Non-cooperating vehicle tracking in VANETs using the conditional logit model

Vehicular Ad Hoc Networks (VANETs) are widely considered as indispensable elements of the future intelligent transportation systems that are aiming to apply information and communications technologies to improve transportation safety and quality of experience. The authors present their take on a relatively unexplored problem, exploiting VANETs for on-road surveillance. The proposal is inspired by multi-agent systems intended for surveillance, e.g., a distributed camera network. The authors propose a tracking system composed of three operational modules, namely, localization, tracking data collection and prediction of future locations of a target. Camera equipped onboard units (OBUs) act as remote mobile sensors. Tracking messages are communicated among the OBUs and roadside units (RSUs). These messages are also triggered in the possible locations of the target in a timely manner. Therefore, it is imperative to scope the search to limit the number of OBUs and RSUs involved in the tracking operation, thus, minimizing the number of tracking messages. To this end, a movement modeling technique utilizes the OBU-observations to classify the target's movement pattern to aid future trajectory prediction. In previous work, the authors proposed a Dirichlet-multinomial (D-M) model under the Bayesian estimation framework. In this paper, the authors present newly identified cues towards improving the movement estimation model. The D-M model is constrained to the assumption that all the choice sets are identical across trials. The authors demonstrate that this is almost never the case. The improved model exploits a choice model, called the conditional logit. The conditional logit model is attractive when choice sets vary across trials. Additionally, the authors weight outcome of each trial according to the given choice sets to achieve higher estimation accuracy. The authors evaluate the new model by means of an experimental analysis and compare results with the D-M model.


  • English

Media Info

  • Media Type: Web
  • Features: References;
  • Pagination: pp 626-633
  • Monograph Title: 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013)

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Filing Info

  • Accession Number: 01563464
  • Record Type: Publication
  • ISBN: 9781479929146
  • Files: TRIS
  • Created Date: May 5 2015 10:59AM