A Combined Trip Generation And Distribution Model Based On Trip Chain Of Typical Travelers And Software Design

Traffic demand forecasting is an important content in urban transportation planning.As the basic link of the whole traffic demand forecast,the research of the forecast method of the trip generation and distribution is always an important research field of traffic planning.At present,China’s major cities use the four-stage method to establish land use-transport relationship model.As a typical disaggregate model of four distinct phases method,the method is easy to understand,but it ignores the effects of traveler’s own social and economic attributes on the travel.Travel behavior analysis method based on activity,based on the disaggregate model,focuses on the individual travel data,make up for the deficiency of the four stage method at the micro level.However,due to the excessive number of variables involved,the model calibration and software development of the method is difficult,which limits the application of this method in actual traffic planning of engineering practice.Therefore,the research about how to combine the traditional four phases forecast method with the travel behavior analysis method based on activity,establish the trip generation and distribution model and guide the traffic planning of engineering practice is of great significance.Based on the National Natural Science Fund Project(51338003、71771049),the paper focused on the reality of urban traffic development and the requirement of the engineering practice in China.Firstly,we use Jiangning district of Nanjing city as an example,on the basis of traffic zone classification,a resident travel database was established according to the trip survey data,and then we extracted the trip chain data,and qualitatively analyzed the characteristics of trip chains of workers,non-workers and students in different types of traffic zones.On the basis of qualitative analysis of characteristics of the trip chains,the paper further explored the key factors influencing the travel chain type of three kinds of people(workers,non-workers and students): workers are mainly influenced by six factors,including gender,age,occupation,with or without a car,family children number and family car number;non-workers are mainly influenced by three factors,including gender,with or without a car and family children number;students are mainly affected by traffic zone type.Based on the key influencing factors,the three groups were further classified in each type of zone,and the typical groups with similar travel characteristics were obtained.We used worker as an example to build the combined generation and distribution model based on the trip chain of typical travelers.In the process of modeling,we used the point of interest data to accurately depict the zone attraction intensity for different travel purposes.On this basis,7 zones in Jiangning district was choosed to verify the proposed model,the predicted results was consistent with the actual situation.Finally,based on the combined generation and distribution model,the Visual C++ programming language was used to realize the function of combined forecast of trip generation and distribution stages in the "TranStar" platform,promoting the applied value of this paper.The research results will provide useful technical ideas and implementation means for the establishment of the combined trip generation and distribution model that conforms to our country’s resident travel characteristics and combines the macro and micro level.Furthermore,the research will provide support for urban traffic system planning and decision making,as well as help to further promote the research results in practical application.