Vehicle trajectory reconstruction from automatic license plate reader data
Using perception data to excavate vehicle travel information has been a popular area of study. In order to learn the vehicle travel characteristics in the city of Ruian, we developed a common methodology for structuring travelers’ complete information using the travel time threshold to recognize a s...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2018-02-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/1550147718755637 |
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| Summary: | Using perception data to excavate vehicle travel information has been a popular area of study. In order to learn the vehicle travel characteristics in the city of Ruian, we developed a common methodology for structuring travelers’ complete information using the travel time threshold to recognize a single trip based on the automatic license plate reader data and built a trajectory reconstruction model integrated into the technique for order preference by similarity to an ideal solution and depth-first search to manage the vehicles’ incomplete records phenomenon. In order to increase the practicability of the model, we introduced two speed indicators associated with actual data and verified the model’s reliability through experiments. Our results show that the method would be affected by the number of missing records. The model and results of this work will allow us to further study vehicles’ commuting characteristics and explore hot trajectories. |
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| ISSN: | 1550-1477 |