Abstract
Household traffic surveys are widely used in travel behavior analysis, especially in travel time and distance analysis. Unfortunately, any one kind of household traffic surveys has its own problems. Even all household traffic survey data is accurate, it is difficult to get the trip routes information. To our delight, electric map API (e.g., Google Maps, Apple Maps, Baidu Maps, and Auto Navi Maps) could provide the trip route and time information, which remedies the traditional traffic survey’s defect. Thus, we can take advantage of the two kinds of data and integrate them into travel behavior analysis. In order to test the validity of the Baidu electric map API data, a field study on 300 taxi OD pairs is carried out. According to statistical analysis, the average matching rate of total OD pairs is 90.74%, which reflects high accuracy of electric map API data. Based on the fused data of household traffic survey and electric map API, travel behavior on trip time and distance is analyzed. Results show that most purposes’ trip distances distributions are concentrated, which are no more than 10 kilometers. It is worth noting that students have the shortest travel distance and company business’s travel distance distribution is dispersed, which has the longest travel distance. Compared to travel distance, the standard deviations of all purposes’ travel time are greater than the travel distance. Car users have longer travel distance than bus travelers, and their average travel distance is 8.58km.
Highlights
It is axiomatic that a model can never be better than the data from which it is estimated [1]
Household traffic surveys are mainly used in transport planning and urban planning
Household traffic surveys are customarily conducted by telephone, face-to-face interviewing, having become expensive and dangerous to accomplish in most urban areas of the continent [2]
Summary
It is axiomatic that a model can never be better than the data from which it is estimated [1]. In order to overcome the shortfall in trips of CATI [3, 4], some countries, such as the US and Switzerland, try to have a household traffic surveys using GPS location devices [5–9]. In order to cast off the deficiency of one kind traffic survey method, several traffic survey methods are used to reap the accurate traffic data in Qingdao’s third traffic survey (2016) They include online-survey, face-to-face interviewing, public transport survey, traffic flow survey, exit-entry survey, and other surveys (see Section 2).
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