Travel Choice Behavior Research On Online Car-hailing Users Considering Group Differences

With the rapid development of Internet technology,there is a upsurge of online car Hailing.Online car Hailing is not only convenient to take a taxi,but also has favorable price.The new form of using online car Hailing platform to release travel information for online car Hailing is favored by many travelers,especially the young and middle-aged groups,which well meets people’s travel needs,significantly improves the overall service quality and level,and has become an important way for people to travel in the urban transportation system However,its rapid development has increased the number of vehicles on the road,which makes the already tense traffic environment further aggravate the urban traffic congestion.Therefore,in the context of urban transportation travel,this paper starts from the micro field of personal travel mode selection,based on the survey data of Dalian network car hailing in 2018,constructs MNL model and NL model for multi-dimensional comparative analysis,and finally selects NL model to study the travel choice behavior of network car Hailing users considering group differences.The survey data are divided into groups with private cars and groups without private cars.NL models are constructed for male and female groups respectively to explore the travel characteristics of different groups’ traffic mode selection behaviors,and to better understand the role of online car hailing in the transportation system.The main conclusions of this study are as follows:(1)With the gradual development of network car hailing and occupying part of the market,it has become an indispensable way of travel for urban transportation.Most of the people are willing to travel by car.In addition,it also reflects the expectation of Dalian network car Hailing users for the improvement of network car Hailing service level.(2)Based on the NL model,using MNL modeling did not find the preference of 18-30year-old youth groups for private cars,and did not capture the impact of 31-40 year-old middle-aged groups on online taxis and private cars.It captures whether the impact of owning a car on the express train is not statistically significant,and finds the preference of the car ownership group for the subway,and the people’s preference for online taxis,private cars and subways during peak travel.(3)In the two models with or without private car groups considering group differences,there are significant differences in age,family income,civil servants,management technicians,peak travel,and whether there is strict arrival time requirements for travel purposes,male and female The two models of the group differ in the significance of age,whether they have a car,civil servants,management technicians,and peak travel.(4)Conduct an elastic analysis on the travel time and travel costs of express trains to clarify the impact of their changes on the travel structure.Prediction of the share rate ofexpress train premium,the results show that when the express train premium increases,the use of other modes of transportation will increase.