A Sensor-Data-Driven Proactive Accident Detection and Traffic Prediction Method Based on Lane-Level Grid Partitioning and a Three-Dimensional Markov Model.
- DOI
- 10.3390/s26175594
- Published
- 2026 Sep 3
- Container
- Sensors (Basel, Switzerland)
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3390/s26175594,
title = {A Sensor-Data-Driven Proactive Accident Detection and Traffic Prediction Method Based on Lane-Level Grid Partitioning and a Three-Dimensional Markov Model.},
author = {Zeng M and Chen H},
year = {2026},
journal = {Sensors (Basel, Switzerland)},
doi = {10.3390/s26175594},
url = {https://doi.org/10.3390/s26175594}
}RIS
TY - JOUR TI - A Sensor-Data-Driven Proactive Accident Detection and Traffic Prediction Method Based on Lane-Level Grid Partitioning and a Three-Dimensional Markov Model. AU - Zeng M AU - Chen H PY - 2026 JO - Sensors (Basel, Switzerland) DO - 10.3390/s26175594 UR - https://doi.org/10.3390/s26175594 ER -
APA
M, Z., & H, C. (2026). A Sensor-Data-Driven Proactive Accident Detection and Traffic Prediction Method Based on Lane-Level Grid Partitioning and a Three-Dimensional Markov Model.. Sensors (Basel, Switzerland). https://doi.org/10.3390/s26175594
Source records
- pubmed · retrieved 2026-09-25T02:40:20.772Z