic capacity increase value for congested roads is studied.And the maximum vehicle arrival rate of congested roads is proposed to quantitatively describe this upper bound value.The vehicle arrival rate is different from the measured traffic flow rate on the road,and it can not be obtained through direct observation.Especially when the road is congested,the vehicle can not be evacuated in time after the arrival of the vehicle,and at this time the arrival rate of the vehicle is greater than the measured traffic flow rate.Therefore,the study of the maximum vehicle arrival rate for congested roads needs to be realized by analogy analysis of traffic flow rate around the road network.In order to analyze the trend of change,the article first analyzes the correlation between traffic parameters of congested roads from time and space.That is to say,the frequency of urban road congestion is determine from the time correlation,and the correlation of urban traffic between roads is analyzed from spatial correlation.The acquisition method of high correlation road segments is also discussed.Secondly,the application of big data is introduced to deal with traffic parameters of congested roads and high correlation road segments,and the change trend of congested roads and high correlation road segments is compared.The actual traffic volume of congested roads is corrected by using the effective section of the high correlation road set change trend,and the daily trend curve of the possible vehicle arrival rate on congested roads is obtained by analogy analysis.Finally,the trend derivative is used to segment the daily variation curves,and the polynomial fitting is applied to solve the maximum vehicle arrival rate of congested roads.Based on the quantitative relationship between the vehicle arrival rate and the upper limit of road traffic capacity increase,the upper limit of capacity increase is calculated.The determination of the reasonable traffic capacity of congested roads is an optimal design problem of traffic network,and a bi-level programming model is introduced to solve the problem.1)the upper limit of traffic capacity increase value of congested roads is used as a constraint condition for increasing value of road traffic capacity of the upper model,and the upper level programming model which the minimum total expected impedance of the system is the objective function is established.2)The classic user equilibrium assignment(UE)model is used as a lower level model.3)The genetic algorithm is used to solve the model.This model can satisfy the optimal design of one index of the whole road network system,and can also sensitively reflect the influence of the traffic volume change of a certain section on the whole system.Then the optimal traffic capacity increase value of the congestion road is solved.Finally,a reconstruction case of South Second Ring East section of Xi’an is carried out to verify the proposed method.