Study On Travel Mode Selection Behavior Of Online Ride-hailing Users Based On Family Income

Travel is closely related to the daily life of residents.Online ride-hailing,as a new mode of travel,provides residents with diversified and multi-level travel options.But for the travelers,the family income level has a great influence on the travelers’ travel mode choice behavior.Income is considered to be an important determinant of urban residents’ travel behavior.The study of travel behaviors of different family income groups(low,medium and high)and the comparative analysis of travel behaviors of different family income groups can provide a more accurate understanding of travel characteristics of different income groups and provide valuable insights for their travel behaviors.Therefore,this article based on the background of urban transportation,in 2019,dalian enterprise survey data about car users,based on the utility maximization theory to build the whole samples of MNL model and ML model,through the comparison and analysis,finally choose ML model considering different family income net about car user groups of travel mode choice behavior research,The factors influencing the travel choice of online ride-hailing users with different family incomes were compared and analyzed.The main contents of this paper include:(1)Study the influencing factors of travelers’ travel mode choice behavior,and summarize the relevant theories of Logit model.(2)A questionnaire combining SP and RP was designed.Data were collected through questionnaire survey.At last,a descriptive analysis was conducted on the collected questionnaire data.(3)The MNL model and ML model of the whole sample were constructed,and the results were compared and analyzed.On net about car user defined groups of different family income,build ML model,analysis the influence factors of different family income group travel choice and action rule,and then express travel time and travel cost for the elastic analysis,finally to express different family income group discount or premium to the share rate prediction.In this paper,Nlogit software is used to solve the problem,and the study shows that the ML model is more reliable.Network about car users of different family income groups in age,level of education,occupation,marital status,whether to have a car and a personal social life satisfaction,travel cost,travel time,express use frequency,the purpose of the travel have strict on the arrival time requirements,discount,transit showed obvious difference.In the elastic analysis,for different family income groups,the reduction of express travel time is more attractive than the reduction of travel cost.The results show that the increase and decrease of express discount have no significant effect on the high income families,but have significant effect on the low income families and the middle income families.There are obvious changes of express premium for high income families,and relatively small changes for low and middle income families.According to the analysis of travel behavior of different family income groups,this paper puts forward some policy suggestions on online car-hailing.