Abstract
Global Positioning System and other location-based services record vehicles' spatial locations at discrete time stamps. Considering these recorded locations in space with given specific time stamps, this paper proposes a novel time-dependent graph model to estimate their likely space-time paths and their uncertainties within a transportation network. The proposed model adopts theories in time geography and produces the feasible network-time paths, the expected link travel times and dwell times at possible intermediate stops. A dynamic programming algorithm implements the model for both offline and real-time applications. To estimate the uncertainty, this paper also develops a method based on the potential path area for all feasible network-time paths. This paper uses a set of real-world trajectory data to illustrate the proposed model, prove the accuracy of estimated results and demonstrate the computational efficiency of the estimation algorithm.
Original language | English (US) |
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Pages (from-to) | 176-194 |
Number of pages | 19 |
Journal | Transportation Research Part C: Emerging Technologies |
Volume | 66 |
DOIs | |
State | Published - May 1 2016 |
Bibliographical note
Funding Information:The material in this paper is based on research supported by National Science Foundation – United States under Grant No. BCS-1224102 “Measuring the Environmental Costs of Space–time Prisms in Sustainable Transportation Planning”. Appendix A
Keywords
- Dynamic shortest path
- GPS map matching
- Traffic state estimation
- Uncertainty estimation