Abstract
The problem of optimally locating sensors on a traffic network has been object of growing interest in the past few years. Sensor location decisions models differ from each other according to the type of sensors that are to be located and the objective that one would like to optimize. In this paper, we survey the main existing contributions in the literature related to the optimal location strategies of Automatic Vehicle Identification (AVI) readers on the links of a network to get travel time information.
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Acknowledgements
The authors thank Dr. Yang He, former Ph.D. student of the second author, for the computational results. The authors acknowledge the partial support from TranStar, Houston, Texas and USDOT support to the ATLAS Center, University of Arizona. The authors also acknowledge support from National Science Foundation Grant n.1234584. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the above mentioned agencies. Finally, the authors thank the co-editors of this book for inviting them to provide this contribution for their timely book.
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Gentili, M., Mirchandani, P. (2015). Locating Vehicle Identification Sensors for Travel Time Information. In: Eiselt, H., Marianov, V. (eds) Applications of Location Analysis. International Series in Operations Research & Management Science, vol 232. Springer, Cham. https://doi.org/10.1007/978-3-319-20282-2_13
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DOI: https://doi.org/10.1007/978-3-319-20282-2_13
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