City Maslow Needs Situational Perception Based On Multi-source Travel Data

With the rapid development of social economy and the continuous improvement of people's living standards,the living needs of urban residents have gradually shifted from low-level physiological needs to high-level spiritual needs.Maslow's Hierarchy of Needs Theory divides people's needs into seven different levels.Fully understanding the demand intensity and regional mobility scenarios of urban residents' travel at each level can directly reflect the quality of life and happiness of urban residents.At present,the research on how to perceive Maslow's travel needs of urban residents is not yet mature,but from the perspective of urban multi-source travel data,it can theoretically reflect the Maslow travel needs of urban residents.Therefore,studying the Maslow demand fuzzy mapping model based on multi-source data and the Maslow demand situation perception method for urban areas can effectively solve the problem on difficult to measure the Maslow demand status and variation of residents' travel in the current research field.The potential application value of travel data has certain reference effect for perception of urban residents' living conditions,urban regional service quality,and urban future planning and construction.This paper wants to excavate the crowd dynamics characteristics of urban residents' travel,and study the Maslow demand scenarios of residents' travel in inner urban areas through multi-source travel data.The specific research content includes the following three aspects:(1)Proposed a multi-source travel data OD recovery method based on stay feature and spatial proximity.To convert multi-source travel data into travel OD data in a standardized format and consistent,it is necessary to design suitable processing methods for the conversion of the trajectory and order data from taxis,buses,and subways stored in different formats.For the taxi trajectory data,data cleaning and OD recovery method based on stay feature and space-time span are designed,and the bus OD speculation method based on space-time proximity is designed for bus card swiping data.Experiments show that the above method can effectively convert multi-source travel data into standard OD objects.Compared with the original segmentation method,the number of taxi ODs increases by 20.6%,and the bus OD calculation results are reasonable.(2)Proposed a questionnaire-based fuzzy mapping model of urban residents' travel Maslow demand.The Maslow demand intensity questionnaire was designed for each kind of POI to construct the POI demand hierarchy probability,and then the Maslow demand fuzzy mapping model was constructed by combining the OD set,POI data,and land use type data to calculate the characteristics.The model realizes the calculation of the probability of Maslow's demand hierarchy corresponding to the OD travel of residents.Experiments show that the model can obtain the intensity distribution and proportion of each Maslow demand hierarchy in the city under various travel modes,and the model has a good portability.(3)Proposed a regional-oriented approach to situational awareness of urban residents' travel needs.The Maslow demand fuzzy mapping results calculated by using multi-source OD data,combined with the regional division,determine the definition of the Maslow demand static scenario,spatial-temporal dynamic scenario for singleregion,and regional interaction-oriented scenario definition for the travel of urban residents,and designed the corresponding perception method.Experiments show that the above definitions and perception methods can effectively perceive Maslow's demand changes and interaction scenarios in various regions of the city,and reflect potential problems in urban construction.