Effective and Efficient Route Planning Using Historical Trajectories on Road Networks
Summary: DRPK splits a route-planning query by detecting a key segment (KSD) and applies destination-driven planning (DRP), both driven by a directed-association (DA) indicator that encodes inter-segment dependencies from historical trajectories. Achieves SOTA accuracy while being far cheaper to train/run (e.g., 2768 RPQs/s), scalable to large datasets and avoiding heavyweight deep models. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Wei Tian
- 2. Jieming Shi
- 3. Siqiang Luo
- 4. Hui Li
- 5. Xike Xie
- 6. Yuanhang Zou
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,115 | Finding Time Period-Based Most Frequent Path in Big Trajectory Data | 2013 | SIGMOD | 0.00013894562 |
| 2,192 | DITA: Distributed In-Memory Trajectory Analytics | 2018 | SIGMOD | 9.3185895e-05 |
| 3,447 | Effective Travel Time Estimation: When Historical Trajectories over Road Networks Matter | 2020 | SIGMOD | 7.0854131e-05 |
| 4,621 | Diversified Top-k Route Planning in Road Network | 2022 | VLDB | 6.0426586e-05 |
| 5,936 | Efficient and Effective Similar Subtrajectory Search with Deep Reinforcement Learning | 2020 | VLDB | 5.2654071e-05 |
| 7,021 | VRE: A Versatile, Robust, and Economical Trajectory Data System | 2022 | VLDB | 4.8581131e-05 |
| 8,305 | Travel Cost Inference from Sparse, Spatio-Temporally Correlated Time Series Using Markov Models | 2013 | VLDB | 4.5435639e-05 |
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