Route Planning based on Multi-domain UGC and VGI data sources

What is it about?

By utilizing today's web-based technologies, people can act as sensors and share their perceptions, emotions and observations in a variety of data forms, such as images, videos, texts, Global Positioning System (GPS) trajectories and maps. These forms are collectively called user-generated content (UGC). These data are in different domains and have a multi-modality nature. Although recent efforts have probed the acquisition of local knowledge by using single-domain UGC data in specific applications, such efforts have not thus far presented a model considering multi-domain UGC specifically to enrich road network data. This article aims at presenting such a model wherein, with the help of each data domain of UGC, one aspect of people knowledge about the road segment is obtained. These different aspects of knowledge are integrated using a Skyline operator to support multi-criteria route finding. We name this model ERSBU (enriching road segments based on UGC). In ERSBU, road segments are basic spatial units, and their subjective properties have been extracted by using available UGC. The scenic score for each road segment was computed by using geo-tagged Panoramio photos. The accessibility level of each road segment to different facilities was calculated based on data captured from Wikimapia and OpenStreetMap. Moreover, for measuring the movement popularity of each road segment, Wikiloc and Everytrail GPS trajectories were utilized. For the implementation of the ERSBU model, Tehran region 6 was considered the case study area. The Evaluation of the results proved that road segments that achieved a high score based on knowledge extracted from UGC also mostly gained top scores by analyzing traditional maps. ERSBU allows users to accomplish more-qualitative path finding by considering the multi-view characteristics of road segments.

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Why is it important?

1. Utilizing multi-domain user-generated contents to enrich road segments' attributes, 2. Extracting latent characteristics of road segments that are in relation with people perception from surrounding environment, 3. Incorporating different aspects of road segment’s knowledge in the form of skyline query to offer non-dominated routes to users based on their preferences.