Two Online Map Matching Algorithms Based on Analytic Hierarchy Process and Fuzzy Logic (2402.11866v1)
Abstract: Our aim of this paper is to develop new map matching algorithms and to improve upon previous work. We address two key approaches: Analytic Hierarchy Process (AHP) map matching and fuzzy logic map matching. AHP is a decision-making method that combines mathematical analysis with human judgment, and fuzzy logic is an approach to computing based on the degree of truth and aims at modeling the imprecise modes of reasoning from 0 to 1 rather than the usual boolean logic. Of these algorithms, the way of our applying AHP to map matching is newly developed in this paper, meanwhile, our application of fuzzy logic to map matching is mostly the same as existing research except for some small changes. Because of the common characteristic that both methods are designed to handle imprecise information and simplicity for implementation, we decided to use these methods.
- Edsger W Dijkstra “A note on two problems in connexion with graphs” In Numerische mathematik 1.1 Springer, 1959, pp. 269–271
- EnviroCar “EnviroCar Data” https://envirocar.org/analysis.html?lng=en, 2023
- “A density-based algorithm for discovering clusters in large spatial databases with noise” In kdd 96.34, 1996, pp. 226–231
- Nikolai Gorte, Edzer Pebesma and Christoph Stasch “Implementation of a Fuzzy Logic Based Map Matching Algorithm in R”, 2014
- Joshua S Greenfeld “Matching GPS observations to locations on a digital map” In Transportation Research Board 81st Annual Meeting 22, 2002, pp. 576–582
- Mahdi Hashemi and Hassan A. Karimi “A Machine Learning Approach to Improve the Accuracy of GPS-Based Map-Matching Algorithms (Invited Paper)” In 2016 IEEE 17th International Conference on Information Reuse and Integration (IRI), 2016, pp. 77–86 DOI: 10.1109/IRI.2016.18
- Minoo Jafarlou “Improving Fuzzy-Logic based Map-Matching Method with Trajectory Stay-Point Detection” In arXiv preprint, 2022 arXiv:2208.02881 [cs.LG]
- “Dataset for testing and training map-matching methods” In 2015 IEEE Intelligent Vehicles Symposium (IV 2015) Seoul, South Korea: Zenodo, 2016 DOI: 10.5281/zenodo.57731
- “Deep learning enabled vehicle trajectory map-matching method with advanced spatial–temporal analysis” In IET Intelligent Transport Systems 14.14 Wiley Online Library, 2020, pp. 2052–2063
- “An improvement on the topological map matching algorithm at junctions: a heuristic approach” In International journal of transportation engineering 9.4 Tarrahan Parseh Transportation Research Institute, 2022, pp. 749–761
- “Hidden Markov Map Matching through Noise and Sparseness” In Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems - GIS ’09 Seattle, Washington: ACM Press, 2009, pp. 336 DOI: 10.1145/1653771.1653818
- OpenAI “ChatGPT” chat.openai.com, Version 3.5, 2023
- Washington Y Ochieng, Mohammed A Quddus and Robert B Noland “Map-matching in complex urban road networks” In Brazilian Journal of Cartography (Revista Brasileira de Cartografia) 55.2, 2003, pp. 1–18
- Mohammed A Quddus, Robert B Noland and Washington Y Ochieng “A high accuracy fuzzy logic based map matching algorithm for road transport” In Journal of Intelligent Transportation Systems 10.3 Taylor & Francis, 2006, pp. 103–115
- Mohammed A Quddus, Washington Y Ochieng and Robert B Noland “Current map-matching algorithms for transport applications: State-of-the art and future research directions” In Transportation research part c: Emerging technologies 15.5 Elsevier, 2007, pp. 312–328
- “A general map matching algorithm for transport telematics applications” In GPS solutions 7 Springer, 2003, pp. 157–167
- “Density-based clustering in spatial databases: The algorithm gdbscan and its applications” In Data mining and knowledge discovery 2 Springer, 1998, pp. 169–194
- “A practical guide to an open-source map-matching approach for big GPS data” In SN Computer Science 3.5 Springer, 2022, pp. 415
- “Road reduction filtering for GPS-GIS navigation” In Transactions in GIS 5.3 Wiley Online Library, 2001, pp. 193–207
- Nagendra R Velaga, Mohammed A Quddus and Abigail L Bristow “Developing an enhanced weight-based topological map-matching algorithm for intelligent transport systems” In Transportation Research Part C: Emerging Technologies 17.6 Elsevier, 2009, pp. 672–683
- Nagendra R Velaga, Mohammed A Quddus and Abigail L Bristow “Improving the performance of a topological map-matching algorithm through error detection and correction” In Journal of Intelligent Transportation Systems 16.3 Taylor & Francis, 2012, pp. 147–158
- “A low-sampling-rate trajectory matching algorithm in combination of history trajectory and reinforcement learning” In Acta Geodaetica et Cartographica Sinica 45.11, 2016, pp. 1328
- “Fast map matching, an algorithm integrating hidden Markov model with precomputation” In International Journal of Geographical Information Science 32.3 Taylor & Francis, 2018, pp. 547–570 DOI: 10.1080/13658816.2017.1400548
- “Bdd100k: A diverse driving dataset for heterogeneous multitask learning” In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, 2020, pp. 2636–2645
- Lotfi A Zadeh “Fuzzy logic” In Computer 21.4 IEEE, 1988, pp. 83–93