Research On Multi-mode Trafficnetwork Assignment Based On Bounded Rationality

In order to promote the development of low-carbon traffic and solve the problem of traffic congestion,we can start from the travel behavior of the traveler.This paper first introduces the study of traffic travel behavior decision from urban low-carbon traffic,Mode travel network,which analyzes the basic rational view of bounded rationality and the influencing factors of traveler 's travel behavior decision.And then constructs the hierarchical structure model of the travel mode and path of the multiexploration traffic network.Among them,the rational rationality of the traveler will make the decision based on the reference point,and the traffic flow distribution is formed by the traveler's decision.Finally,the author analyzes the bounded rational behavior of the traveler in the daily travel,constructs the daily dynamic distribution model and provides the solution process.It is proved that the model can reach the equilibrium state of the traffic network by the example analysis and the influence of different parameters on the equilibrium state is analyzed As well as to provide traffic managers to guide travelers travel behavior countermeasures.The main contents and conclusions are as follows:(1)Analyzed the structure of residents' traffic and calculated the total CO2 and emission efficiency of residents traveling in the main city of Chongqing in recent ten years and the sharing of different modes of travel.It is concluded that the increase of the discharge capacity of the residents in the main urban area of Chongqing is the change of the travel structure,the increase of the travel share of the private car and the decrease of the number of passengers.It is suggested that the taxi is a convenient and efficient way of travel,Light rail is the best way to low-carbon travel.(2)Describe the view of bounded rationality.The characteristics of the foreground are mainly reflected in the different risk preferences of income and loss and the importance of small probability events,which will explain the phenomenon of residents' travel in a more accurate and reasonable way.So as to analyze the subjective factors and objective influencing factors of travel behavior through two aspects: personality trait and travel decision-making process.(3)Analyze and construct a hierarchical network model of multi-mode traffic network structure and mode and travel path joint selection.The travel decision is not based on the travel cost(time and cost)size value,but by the travel cost and the corresponding travel mode of the reference point of the difference between the value obtained by the value of the function to replace the utility of the utility theory Select,so as to get the flow distribution of each mode and path.(4)Based on this analysis of the characteristics of traveler's daily travel decisionmaking process,when the trip decision will be affected by the previous travel experience,while travel experience will be accumulated,and in the calculation of the various sections of the mode of running time will travel And the running time of each mode and path.The daily dynamic distribution model of multi-mode traffic network is established,which takes into account the degree of dependence of travel experience and the cognitive error of traveler and is solved by heuristic algorithm.(5)Through the analysis of the example,it is shown that the model can achieve the equilibrium state of the traffic network,in which the probability of arrival of the reference point,the familiarity of the traffic network and the time conversion parameters have a significant effect on the flow distribution under the equilibrium state.The higher the degree of dependence on the travel experience,the higher the traffic network needs to reach the network equilibrium state;the traveler to the traffic network The higher the degree of familiarity,the more rational the choice;the more attention the traveler value of time,the choice of travelers will tend to coherent;crowded costs can effectively promote the development of public transport.