Abstract
Identifying flow patterns from massive trajectories of car tourists is considered a promising way to improve the management of tourism traffic. Previous researches have mainly focused on tourist movements at the macro-scale, such as inbound, domestic, and urban tourism using flow maps. Compared with modeling the flow patterns of tourists at the macro-scale, modeling tourist flow at the microscale is more complicated. This paper takes Dapeng Island located in Shenzhen as the study area and uses the car recognition devices to collect traffic flow. Firstly, car tourists are separated from the mixed traffic flow after analyzing the spatial-temporal characteristics of tourists and residents. Next, daily graphs of tourist movements between road segments and tourist attractions are constructed. Finally, a frequent subgraph mining algorithm is used to extract the flow patterns of car tourists. The experimental results show that (1) car tourists have obvious preferences in the selection of trip time and tourist attractions; (2) the intercity tourists tend to take multidestination trips rather than a single destination trip in the same type of attractions; (3) car tourists are inclined to park their cars in an easy-to-access place, even if the attractions visited are changed. The main contribution of this paper is to present a new method for discovering the flow patterns of car tourists hidden in massive amounts of license plate data.
Highlights
IntroductionDue to the flexibility and convenience of road transportation, car-based tourism (travel in owned or rented cars, named driving tours [1], car tourism [2], and selfdriving tours [3]; for simplicity, this paper uses the term car tourism) has been one of the popular forms for leisure and recreation
Due to the flexibility and convenience of road transportation, car-based tourism has been one of the popular forms for leisure and recreation
E proposed approach is outlined in Figure 3. is section introduces the detailed steps for the mining of frequent flow patterns of car tourists at the microscale in a tourist intradestination
Summary
Due to the flexibility and convenience of road transportation, car-based tourism (travel in owned or rented cars, named driving tours [1], car tourism [2], and selfdriving tours [3]; for simplicity, this paper uses the term car tourism) has been one of the popular forms for leisure and recreation. Car tourism has been growing rapidly in China, and its scale is continuing to expand with the improvement of road infrastructure and the growth of car ownership. A statistical report indicated that by 2015, there were 2.34 billion car tourists in China, accounting for more than 58.5% of the total domestic tourists [4]. It can be foreseen that the percentage of car tourists will increase over time. Car tourists need to share roads in urban areas or tourist attractions with residents, and they depend on the road network to achieve circulation between the places of origin and multiple tourist attractions. When a large number of tourist cars enter the road network during peak tourist season, the pressure on road traffic management may be increased. It is worth noting that this phenomenon is severe for coastal tourist attractions
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
