Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10352149 | Computers, Environment and Urban Systems | 2012 | 12 Pages |
Abstract
⺠Inferring transportation mode from GPS data without user information or context assumptions. ⺠Speed and acceleration are the variables with the highest mode discriminatory power. ⺠Transportation mode inference is based on a moving window SVM classification. ⺠GPS trips segmented into single-mode stages to preserve classification cohesiveness. ⺠Our model achieves 88% mode classification accuracy with both variables combined.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Adel Bolbol, Tao Cheng, Ioannis Tsapakis, James Haworth,