A Method of Vehicle Route Prediction Based on Social Network Analysis. (30th April 2015)
- Record Type:
- Journal Article
- Title:
- A Method of Vehicle Route Prediction Based on Social Network Analysis. (30th April 2015)
- Main Title:
- A Method of Vehicle Route Prediction Based on Social Network Analysis
- Authors:
- Ye, Ning
Wang, Zhong-qin
Malekian, Reza
Zhang, Ying-ya
Wang, Ru-chuan - Other Names:
- Cao Jian-Nong Academic Editor.
- Abstract:
- Abstract : A method of vehicle route prediction based on social network analysis is proposed in this paper. The difference from proposed work is that, according to our collected vehicles' past trips, we build a relationship model between different road segments rather than find the driving regularity of vehicles to predict upcoming routes. In this paper, firstly we depend on graph theory to build an initial road network model and modify related model parameters based on the collected data set. Then we transform the model into a matrix. Secondly, two concepts from social network analysis are introduced to describe the meaning of the matrix and we process it by current software of social network analysis. Thirdly, we design the algorithm of vehicle route prediction based on the above processing results. Finally, we use the leave-one-out approach to verify the efficiency of our algorithm.
- Is Part Of:
- Journal of sensors. Volume 2015(2015)
- Journal:
- Journal of sensors
- Issue:
- Volume 2015(2015)
- Issue Display:
- Volume 2015, Issue 2015 (2015)
- Year:
- 2015
- Volume:
- 2015
- Issue:
- 2015
- Issue Sort Value:
- 2015-2015-2015-0000
- Page Start:
- Page End:
- Publication Date:
- 2015-04-30
- Subjects:
- Detectors -- Periodicals
681.205 - Journal URLs:
- https://www.hindawi.com/journals/js/ ↗
- DOI:
- 10.1155/2015/210298 ↗
- Languages:
- English
- ISSNs:
- 1687-725X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 10795.xml