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Title: Robust real-time route inference from sparse vehicle position data
Authors: Jagadeesh, George Rosario
Srikanthan, Thambipillai
Keywords: Computer Science Engineering
Issue Date: 2014
Source: Jagadeesh, G. R., & Srikanthan, T. (2014). 2014 IEEE 17th International Conference on Intelligent Transportation Systems (ITSC). Robust real-time route inference from sparse vehicle position data, 296-301.
metadata.dc.contributor.conference: 2014 IEEE 17th International Conference on Intelligent Transportation Systems (ITSC)
Abstract: The ability to correctly infer the route traveled by vehicles in real time from infrequent, noisy observations of their position is useful for several traffic management applications. This task, known as map matching, is efficiently performed through probabilistic inference on a Hidden Markov Model that represents the candidate vehicle states and the transitions between them. In this paper, we present new methods for improving the accuracy and timeliness of existing solutions. We propose assigning the transition probability between a pair of candidate vehicle states by considering the alternative paths present in the context. A discrete route choice model is used to estimate the probability that a driver would choose the path under consideration over the best alternative available. In order to facilitate real-time operation, we present a simple yet effective heuristic to reduce the output latency of the route-inference algorithm with negligible loss of accuracy. Tests conducted with ground truth GPS data from a dense urban region in Singapore show that the proposed techniques outperform the conventional baseline approach.
DOI: 10.1109/ITSC.2014.6957707
Schools: School of Computer Engineering 
Rights: © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [].
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Conference Papers

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