Classifying pedestrian movement behaviour from GPS trajectories using visualization and clustering
نویسندگان
چکیده
منابع مشابه
Classifying pedestrian movement behaviour from GPS trajectories using visualization and clustering
The quantity and quality of spatial data are increasing rapidly. This is particularly evident in the case of movement data. Devices capable of accurately recording the position of moving entities have become ubiquitous and created an abundance of movement data. Valuable knowledge concerning processes occurring in the physical world can be extracted from these large movement data sets. Geovisual...
متن کاملLearning Pedestrian Profiles from Movement Trajectories
Pedestrians are highly heterogeneous with regards to their physical capabilities and preferences, which in turn determine their individual infrastructural needs (Saelens et al. 2003, Millonig 2006). Other than in current pedestrian navigation systems, therefore, the possibility to compute personalized walking routes would be desirable, a precondition of which, however, is to derive detailed use...
متن کاملInterpreting Pedestrian Behaviour by Visualising and Clustering Movement Data
Recent technological advances have increased the quantity of movement data being recorded. While valuable knowledge can be gained by analysing such data, its sheer volume creates challenges. Geovisual analytics, which helps the human cognition process by using tools to reason about data, offers powerful techniques to resolve these challenges. This paper introduces such a geovisual analytics env...
متن کاملDetecting Anomalous Trajectories and Behavior Patterns Using Hierarchical Clustering from Taxi GPS Data
Anomalous taxi trajectories are those chosen by a small number of drivers that are different from the regular choices of other drivers. These anomalous driving trajectories provide us an opportunity to extract driver or passenger behaviors and monitor adverse urban traffic events. Because various trajectory clustering methods have previously proven to be an effective means to analyze similariti...
متن کاملCitySense: multiscale space time clustering of GPS points and trajectories
A generalized scan statistic is provided for periodic geographic surveillance of various measures of city-wide activity. The resulting algorithms scan for both elliptical and rectangular clusters and can be optionally adjusted for covariates such as time-of-day, day-of-week or season. An empirical Bayes procedure is used to account for parameter uncertainties in the framework. Additionally, sca...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Annals of GIS
سال: 2014
ISSN: 1947-5683,1947-5691
DOI: 10.1080/19475683.2014.904560