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An Accurate Multi-sensor Multi-target Localization Method for Cooperating Vehicles

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Theoretical Information Reuse and Integration

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 446))

Abstract

Accurate and reliable vehicle localization is a key component of Intelligent Transportation System (ITS) applications. Personalized travel related services and recommendation systems like collision avoidance rely principally on the accurate and reliable knowledge of vehicles’ positioning. In this paper we propose a cooperative multi-sensor multi-vehicle localization method with high accuracy for terrestrial consumer vehicles. Two streams of real-time data are assumed available. One in the form of GPS coordinates of nearby vehicles received from a vehicle-to-vehicle (V2V) network and the other in the form of inter-vehicle distance measurements from a range sensor. In real-world situations, these heterogeneous sources of information are noisy and could be unavailable during short intervals. To overcome the effect of noise, measurements from two sources are fused together to estimate the number and motion model parameters of the vehicles. The problem is formulated in the context of Bayesian framework and vehicle locations as well as their velocities are estimated via a Sequential Monte-Carlo Probability Hypothesis Density (SMC-PHD) filter. To test the effectiveness of the proposed approach, a simulated scenario based on a grid portion of downtown Calgary is designed. Traffic intensity values match real-world reported data for the selected test location. Results of the simulation indicate that the proposed method provides reliable estimation of motion model parameters that predict the future location of vehicles.

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Acknowledgments

This work is partially supported by Alberta Innovative Technology Futures (AITF), Calgary, AB, Canada.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, University of Calgary, Calgary, Canada

    Sepideh Afkhami Goli, Behrouz H. Far & Abraham O. Fapojuwo

Authors
  1. Sepideh Afkhami Goli
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  2. Behrouz H. Far
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  3. Abraham O. Fapojuwo
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Corresponding authors

Correspondence to Sepideh Afkhami Goli or Behrouz H. Far .

Editor information

Editors and Affiliations

  1. d'Informatique, Ecole Nationale Supérieure, Alger, Algeria

    Thouraya Bouabana-Tebibel

  2. Code 71730, BS, SPAWAR Systems Center Pacific, San Diego, California, USA

    Stuart H. Rubin

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© 2016 Springer International Publishing Switzerland

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Goli, S.A., Far, B.H., Fapojuwo, A.O. (2016). An Accurate Multi-sensor Multi-target Localization Method for Cooperating Vehicles. In: Bouabana-Tebibel, T., Rubin, S. (eds) Theoretical Information Reuse and Integration. Advances in Intelligent Systems and Computing, vol 446. Springer, Cham. https://doi.org/10.1007/978-3-319-31311-5_9

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  • DOI: https://doi.org/10.1007/978-3-319-31311-5_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-31309-2

  • Online ISBN: 978-3-319-31311-5

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