ABSTRACT
Many geographic information systems applications rely on data provided by user devices in the road network, including traffic monitoring, driving navigation, and road closure detection. The underlying signal is generally collected by sampling locations from user trajectories. The sampling process, though critical for various applications, has not been studied sufficiently in the literature. While the most natural way to sample a trajectory may be to use a frequency based algorithm, e.g., sampling locations every x seconds, such a sampling strategy can be quite wasteful in resources (e.g., server-side processing, user battery) as well as stored user data. In this work, we conduct a horizontal study of various location sampling algorithms (based on frequency, road geography, reservoir sampling, etc.) and assess their trade-offs in terms of the size of the stored data and the induced quality of training for prediction tasks (specifically predicting speeds on road segments).
Supplemental Material
- Quanjun Chen, Renhe Jiang, Chuang Yang, Zekun Cai, Zipei Fan, Kota Tsubouchi, Ryosuke Shibasaki, and Xuan Song. 2020. DualSIN: Dual Sequential Interaction Network for Human Intentional Mobility Prediction. In Proceedings of the 28th International Conference on Advances in Geographic Information Systems (Seattle, WA, USA) (SIGSPATIAL '20). Association for Computing Machinery, New York, NY, USA, 283--292. https://doi.org/10.1145/3397536.3422221Google ScholarDigital Library
- Daniel Delling, Andrew Goldberg, Thomas Pajor, and Renato Werneck. 2011. Customizable Route Planning. In Proceedings of the 10th International Symposium on Experimental Algorithms (SEA'11) proceedings of the 10th international symposium on experimental algorithms (sea'11) ed.) (Lecture Notes in Computer Science). Springer Verlag. https://www.microsoft.com/en-us/research/publication/customizable-route-planning/Google ScholarCross Ref
- Abdeltawab Hendawi, Sree Sindhu Sabbineni, Jianwei Shen, Yaxiao Song, Peiwei Cao, Zhihong Zhang, John Krumm, and Mohamed Ali. 2019. Which One is Correct, The Map or The GPS Trace (SIGSPATIAL '19). Association for Computing Machinery, New York, NY, USA, 472--475. https://doi.org/10.1145/3347146.3359099Google ScholarDigital Library
- Weiwei Jiang and Jiayun Luo. 2021. Graph Neural Network for Traffic Forecasting: A Survey. CoRR , Vol. abs/2101.11174 (2021). arxiv: 2101.11174 https://arxiv.org/abs/2101.11174Google Scholar
- Kostas Kollias, Arun Chandrashekharapuram, Lisa Fawcett, Sreenivas Gollapudi, and Ali Kemal Sinop. 2021. Weighted Stackelberg Algorithms for Road Traffic Optimization. In Proceedings of the 29th International Conference on Advances in Geographic Information Systems (Beijing, China) (SIGSPATIAL '21). Association for Computing Machinery, New York, NY, USA, 57--68. https://doi.org/10.1145/3474717.3483652Google ScholarDigital Library
- John Krumm. 2022. Maximum Entropy Bridgelets for Trajectory Completion. In Proceedings of the 30th International Conference on Advances in Geographic Information Systems (Seattle, Washington) (SIGSPATIAL '22). Association for Computing Machinery, New York, NY, USA, Article 79, bibinfonumpages8 pages. https://doi.org/10.1145/3557915.3561015Google ScholarDigital Library
- Bureau of Public Roads. 1964. Traffic assignment manual. US Department of Commerce.Google Scholar
- OpenStreetMap contributors. 2017. Planet dump retrieved from https://planet.osm.org . https://www.openstreetmap.org.Google Scholar
- Salman Ahmed Shaikh, Hiroyuki Kitagawa, Akiyoshi Matono, and Kyoung-sook Kim. 2022. TStream: A Framework for Real-Time and Scalable Trajectory Stream Processing and Analysis. In Proceedings of the 30th International Conference on Advances in Geographic Information Systems (Seattle, Washington) (SIGSPATIAL '22). Association for Computing Machinery, New York, NY, USA, Article 30, bibinfonumpages4 pages. https://doi.org/10.1145/3557915.3560964Google ScholarDigital Library
- Ali Kemal Sinop, Lisa Fawcett, Sreenivas Gollapudi, and Kostas Kollias. 2021. Robust Routing Using Electrical Flows. In SIGSPATIAL '21: 29th International Conference on Advances in Geographic Information Systems, Virtual Event / Beijing, China, November 2--5, 2021, Xiaofeng Meng, Fusheng Wang, Chang-Tien Lu, Yan Huang, Shashi Shekhar, and Xing Xie (Eds.). ACM, 282--292.Google Scholar
Index Terms
- Efficient Location Sampling Algorithms for Road Networks
Recommendations
Efficient sampling: application to image data
PAKDD'05: Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data MiningSampling is an important preprocessing algorithm that is used to mine large data efficiently. Although a simple random sample often works fine for reasonable sample size, accuracy falls sharply with reduced sample size. In kdd'03 we proposed ease that ...
Line segment sampling with blue-noise properties
Line segment sampling has recently been adopted in many rendering algorithms for better handling of a wide range of effects such as motion blur, defocus blur and scattering media. A question naturally raised is how to generate line segment samples with ...
Efficient maximal poisson-disk sampling
We solve the problem of generating a uniform Poisson-disk sampling that is both maximal and unbiased over bounded non-convex domains. To our knowledge this is the first provably correct algorithm with time and space dependent only on the number of ...
Comments